Data Driven

In this episode, we turn the microphones on ourselves on more time and ask the questions we ask (almost) all our guests to our favorite data engineer, Andy Leonard.

Andy and I are mourning the loss of a dear friend and mentor, Brian Moran has passed away.

I spoke a few words in his honor and Andy wrote this: https://andyleonard.blog/2021/07/rest-in-peace-brian-moran/

The world is a better place because Brian Moran was in it.

He will be missed.

In this third episode of the fifth season, we turn the microphone onto ourselves and interview one of our own: Frank La Vigne.

This episode was recorded as a livestream on LinkedIn, YouTube, and Twitch. You should consider subscribing to us there, so you can participate in the live Q and A.

In this second episode of the fifth season, Frank and Andy speak to Chris Wexler about using AI to protect the vulnerable.

Speaking of which, I would like to advise you, dear listener, that this show touches on some sensitive areas, namely child sexual abuse materials.

If you have little ears or sensitive persons within listening range, you may want to pause or skip this episode.

00:00:00 BAILey 

Hello and welcome to data driven, the podcast where we explore the emerging fields of data science and artificial intelligence. 

00:00:07 BAILey 

In this second episode of the 5th season, Frank and Andy speak to Chris Wexler about using AI to protect the vulnerable. 

00:00:13 BAILey 

Speaking of which, I would like to advise you, dear listener, that this show touches on some sensitive areas, namely child sexual. 

00:00:20 BAILey 

Abuse materials. 

00:00:22 BAILey 

If you have little ears or sensitive persons within listening range, you may want to pause or skip this episode. 

00:00:28 BAILey 

Don't say we didn't warn you. 

00:00:30 BAILey 

Now on with the show. 

00:00:31 Frank 

Hello and welcome to data driven, the podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. 

00:00:39 Frank 

If you like to think of data as the new oil, then you can think of us as well Car Talk because we focus on where the rubber meets the verb. 

00:00:46 Frank 

Road and with me on this epic virtual road trip down the information superhighway, as always is Andy Lander. How's it going, Andy? 

00:00:54 Andy 

Good Frank, how are you brother? 

00:00:56 Frank 

I'm doing alright, I'm doing alright. We've had a chaotic week at Chateau Lavinia we. We ended up going to Baltimore in the middle of the night on. 

00:01:05 Frank 

Wednesday, wow, so you pick up. 

00:01:06 Andy 

Wow, what was in Baltimore? 

00:01:06 Andy 

What was in Baltimore? 

00:01:09 Frank 

A really good pizza, but mostly we went because there was a situation bad situation where the pit bull that was about to go to a shelter and so we do a lot of fostering and rescuing of dogs. 

00:01:25 Frank 

So we just got her out and we've spent kind of the rest of the week all over our free time trying to find our new home and she landed in the new home on Saturday and she's doing great. So that's. 

00:01:37 Andy 

That's awesome, and it's really it's really awesome y'all do that kind of stuff. 

00:01:41 

Yeah. 

00:01:42 Frank 

Yeah, I always wanted to do it, but it only and it's only been in the last. You know, maybe like 5-10 years I've been able to do it, so we've been doing that. 

00:01:51 Frank 

Cool, the risk of fostering is primarily foster failing. How we we got our current dog count up to five. 

00:01:59 Frank 

Uh, while twelve. That weekend, my wife and I counted it like 12 dogs who kind of come through our house the last two years. Three years. 

00:02:06 Andy 

Nice. 

00:02:07 Frank 

So it's a good thing to do. We have the space to do it and. 

00:02:12 Frank 

You know at the time this one, we didn't know anything about, so we had to kind of keep her isolated. 

00:02:17 Frank 

So we had like this airlock system. She's a super sweetheart with people, but she's kind of iffy around other dogs and she she's super strong. So once she had her mind to do something it takes a lot of effort. 

00:02:18 Andy 

Light. 

00:02:25 

Right? 

00:02:32 Frank 

To corral her. 

00:02:34 Frank 

But she's super happy. She's the only dog in her new home and she has them wrapped around her little paw already, so. 

00:02:42 Frank 

How things go? 

00:02:42 Andy 

That's funny, things are good, you know, pretty quiet weekend. Here we have, uh, it's warmer weather. We're recording this on the Ides of March. 

00:02:54 Andy 

Now debatably, the upwards of March, yes, depending on who you talk to, it's probably the 13th, but I don't, I don't know. 

00:02:54 Frank 

Well, you are smart. 

00:03:02 Andy 

But we're on the 15th of March 2021 and it's starting to warm up. Our greenhouse is is being put to use. 

00:03:11 Andy 

We have some seedlings in there and that's always fun and we've got some raised beds out to the side of the house. Those are. 

00:03:19 Andy 

There's a starting to come. We're starting to see different things come up. They're kind of colder weather crops, so we started assigning couple three weeks ago. 

00:03:29 Andy 

And it's you know it's been nice. I love getting outside and working, especially this time of year. The bugs haven't shown up yet. 

00:03:36 Frank 

So pollen. 

00:03:37 Andy 

The pollen is really low, it's there, but it's really. 

00:03:40 BAILey 

Oh 

00:03:41 Andy 

Yeah. 

00:03:41 Frank 

It hasn't affected me yet, so. 

00:03:43 Andy 

Oh good good yeah. 

00:03:45 Frank 

That 

00:03:47 Andy 

It's good that time is coming, so let's enjoy it while we can. 

00:03:51 Frank 

Oh, I totally agree. There's like 2 weeks a year where the weather in DC is wonderful and this is one of those two weeks so. 

00:03:55 BAILey 

Yes. 

00:03:56 Andy 

That's it, that's it. 

00:03:58 Frank 

Uh, so today we have an awesome guest and and this is, you know, in our in our HR we always talk about where the rubber meets the road in terms of you know how a I can you know how data becomes AI now a I can kind of help businesses and I think this time we have an interesting guest because now we're not just talking about helping AI. 

00:04:18 Frank 

But we're helping society. 

00:04:20 Frank 

Uh, and you know, I'll make sure Bailey has a kind of intro speech that if you have little little ears in the car, you may not. 

00:04:29 Frank 

You may want to listen to this later or listen to this on a headset, because we're going to be talking about human trafficking and all the sorts of horrible things that happen to kids. 

00:04:39 Frank 

And but he's doing some. He's doing some great work in terms of leveraging the power of AI. 

00:04:46 Frank 

To help child sexual abuse materials that are online as well as you know, kind of human trafficking and all the bad things that happen with the technology we like to focus on all the wonderful things. But there's a clearly a large underbelly. 

00:05:06 Frank 

To the Internet and I'm I'm a big believer in transparency because what happens when you I grew up in New York City? 

00:05:16 Frank 

Cockroaches are inevitable no matter what you do. One thing is when the lights come on, they all scatter. So I I think bad things tend to happen in the shadows and you know. 

00:05:29 Frank 

So the more light you turn on, I think the better it is for society as a whole. So with that I'd like to introduce. 

00:05:36 Frank 

Chris Wexler, who is the CEO at Crunch Krenim Craney I. We covered this in the green room. 

00:05:43 Frank 

But 

00:05:44 Chris 

Crew on crew nob. It's OK. 

00:05:46 Andy 

Rudoff crew Nam. There we go. 

00:05:49 Frank 

I I need to drink more coffee in the morning, but Trudeau is in the business of removing what I like this term that he uses digital toxic waste from the Internet and using AI to identify. I never heard this acronym before, but Sicam child sexual abuse materials. 

00:06:09 Frank 

And other awful content to help content moderation and his technology is already in use by law enforcement and is now moving into. 

00:06:21 Frank 

The the private sector and there's a whole bunch of stuff we could talk about, but particularly what's interesting is a for profit startup or social benefit corporation so we can talk about that. 

00:06:32 Frank 

But I like to work so welcome Chris to the show and and thank him for putting up with some of. 

00:06:36 Frank 

The scheduling growing pains that we're having. 

00:06:40 Chris 

Yeah, no. It's it's really great to meet you guys and. 

00:06:43 Chris 

The. 

00:06:43 Chris 

00:06:44 Chris 

I understand having five dogs. I definitely hearing the intro. I understand I like to refer to my house as the event horizon. If an animal comes in, it never gets out, so I I understand. 

00:06:55 Frank 

Ha ha ha ha. 

00:06:58 Frank 

Yeah, we are. Our track record is 5050 so. 

00:07:02 Frank 

Uh, I I tell you that dog was better with other dogs. She would she would she bring what a bit of current president. 

00:07:08 Chris 

Exactly. 

00:07:11 Andy 

Wow. 

00:07:11 Frank 

Wow. 

00:07:11 Frank 

00:07:13 Andy 

So. 

00:07:14 Frank 

How did you? 

00:07:15 Frank 

Get started in this and and and and your name. Uh, how did the name of the company come about? 'cause I think that's an interesting story right there. 

00:07:22 Chris 

Yeah, well kronom is. It's named in honor of a human trafficking child trafficking warrior in Thailand, kronom. Her name is 2 words crude. 

00:07:33 Chris 

Nam was a street artist in Chiang Mai and actually doing very well. Very well renowned. I mean, did a project with the street kids there. 

00:07:42 Chris 

And and said, hey just paint your life and she could not believe what they painted. It was eye opening. 

00:07:51 Chris 

And when she realized that a lot of the karaoke bars in Chiang Mai were fronts for child sexual trafficking, she was compelled to do something. And unlike I think 99.9% of the population, including myself. 

00:08:09 Chris 

She just marched into the. 

00:08:13 Chris 

The karaoke bars and pulled kids out and she had done this 20 times and had twenty kids in her little apartment. When the traffickers came and said, if you do that again, we're going to kill you at, at which point she went north and found a way to do that and has constantly been evolving her tactics. 

00:08:34 Chris 

And what she's done for the last 20 years and now she's saved thousands of kids. One of the first kids she rescued just was one of the first stateless, was the first stateless child in Thailand to graduate from university. 

00:08:48 Chris 

She's just been such an inspiration to us and you know, I think if you go from top to bottom. 

00:08:53 Chris 

In our organization at Kronom, we've. 

00:08:56 Chris 

All been confronted with what's going on in the world and been compelled to change what we're doing to try to help. 

00:09:05 Chris 

Try to help others in the space of human trafficking and so it just made sense to all of us to name the company in her honor. 

00:09:12 

Murmure 

00:09:15 Andy 

Well, we talked a little in the green room about about some of the other organizations you mentioned. Your brother had started a similar organization. 

00:09:22 Chris 

Yeah. 

00:09:24 Chris 

Yeah, he and David Batstone started not for sale back in I think 2006 or 7. 

00:09:33 Chris 

And it was actually started because Kronom reached out to them and said, I've got 40 kids in a field and are lean to burn down. 

00:09:42 Chris 

And you said you might be able to help. So my brother strapped $10,000 to his body to go up to the field and so she could rebuild a space for him. 

00:09:44 Andy 

Extract. 

00:09:52 Chris 

So she even started that organization, but they have since been just bringing innovation to the field of human trafficking. 

00:10:01 Chris 

Left and right, and, uh. 

00:10:05 Chris 

And so it's interesting that. 

00:10:08 Chris 

Kronom was it is a joint venture with a company out of London called Vigil AI, which has largely been in the defense and public safety space. Like really doing proof of concept. 

00:10:25 Chris 

Uh projects, though, like stuff that just you know I the geek in me just gets so excited when I hear what they do. 

00:10:34 Chris 

But, uh. 

00:10:36 Chris 

Vigil AI was one side of it. The other side was just business, which was the venture group that not for sale and non profit started because what we what they realized was that. 

00:10:49 Chris 

The dichotomy of for profit and non profit really didn't work when you're trying to solve really big problems, it's great for direct service, but when you're trying to solve a really big problem. 

00:11:01 Chris 

But 

00:11:01 Chris 

00:11:05 Chris 

Any bit of money that you get comes with, UM comes with a lot of strings as either governmental. Like a lot of a lot of nonprofits are really, you know, pseudo governmental projects or from a large a large foundation that's donating money. So you're constantly changing who you are to keep your funding. 

00:11:16 Andy 

Right? 

00:11:25 Chris 

And what they realized was, well, that you know Dave had a background in venture capital, and so they went and started companies what they like to say is they were A cause in search of a. 

00:11:38 Chris 

And the first one they started was rebel drinks, which if you're ever in homed or not Whole Foods, is is one of the most popular drinks at Whole Foods and around the many other retailers. But it's one of the fastest growing natural drink companies in the history of the US there. 

00:11:58 Chris 

The sole financial partner of velocity. One of the big innovators in the corporate relocation space. And if you're ever in like say, Amsterdam or they just opened up in The Hague. 

00:12:13 Chris 

Dignita, which is a a brunch place that started in Amsterdam that was all about all about giving women who got out of trafficking into the red light district. Training in the hospitality business. And now. 

00:12:32 Chris 

People who go eat there don't even realize it until unless they read. You know the back of the menu because it's the top one of the top rated brunch places in all of Amsterdam. 

00:12:41 Chris 

And so you know, we like to say we we can't do good until we do well. So we're building world class companies. 

00:12:49 Chris 

All built with social justice built into them at the scale of capitalism because it's a powerful tool and that's kind of why we went into. 

00:12:58 Chris 

You know, we decided with AI that that was so important for us because AI is a is a amazing critical tool for the future. 

00:13:09 Chris 

And when you know, particularly in the age of COVID, with all of us behind computer screens and not travel. 

00:13:16 Chris 

The tactics of abuse changed and a lot more was happening online. A huge spike in. See Sam and the reason we say see Sam and that child *********** is that child *********** implies consent and there is none in that situation and so it's child sexual abuse. So that's why we say see Sam. 

00:13:37 Chris 

But as with COVID, what we're seeing is that is a shift of people paying for shows online, or and then they record it, and then they share the image. 

00:13:47 Chris 

And that's a critical. So this is a critical new front. Not even new, but a critical growing front in fighting human trafficking. 

00:13:57 Chris 

And so AI is the best tool to do that. And my background is I I was in the marketing technology side. 

00:14:06 Chris 

Things I I was with some of the largest ad agencies in the world over the last 20 years. 

00:14:12 Chris 

And really was on the other side of it. I was, you know, one of the first customers of Facebook and one of the first customers of Google and constantly evolving my marketing tactics to, you know, sell one more garbage bag or one more motorcycle to a middle aged man and and you know, established. 

00:14:33 Chris 

Data analytics practices to to learn how to do that better and you know eventually that evolved into you. Know AI projects and and what I realized was I could do I mean that that was a a good career, but I could take those skills. 

00:14:50 Chris 

And really make it impact and so that's why I came on board to lead this new joint venture. And so it's a. It's an exciting time for me because. 

00:15:02 Chris 

Uh, I feel like a lot of my like history has been able to kind of come in here and I have the skills that can really help make a difference and so that's why we're doing kruna 

00:15:16 Frank 

Wow, I mean that's there's so much to unpack in there in terms of the AI and kind of the social good. 

00:15:25 Frank 

And. 

00:15:27 Frank 

The detection of this, but the first thing that comes to mind is...

In this episode of Data Driven, Frank and Andy chat with Philadelphia Microsoft Technology Center Data Architect Dave Wentzel on why you do not need a data warehouse.

Also, Frank discusses leaving Microsoft, Frank and Andy talk about five seasons of Data Driven, and even BAILeY has a sentimental moment.

00:00:00 BAILey 

Hello and welcome to data driven, the podcast where we explore the emerging wait a tick. This is the premiere episode of Season Five. Can you believe it? Data driven started four years ago this month. 

00:00:14 BAILey 

Up until last season, we had a human doing the voiceover work. That is until she was replaced by an AI. Yours truly. 

00:00:23 BAILey 

In this episode, Frank and Andy speak to Dave Wensel about why you don't need a datawarehouse. We're starting off the new season with a bit of contrarian tone. 

00:00:33 BAILey 

It's a lively back and forth conversation that runs contrary to prevailing wisdom. Don't say we didn't warn you? Now on with the show. 

00:00:41 Frank 

Hello and welcome to data driven. The podcasts were we wait a minute. We've been saying this Andy for four years now. Can you believe it? 

00:00:48 Andy 

Four years, that's crazy talk. 

00:00:52 Frank 

That's just craziness. So I think when you and I first talked about this and that was that fateful, I think it was December was right after Thanksgiving. But before Christmas, I was thinking about starting a podcast and as a data scientist, I needed someone. 

00:01:01 Andy 

Yeah, yeah. 

00:01:09 Frank 

That was a data engineer that could kind of round out the talent there and and and and obviously I wanted someone I knew, liked, and trust. 

00:01:11 Frank 

Found out. 

00:01:11 Frank 

00:01:22 Frank 

And so it was you. 

00:01:25 Andy 

Well, I'm just glad all of the real smart data engineers you knew were busy. That's all I got to say. 

00:01:25 Frank 

Much. 

00:01:30 Frank 

Ah, no man. You were the first one. I reached out to and the only one I would have done it with it. So I was delighted when you said yes because starting a podcast can sound like a daunting thing, particularly if you haven't done it before. 

00:01:44 Andy 

Yeah, neither one of us really had. And gosh, it's it's worked out. What are we up to? 180,000 downloads or something? I mean that's. 

00:01:52 Frank 

Something. 

00:01:53 Frank 

Like that about hundred 8000 downloads. I mean, we're not Joe Rogan, but that's OK, Yep. 

00:01:55 

Yeah. 

00:01:57 Andy 

No. 

00:01:59 Andy 

Yep, Yep. 

00:01:59 Andy 

Yep. 

00:02:01 Frank 

But you know what, we we we've impacted. I think the community in a significant way. We've we've done a number of things we've we've innovative how we podcast. 

00:02:12 Frank 

Uh, we we've actually managed to keep a good cadence with some exceptions. 

00:02:18 Andy 

Yeah, thanks. 

00:02:19 Frank 

You know, we we finally did earlier this year or late last year, kind of fulfill our vision of it being data driven TV when we actually interviewed guests on. 

00:02:27 Andy 

Yes. 

00:02:32 Frank 

On video. 

00:02:33 Frank 

And that was that actually delayed the launch of the show by about three months. 

00:02:38 Andy 

It did but also uhm. Yeah, that was interesting, but you know it's typical software development, right? You release a feature and then you debug it. The I have this saying about that Frank. All software is tested some intentionally. 

00:02:52 Frank 

Sometimes. 

00:02:53 Andy 

Right? 

00:02:56 Frank 

I love it, but I also like how, how, how both our careers have evolved over the last four years. And dumb, you know, this being the premiere episode of Season 5 and we have something special lined up, but I'll get to that in a minute. 

00:02:58 Andy 

Hello. 

00:03:03 Andy 

Oh gosh, itch. 

00:03:11 Andy 

June. 

00:03:12 Frank 

You've progressed in your career. We, you and I've worked on some some projects together or virtual Summit. What we're calling Ring Gate, which will announce very very soon and and but. But most of all, is been my kind of skilling up in transition into data engineering myself. 

00:03:29 BAILey 

Ehm 

00:03:31 Frank 

Which was something that when I joined, so this is just a job update about a year ago. I I left the role of Microsoft kind of field sales and I went into the Microsoft Technology Center stick with me. There's a point to this story and basically I was at the rest in MTC. 

00:03:52 Frank 

And basically I was the AI guy on my my my field sales team, but I didn't really have deep knowledge of kind of the typical typical data engineering pipe work that goes into that role and basically my my. My then manager said you know he's like hey, you know, if you want this role, you've got a skill. 

00:04:12 Frank 

And skill up I did. And with Andy's mentoring and a bunch of other folks that helped me kind of skill up on our the data engineering side. I looked at it this morning. I'm like 88 hours on Pluralsight. 

00:04:25 Frank 

Wow, that was from mid may till we're recording this on April 30th. So just about a year 88 hours right now tracking on about 200 four 205 consecutive days of getting on LinkedIn. I'm not on LinkedIn on Pluralsight, LinkedIn learning. I also have a number of courses too. 

00:04:31 Andy 

Yeah. 

00:04:43 Frank 

Uh, that is something I'm proud of in terms of career evolution. 

00:04:47 Andy 

Absolutely Frank, you should be. How many cirts are you up to now? 

00:04:50 Frank 

I 87. 

00:04:53 Andy 

Slacker. 

00:04:54 Frank 

I know, I know. 

00:04:54 Frank 

Know, I know. 

00:04:54 Andy 

I think I've got 4. 

00:04:56 Frank 

Ah, now I know you and I did the data engineering thing, so you have at least 11. 

00:05:00 Andy 

That's true, that's true. We did that one and you know that was it's just. It's just been a nice journey and I'll take credit for this. 'cause 'cause I can I was. I was actually pestering you years ago. We've been friends since 2005 and we started doing. 

00:05:20 Andy 

Code camps here in the Richmond area. 

00:05:22 Andy 

Together and co-founded RE co-founded Richmond SQL Server Users Group and you know, worked with the net users group and stuff. And I told you as soon as I saw some of your graphic art and Frank would do a keynote for the Richmond code camps and every time he would make movie posters, the one that. 

00:05:41 Frank 

Oh yeah. 

00:05:42 Andy 

Still sticks out is 1 called devs on a plane. 

00:05:45 Frank 

Ha ha ha. 

00:05:49 Andy 

Oh yeah, I loved that one that was so so cool and. 

00:05:49 Andy 

And that was. 

00:05:49 Andy 

00:05:54 Andy 

You know I saw the graphic arts part of it and I just knew I said you, you'd be really good in analytics and data visualization. You should get into by and you were busy doing other stuff which was cool. You were good at that too. It wasn't, you know you. I don't know of anything you've done that you haven't mastered. By thank you. You know you when. 

00:06:14 Andy 

Things took a took, uh, started taking a turn for you in your first rodeo at Microsoft. You got into it and and took off with it. I don't. I won't tell the story well, but you just really turned around. You focused on data and. 

00:06:32 Andy 

You know, I'll say this Frank. I was right. 

00:06:35 Frank 

Well, with that he totally I. I think if anything I took away is I should have listened to Andy 10 years earlier. 

00:06:36 Dave 

You aren't very good. 

00:06:40 Frank 

Uhm? 

00:06:41 Frank 

And that that that that is something that that that that's the big takeaway we'll talk about, kind of that journey. 'cause I think that's worth kind of talking about. And I think one of the things we you, and I've been bouncing around is kind of interviewing each other. 

00:06:46 

We 

00:06:55 Frank 

Like in asking one of us those those those questions we have, so we definitely will do that, but not today kids. 

00:06:55 Frank 

Yeah. 

00:06:55 Frank 

00:06:59 Dave 

We need to. 

00:06:59 Dave 

Need to. 

00:07:02 Andy 

Today, do we have Dave? 

00:07:02 Andy 

Today do Dave. 

00:07:03 Frank 

Today we have a special guest we have Dave Wentzel. Dave Wentzel is a was a peer of mine when I worked at the Microsoft MTC and that reminds me, I no longer work at Microsoft 2 weeks ago was my last day. I turned in my second blue badge. 

00:07:05 Frank 

Yeah. 

00:07:05 Frank 

00:07:18 Frank 

And I joined a startup called electrify. We'll talk about them a later day, but I'm so excited to have Dave here. Dave is the data in AI architect out of the Philadelphia Microsoft Technology Center, and he's an awesome guy. Awesome, got to work with. I worked with him when I was in field sales and I worked with him when I was in the MTC organization. 

00:07:38 Frank 

It is April. It was a privilege and honor Dave to have you as a colleague, and it's once again a privilege and an honor to have you here as a guest on data driven. 

00:07:46 Dave 

Well, thank you so much, appreciate that. 

00:07:47 Andy 

Welcome Dave. 

00:07:49 Dave 

Thank you. 

00:07:51 Frank 

So, uhm, so for folks that don't know what the MTC is. Shocking that there are actually people that don't know what that is, what? What is the MTC? 

00:08:00 Dave 

So basically we're a free service to our customers and I'm a data and AI technology architect. We talked to customers about data and it could be anything from just, you know. Hey, here's what we're doing. State of the art in Azure with. 

00:08:16 Dave 

With data, but it could also be architectural design sessions where we talk to customers. Our customers bring us their architectures, and then we kind of get it with them. Give them the pros and cons, alternative ways of thinking, and then what I really enjoy doing is hackathons with customers and workshops and just you know, helping them to learn without just. 

00:08:37 Dave 

Taking a course somewhere so actually using their data and then I guess I'm roughly a data scientist, so we also do design thinking sessions and those are absolutely a lot of fun. 

00:08:48 Dave 

We did one at the MTC with CSL Behring a couple years ago and it actually won a Forrester Award. So I'm very proud of that one. And yeah, it's it's a. It's a lot of fun and it's a good way to bring to have executives and business people understand the actual capabilities of data science. And then within two days be able to come up with a use case. 

00:08:55 Andy 

Oh wow, wow. 

00:09:08 Dave 

And actually build a prototype out a lot of fun. 

00:09:11 Frank 

Yeah, the NPC's are definitely like Microsoft Secret weapon in terms of how 'cause you know. Although I will say and because we were in the DC and we dealt with a lot of government contracts, we could not say that they were a free service. They were and already included paid for service. 

00:09:26 

That's. 

00:09:26 Dave 

Much, much better said yes. 

00:09:28 Frank 

I I 'cause I said free once and I got kind of slapped. 

00:09:31 Frank 

On the hand, say that. 

00:09:34 Frank 

But you know it, it really is something that if you do have a Microsoft account team and you are encountering any kind of questions or or whatever, and it's not strictly technical, there's also pretty good. You know, we basically wouldn't engage with the business development, business decision makers. 

00:09:52 Frank 

Technical decision makers all the way from kind of like you know, hey, this is what Azure can do. This is what data can do for you all the way down to OK. What's your problem? Let's build something out, give you 3 days with one of the top Notch architects in the. 

00:10:04 Frank 

Space and. 

00:10:07 Frank 

You know, boom, you know we knock it out and and you know I I enjoyed it you know had this opportunity not come I would have I would have gladly stayed another. You know 5-10 years of the MTC. Like a lot of people do, and it's a fun organization. So with that in mind, today we're going to do something a little different. We're kind of doing the. 

00:10:27 Frank 

A contrarian approach is that right, Dave. 

00:10:29 Dave 

Yes, exactly. 

00:10:31 Frank 

So this this has actually come up one of my last. This is one of the things that intrigued me about about your idea for the show was this came up when I was working with a we'll just call it a large governmental agency known for its. 

00:10:42 Frank 

Birds. 

00:10:42 Frank 

00:10:43 Frank 

Tape. 

00:10:44 Frank 

That that should keep it generic enough. They basically came to us and say we want Synapse. We want a data Lake. We want this. We want that. And I was like, OK, well how much data you're talking about. And like we have maybe you know 5 maybe 20 gigs of data. 

00:11:02 Frank 

And I'm like, uh, OK, tell me what are you trying to do? And ultimately I kind of pitched the idea like look, you know you don't have that much data right to make data bricks. 

00:11:14 Frank 

But you really want it so. 

00:11:17 Frank 

If you really want it, I won't stop you, but I think it's kind of overkill. I think you're taking instead of using a steak knife to cut the steak using a chainsaw. 

00:11:25 Frank 

And. 

00:11:27 Frank 

You know they kind of came back and ultimately what won the day was they already they couldn't get approval for whatever we recommended 'cause it didn't get stamped by there. 

00:11:37 Frank 

They're people for security usage yet, and things like that so they end up doing kind of the right thing because of their own bureaucracy, which. 

00:11:44 Frank 

It's kind of weird. It's kind of like dividing by zero and seeing the universe fold in on itself. 

00:11:50 Frank 

But UM, so the topic of today is kind of like no, you don't need a data warehouse. Did I get that right? 

00:11:58 Dave 

Exactly, that's what I believe in, and I believed in it since I was in college and I first learned about data warehouses. I'm not saying data warehouses are always bad, they definitely have their. 

00:12:10 Dave 

Use cases, but in 2021 when we're talking about advanced analytics and we're trying to tell customers you need to be more predictive than prescriptive. 

00:12:19 Dave 

The data warehouse really doesn't deliver. 

00:12:23 Frank 

Really, how so? 'cause? That's that's totally not the power. Certainly not the party line. I'm not going to say which party it was. You can figure it out but but why, why why would you say that? 

00:12:33 Dave 

OK so take. 

00:12:33 Dave 

A step back here, right? We're all data consultants, or we were at some point in our life and probably most of the listeners are. And if you've been doing this, I've been doing this since the mid 90s in college and when I first started I had an internship with a consumer package. Good company, they made candy. 

00:12:52 Dave 

Hours and they said, hey, we wouldn't want to do an internship and take a look at our data and figure out where is the best spot to put candy on a shelf so that we sell more candy to kids, right? So we used data for that at the time that was known as business Intelligence in the industry. Nowadays business intelligence means something totally different. In reality, it's really closer to what? 

00:13:12 Dave 

Today we would call data science right? So my tools of choice were SQL, although I didn't know what SQL was at the time and we had this goofy SQL engine and and essentially something called ESP's, which is roughly the equivalent of like our or stats package something. 

00:13:28 Dave 

Like that and we kind of looked at data as just, you know I have data and let me find the Nuggets of gold and I'm not going to concern myself with schema and that is I think the biggest problem with data warehouses. But take a, you know a metal layer higher right? Talk to the average business executive like a you know a CTO or CEO. 

00:13:48 Dave 

And tell them, as a consultant, you're going to go in and build them a data warehouse. 

00:13:53 Dave 

Instantly,...

In this episode, Frank and Andy speak to Carlos Chacon about data community, family, and messy data in legacy CRM systems.

Transcript

00:00:00 BAILey 

Hello and welcome to data driven, the podcast where we explore the emerging wait a tick. This is the premiere episode of Season Five. Can you believe it? Data driven started four years ago this month. 

00:00:14 BAILey 

Up until last season, we had a human doing the voiceover work. That is until she was replaced by an AI. Yours truly. 

00:00:23 BAILey 

In this episode, Frank and Andy speak to Dave Wensel about why you don't need a datawarehouse. We're starting off the new season with a bit of contrarian tone. 

00:00:33 BAILey 

It's a lively back and forth conversation that runs contrary to prevailing wisdom. Don't say we didn't warn you? Now on with the show. 

00:00:41 Frank 

Hello and welcome to data driven. The podcasts were we wait a minute. We've been saying this Andy for four years now. Can you believe it? 

00:00:48 Andy 

Four years, that's crazy talk. 

00:00:52 Frank 

That's just craziness. So I think when you and I first talked about this and that was that fateful, I think it was December was right after Thanksgiving. But before Christmas, I was thinking about starting a podcast and as a data scientist, I needed someone. 

00:01:01 Andy 

Yeah, yeah. 

00:01:09 Frank 

That was a data engineer that could kind of round out the talent there and and and and obviously I wanted someone I knew, liked, and trust. 

00:01:11 Frank 

Found out. 

00:01:11 Frank 

00:01:22 Frank 

And so it was you. 

00:01:25 Andy 

Well, I'm just glad all of the real smart data engineers you knew were busy. That's all I got to say. 

00:01:25 Frank 

Much. 

00:01:30 Frank 

Ah, no man. You were the first one. I reached out to and the only one I would have done it with it. So I was delighted when you said yes because starting a podcast can sound like a daunting thing, particularly if you haven't done it before. 

00:01:44 Andy 

Yeah, neither one of us really had. And gosh, it's it's worked out. What are we up to? 180,000 downloads or something? I mean that's. 

00:01:52 Frank 

Something. 

00:01:53 Frank 

Like that about hundred 8000 downloads. I mean, we're not Joe Rogan, but that's OK, Yep. 

00:01:55 

Yeah. 

00:01:57 Andy 

No. 

00:01:59 Andy 

Yep, Yep. 

00:01:59 Andy 

Yep. 

00:02:01 Frank 

But you know what, we we we've impacted. I think the community in a significant way. We've we've done a number of things we've we've innovative how we podcast. 

00:02:12 Frank 

Uh, we we've actually managed to keep a good cadence with some exceptions. 

00:02:18 Andy 

Yeah, thanks. 

00:02:19 Frank 

You know, we we finally did earlier this year or late last year, kind of fulfill our vision of it being data driven TV when we actually interviewed guests on. 

00:02:27 Andy 

Yes. 

00:02:32 Frank 

On video. 

00:02:33 Frank 

And that was that actually delayed the launch of the show by about three months. 

00:02:38 Andy 

It did but also uhm. Yeah, that was interesting, but you know it's typical software development, right? You release a feature and then you debug it. The I have this saying about that Frank. All software is tested some intentionally. 

00:02:52 Frank 

Sometimes. 

00:02:53 Andy 

Right? 

00:02:56 Frank 

I love it, but I also like how, how, how both our careers have evolved over the last four years. And dumb, you know, this being the premiere episode of Season 5 and we have something special lined up, but I'll get to that in a minute. 

00:02:58 Andy 

Hello. 

00:03:03 Andy 

Oh gosh, itch. 

00:03:11 Andy 

June. 

00:03:12 Frank 

You've progressed in your career. We, you and I've worked on some some projects together or virtual Summit. What we're calling Ring Gate, which will announce very very soon and and but. But most of all, is been my kind of skilling up in transition into data engineering myself. 

00:03:29 BAILey 

Ehm 

00:03:31 Frank 

Which was something that when I joined, so this is just a job update about a year ago. I I left the role of Microsoft kind of field sales and I went into the Microsoft Technology Center stick with me. There's a point to this story and basically I was at the rest in MTC. 

00:03:52 Frank 

And basically I was the AI guy on my my my field sales team, but I didn't really have deep knowledge of kind of the typical typical data engineering pipe work that goes into that role and basically my my. My then manager said you know he's like hey, you know, if you want this role, you've got a skill. 

00:04:12 Frank 

And skill up I did. And with Andy's mentoring and a bunch of other folks that helped me kind of skill up on our the data engineering side. I looked at it this morning. I'm like 88 hours on Pluralsight. 

00:04:25 Frank 

Wow, that was from mid may till we're recording this on April 30th. So just about a year 88 hours right now tracking on about 200 four 205 consecutive days of getting on LinkedIn. I'm not on LinkedIn on Pluralsight, LinkedIn learning. I also have a number of courses too. 

00:04:31 Andy 

Yeah. 

00:04:43 Frank 

Uh, that is something I'm proud of in terms of career evolution. 

00:04:47 Andy 

Absolutely Frank, you should be. How many cirts are you up to now? 

00:04:50 Frank 

I 87. 

00:04:53 Andy 

Slacker. 

00:04:54 Frank 

I know, I know. 

00:04:54 Frank 

Know, I know. 

00:04:54 Andy 

I think I've got 4. 

00:04:56 Frank 

Ah, now I know you and I did the data engineering thing, so you have at least 11. 

00:05:00 Andy 

That's true, that's true. We did that one and you know that was it's just. It's just been a nice journey and I'll take credit for this. 'cause 'cause I can I was. I was actually pestering you years ago. We've been friends since 2005 and we started doing. 

00:05:20 Andy 

Code camps here in the Richmond area. 

00:05:22 Andy 

Together and co-founded RE co-founded Richmond SQL Server Users Group and you know, worked with the net users group and stuff. And I told you as soon as I saw some of your graphic art and Frank would do a keynote for the Richmond code camps and every time he would make movie posters, the one that. 

00:05:41 Frank 

Oh yeah. 

00:05:42 Andy 

Still sticks out is 1 called devs on a plane. 

00:05:45 Frank 

Ha ha ha. 

00:05:49 Andy 

Oh yeah, I loved that one that was so so cool and. 

00:05:49 Andy 

And that was. 

00:05:49 Andy 

00:05:54 Andy 

You know I saw the graphic arts part of it and I just knew I said you, you'd be really good in analytics and data visualization. You should get into by and you were busy doing other stuff which was cool. You were good at that too. It wasn't, you know you. I don't know of anything you've done that you haven't mastered. By thank you. You know you when. 

00:06:14 Andy 

Things took a took, uh, started taking a turn for you in your first rodeo at Microsoft. You got into it and and took off with it. I don't. I won't tell the story well, but you just really turned around. You focused on data and. 

00:06:32 Andy 

You know, I'll say this Frank. I was right. 

00:06:35 Frank 

Well, with that he totally I. I think if anything I took away is I should have listened to Andy 10 years earlier. 

00:06:36 Dave 

You aren't very good. 

00:06:40 Frank 

Uhm? 

00:06:41 Frank 

And that that that that is something that that that that's the big takeaway we'll talk about, kind of that journey. 'cause I think that's worth kind of talking about. And I think one of the things we you, and I've been bouncing around is kind of interviewing each other. 

00:06:46 

We 

00:06:55 Frank 

Like in asking one of us those those those questions we have, so we definitely will do that, but not today kids. 

00:06:55 Frank 

Yeah. 

00:06:55 Frank 

00:06:59 Dave 

We need to. 

00:06:59 Dave 

Need to. 

00:07:02 Andy 

Today, do we have Dave? 

00:07:02 Andy 

Today do Dave. 

00:07:03 Frank 

Today we have a special guest we have Dave Wentzel. Dave Wentzel is a was a peer of mine when I worked at the Microsoft MTC and that reminds me, I no longer work at Microsoft 2 weeks ago was my last day. I turned in my second blue badge. 

00:07:05 Frank 

Yeah. 

00:07:05 Frank 

00:07:18 Frank 

And I joined a startup called electrify. We'll talk about them a later day, but I'm so excited to have Dave here. Dave is the data in AI architect out of the Philadelphia Microsoft Technology Center, and he's an awesome guy. Awesome, got to work with. I worked with him when I was in field sales and I worked with him when I was in the MTC organization. 

00:07:38 Frank 

It is April. It was a privilege and honor Dave to have you as a colleague, and it's once again a privilege and an honor to have you here as a guest on data driven. 

00:07:46 Dave 

Well, thank you so much, appreciate that. 

00:07:47 Andy 

Welcome Dave. 

00:07:49 Dave 

Thank you. 

00:07:51 Frank 

So, uhm, so for folks that don't know what the MTC is. Shocking that there are actually people that don't know what that is, what? What is the MTC? 

00:08:00 Dave 

So basically we're a free service to our customers and I'm a data and AI technology architect. We talked to customers about data and it could be anything from just, you know. Hey, here's what we're doing. State of the art in Azure with. 

00:08:16 Dave 

With data, but it could also be architectural design sessions where we talk to customers. Our customers bring us their architectures, and then we kind of get it with them. Give them the pros and cons, alternative ways of thinking, and then what I really enjoy doing is hackathons with customers and workshops and just you know, helping them to learn without just. 

00:08:37 Dave 

Taking a course somewhere so actually using their data and then I guess I'm roughly a data scientist, so we also do design thinking sessions and those are absolutely a lot of fun. 

00:08:48 Dave 

We did one at the MTC with CSL Behring a couple years ago and it actually won a Forrester Award. So I'm very proud of that one. And yeah, it's it's a. It's a lot of fun and it's a good way to bring to have executives and business people understand the actual capabilities of data science. And then within two days be able to come up with a use case. 

00:08:55 Andy 

Oh wow, wow. 

00:09:08 Dave 

And actually build a prototype out a lot of fun. 

00:09:11 Frank 

Yeah, the NPC's are definitely like Microsoft Secret weapon in terms of how 'cause you know. Although I will say and because we were in the DC and we dealt with a lot of government contracts, we could not say that they were a free service. They were and already included paid for service. 

00:09:26 

That's. 

00:09:26 Dave 

Much, much better said yes. 

00:09:28 Frank 

I I 'cause I said free once and I got kind of slapped. 

00:09:31 Frank 

On the hand, say that. 

00:09:34 Frank 

But you know it, it really is something that if you do have a Microsoft account team and you are encountering any kind of questions or or whatever, and it's not strictly technical, there's also pretty good. You know, we basically wouldn't engage with the business development, business decision makers. 

00:09:52 Frank 

Technical decision makers all the way from kind of like you know, hey, this is what Azure can do. This is what data can do for you all the way down to OK. What's your problem? Let's build something out, give you 3 days with one of the top Notch architects in the. 

00:10:04 Frank 

Space and. 

00:10:07 Frank 

You know, boom, you know we knock it out and and you know I I enjoyed it you know had this opportunity not come I would have I would have gladly stayed another. You know 5-10 years of the MTC. Like a lot of people do, and it's a fun organization. So with that in mind, today we're going to do something a little different. We're kind of doing the. 

00:10:27 Frank 

A contrarian approach is that right, Dave. 

00:10:29 Dave 

Yes, exactly. 

00:10:31 Frank 

So this this has actually come up one of my last. This is one of the things that intrigued me about about your idea for the show was this came up when I was working with a we'll just call it a large governmental agency known for its. 

00:10:42 Frank 

Birds. 

00:10:42 Frank 

00:10:43 Frank 

Tape. 

00:10:44 Frank 

That that should keep it generic enough. They basically came to us and say we want Synapse. We want a data Lake. We want this. We want that. And I was like, OK, well how much data you're talking about. And like we have maybe you know 5 maybe 20 gigs of data. 

00:11:02 Frank 

And I'm like, uh, OK, tell me what are you trying to do? And ultimately I kind of pitched the idea like look, you know you don't have that much data right to make data bricks. 

00:11:14 Frank 

But you really want it so. 

00:11:17 Frank 

If you really want it, I won't stop you, but I think it's kind of overkill. I think you're taking instead of using a steak knife to cut the steak using a chainsaw. 

00:11:25 Frank 

And. 

00:11:27 Frank 

You know they kind of came back and ultimately what won the day was they already they couldn't get approval for whatever we recommended 'cause it didn't get stamped by there. 

00:11:37 Frank 

They're people for security usage yet, and things like that so they end up doing kind of the right thing because of their own bureaucracy, which. 

00:11:44 Frank 

It's kind of weird. It's kind of like dividing by zero and seeing the universe fold in on itself. 

00:11:50 Frank 

But UM, so the topic of today is kind of like no, you don't need a data warehouse. Did I get that right? 

00:11:58 Dave 

Exactly, that's what I believe in, and I believed in it since I was in college and I first learned about data warehouses. I'm not saying data warehouses are always bad, they definitely have their. 

00:12:10 Dave 

Use cases, but in 2021 when we're talking about advanced analytics and we're trying to tell customers you need to be more predictive than prescriptive. 

00:12:19 Dave 

The data warehouse really doesn't deliver. 

00:12:23 Frank 

Really, how so? 'cause? That's that's totally not the power. Certainly not the party line. I'm not going to say which party it was. You can figure it out but but why, why why would you say that? 

00:12:33 Dave 

OK so take. 

00:12:33 Dave 

A step back here, right? We're all data consultants, or we were at some point in our life and probably most of the listeners are. And if you've been doing this, I've been doing this since the mid 90s in college and when I first started I had an internship with a consumer package. Good company, they made candy. 

00:12:52 Dave 

Hours and they said, hey, we wouldn't want to do an internship and take a look at our data and figure out where is the best spot to put candy on a shelf so that we sell more candy to kids, right? So we used data for that at the time that was known as business Intelligence in the industry. Nowadays business intelligence means something totally different. In reality, it's really closer to what? 

00:13:12 Dave 

Today we would call data science right? So my tools of choice were SQL, although I didn't know what SQL was at the time and we had this goofy SQL engine and and essentially something called ESP's, which is roughly the equivalent of like our or stats package something. 

00:13:28 Dave 

Like that and we kind of looked at data as just, you know I have data and let me find the Nuggets of gold and I'm not going to concern myself with schema and that is I think the biggest problem with data warehouses. But take a, you know a metal layer higher right? Talk to the average business executive like a you know a CTO or CEO. 

00:13:48 Dave 

And tell them, as a consultant, you're going to go in and build them a data warehouse. 

00:13:53 Dave 

Instantly, that's a political statement you just made. Data warehouses have connotations of you, know risky projects over budget projects as far as time and money, and...

In this episode Frank and Andy have a chat with Chris Gherardini on the role of data in ERP and CRM Systems.

00:00:00 BAILey 

Hello and welcome to data driven, the podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. In this episode, Frank and Andy speak to Chris Gardini about the role data plays in ERP and CRM systems. 

00:00:17 Frank 

Hello and welcome back to data driven. The podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. If you like to think of data as the new oil, then you can think of us like Car Talk because we focus on where the rubber meets the road. Although there's not much of a road trip usually on this virtual road trip. 

00:00:37 Frank 

Is Andy Leonard? How's it going, Andy? 

00:00:40 Andy 

Hey Frank, it's going really well. How are you doing? 

00:00:43 Frank 

I'm doing alright, you know, with the exception I might have to buy a new desktop computer. 

00:00:48 Andy 

Ah, I have not. 

00:00:49 Frank 

Possibly, or power supply. Literally. We were on this call and all of a sudden everything froze and I was like Oh well, blue screen. Big deal. 

00:00:59 Frank 

And then when I went to power it back on. 

00:01:03 Frank 

It just kept keeps beeping so I'm like oh, fee something something hard so I'm going to have to do some search engine work and possibly get a new power supply or something. 

00:01:06 Andy 

Codes. 

00:01:13 Frank 

Fortunately, micro center. 

00:01:14 Andy 

Everything is. 

00:01:17 Andy 

Go ahead. 

00:01:17 Andy 

00:01:17 Andy 

I've gotta say Frank, everything is figure out able right? 

00:01:21 Frank 

Everything is figure out able because of my experience with clear DB and all sorts of other drama. I have multiple backups of just about everything it if if you know so it's it's. It'll be an inconvenience, not a tragedy. 

00:01:32 Andy 

Outstanding. 

00:01:37 Frank 

But every opportunity to come back from a complete backup failure is an opportunity to learn. 

00:01:47 Frank 

And, uhm, Speaking of opportunity, it's really good timing that this guest is here because I as folks know I work at the Microsoft Technology Center in Reston and recently. 

00:02:00 Frank 

There was a, uh, someone we were on this engagement and it was very heavy into dynamics and uh, dynamics is one of those things. I haven't really looked into Andy and I have been experimenting with power apps and power platform, mostly to kind of help automate a lot of our content. 

00:02:21 Frank 

Production. 

00:02:22 Chris 

This is crucial as we. 

00:02:24 Frank 

Continue to put the final touches on our secret project, but this guest here is an expert in dynamics as well as various ERP solutions. 

00:02:36 Frank 

And he's from Saint Louis, and his name is Christian. I'm really blowing this intro here. His name is Cristiano Gardeny. Did I pronounce that right? 

00:02:48 Chris 

Cristiano Guardian yeah, he pulled our sounded out there so. 

00:02:48 Frank 

OK good good. 

00:02:51 Frank 

He did fine, got it. Sorry about that. He's the president and owner of Turnkey Technologies and they are a Microsoft partner. I did looking around on their website and they are basically they provide development, analytics, training and support services for Microsoft Dynamics. 

00:03:09 Frank 

If you don't know what Microsoft Dynamics is, a lot of people don't. In the data world tend to just know it tangentially. It's basically Microsoft CRM system, so welcome to the show, Cristiano. 

00:03:21 Chris 

Thank you very much. Thanks for having me. 

00:03:25 Frank 

It's good to have you here, and so what's the weather like in Saint Louis right now? 

00:03:30 Chris 

Ah, it's beautiful and sunny. Today it's about 64 degrees Sun index is just right around A5, so it's actually it's actually nice and better than the the ice. We had a couple weeks ago so. 

00:03:38 Frank 

Knife. 

00:03:42 Andy 

Yeah, it got bitterly cold out there for about a week, didn't it? 

00:03:47 Chris 

That's right, I happen to be in Florida that entire week. Everybody couldn't believe I missed all the fun. So with the IT was good, it was a good week to be gone. We left Saturday. We came back Sunday was 52 when we got back and the 9 inches of snow had melted and. 

00:03:51 Chris 

Unfelt 

00:03:51 Chris 

00:04:00 Chris 

So yeah, perfect timing. 

00:04:02 Frank 

Nice, now you have excellent timing Sir. Not only in just the fact that dynamics is kind of coming up, coming up on my personal radar, but also in terms of avoiding bad weather. My first question is and I'm calm. Still a new bit dynamics. I learned a lot just by working on this. 

00:04:23 Frank 

One engagement we had DMTC. 

00:04:27 Frank 

Is Dinah. 

00:04:28 BAILey 

Mix. 

00:04:29 Chris 

So Dynamics Dynamics is the biz apps. I mean, you said CRM. It's more than CRM. But today dynamics represents a family of products. You know, the legacy on Prem products, Dynamics AX Dynamics, Navy Dynamics, GP, Dynamics, SL and then the current dynamics 365, which encompasses both you know financing. 

00:04:49 Chris 

Operations, which was the dynamics AX and then Dynamics 365 business Central which was the Navy? So those are both ERP products. 

00:04:57 Chris 

And then Dynamics customer engagement, which is the CRM platform so so dynamics is a collection of biz apps. It's a family of products and you know today we we focus on the two dynamics 365 ERP products and the CRM. The customer engagement product. So great solution, but it's a platform also it. 

00:05:15 Frank 

That's what I noticed, and folks that are listening. They're like this is a data science kind of data engineering show. Why the heck are you talking about? 

00:05:25 Frank 

Dynamics but dataverse the data models, which are one of the things that blew me away, was on this one demo is that there's a. There's a button where you just basically can dump out all your cream data. 

00:05:38 Frank 

Or all your data and dynamics out to a data Lake. 

00:05:42 Chris 

That's absolutely right, Azure. So if you think about the challenges where you move from a legacy system to the cloud, maybe all the data doesn't move and you need to combine it in an Azure data like a data warehouse, and certainly all those tools and all the analytics are all part of the platform. That's just it touches dynamics out of the box, so it's quite a quite a degree of efficiency. 

00:06:02 Chris 

There. 

00:06:03 Frank 

Interesting. 

00:06:05 Frank 

So one question I have about dynamics is it's history now. You mentioned Dynamics AX and a couple of other letters next to the word dynamics. 

00:06:17 Frank 

Once Upon a time when I worked when I lived in Richmond, there was a guy who used to do a lot of work with that technology. 

00:06:24 Frank 

Back and it was Solomon in Great Plains is that is that the same thing is that the lineages from it. 

00:06:30 Chris 

That's correct, that's correct, that's correct. And so the US based products was Great Plains software out of Fargo ND, and a gentleman named Doug Burgum owned that company privately and then his family. They bought the the Salomon product line as well and then in 2001 is when Microsoft bought Great Plains. 

00:06:32 

Silly. 

00:06:46 Chris 

Software, so that's kind of how they consume the North American products and then a year later Microsoft went to Europe and bought Dynamics AX and Dynamics Navy. It was called Exapta in division so and that became a second big purchase and instantly at 2002 they had four ERP products and they're in the biz apps space like they've never been. 

00:06:48 Chris 

OK, so. 

00:06:48 Chris 

00:07:06 Chris 

Before so. 

00:07:09 Frank 

Ah OK, that's interesting. 'cause I I now I know why. There's a huge Microsoft campus in Fargo. 

00:07:16 Chris 

Yes, yes. 

00:07:18 Chris 

It's beautiful campus. 

00:07:19 Frank 

Uhm? 

00:07:21 Frank 

Yeah, I haven't been there, but I definitely maybe one day I'll end up going but the the other question I have for you. You keep saying biz apps when you say biz apps? What exactly do you mean like what? 

00:07:32 Chris 

Sure, so I'm. I'm a technical guy. I'm engineering comp SCI math and there's two directions you go and even those curriculums you go **** **** or you or business applications and so business applications in our context is, you know, we're we're business process automation again, whether it starts in an ERP from a quote to cash or a procure to pay those. 

00:07:33 Frank 

What what comic sub is that like? 

00:07:52 Chris 

For business processes and the business applications support. 

00:07:56 Chris 

Work, transactional processing or even non transactional if you think about context of a lead to opportunity to customer type of flow where you start even earlier in the process, but it is it's process automation and exception management and workflow and approvals and can go to the NTH degree of complexity. But but it's biz apps in that categorization. 

00:08:16 Chris 

So as opposed to scientific apps or development tools or games, for example, right, we're focused on businesses, not on residential applications. 

00:08:26 Chris 

That makes sense. 

00:08:27 Andy 

It does, yeah. 

00:08:28 Frank 

Do you have any questions Andy? 

00:08:30 Frank 

This is so awkward being on on this recording, but not being live. So for those that are watching or listening or maybe watching. 

00:08:35 Andy 

Yeah, I don't work. 

00:08:40 Frank 

Go ahead. 

00:08:42 Andy 

Yeah, I'd like to apologize to Chris, especially thank you for coming on here, but we're a little off because of the video. I I I never shaved but. 

00:08:50 Chris 

No worries. 

00:08:55 Andy 

I would have I. I have a face for radio. I think in audio, so that's what's throwing us just a bit. Although Frank and I do live streaming and stuff, can you tell us a little bit more about about what your company does, how how your team implements these biz apps? 

00:09:14 Chris 

Sure, so so turnkey is a is a direct Microsoft distributor, so we distribute dynamics licensing and then we provide 100% of the professional services to to plan to implement, to convert, to customize, to integrate. So really, if you think about there's two parts of business, there's the licensing side and and then the services side, which we've got about 60 team members. 

00:09:35 Chris 

These days, and as you think about, you know, delivering an implementation once the solutions been kind of articulated as project management methodology, really drive the success of the project, and so there's an intimate, detailed plan. 

00:09:48 Chris 

Where we use Microsoft project and and we plan in very very low levels of detail for project execution. Everything from you know, the initial phases of analyzing and requirements and then through design and then through development and through deployment. And then we take people live, but it's a very predictable methodology that's used for project delivery. 

00:10:08 Chris 

Around the ERP products, so that's that's the first spot, so. 

00:10:12 Andy 

You know that sounds an awful lot like what what we do when we're doing data warehousing as well and and similar work I I would say. 

00:10:22 Chris 

Absolutely the disciplines or you know, are kind of agnostic when you think about project methodology. 

00:10:27 Andy 

So just curious, what is a typical engagement about how long does a typical engagement last? 

00:10:34 Chris 

So and again, we sell 2 flavors Dynamics, 365 business Central. We talk about small, medium and those projects could. 

00:10:41 Chris 

Maybe three months for somebody small coming off of a QuickBooks. It's just financials, but it could be six months for somebody that's implementing distribution and manufacturing, for example. So depending on complexity, three months is normally the least amount of time, and in 6 plus months for the business, central on the finance and supply chain, which was acts as a much larger applications targeted at, you know. 

00:11:01 Chris 

Mid market enterprise organizations. Those projects are typically not being delivered in less than six months. Frankly, and I've got some that we see them take 12 to 18 months for example so. 

00:11:13 Chris 

No, it's gonna save us the the project management requirement. Because of that duration and scope and girth. You really people get lost right? Anyway, I'm sorry please. 

00:11:23 Frank 

Oh no no no no no so. 

00:11:26 Frank 

The the, the ERM or the ERP systems like Dave require. So Once Upon a time I was working for a large German chemical company, right? And of course it's a German company, so they used SAP and they hired a bunch of consultants and consulting firms to build out the system. But when they. 

00:11:46 Frank 

Rolled out SA P R2. I think it was. 

00:11:49 Frank 

Is. 

00:11:50 Frank 

Apparently there was not. 

00:11:52 Frank 

A lot of project discipline now I'll just. I'll just leave it there. 

00:11:57 Frank 

And it basically shut down some of their plants because there were just things were not coming in the way they were supposed to. So So what? 

00:12:06 Frank 

How? 

00:12:07 Frank 

How does ERP systems? How do our ERP systems? Kind of you know if they're done wrong? It sounds like they can create a big mess if they're done right, they could really optimize operations. 

00:12:19 Frank 

Uhm? 

00:12:21 Frank 

I mean is that, is that true? 'cause I I kind of saw, I mean. 

00:12:23 Frank 

That was just a Horror Story. It's true. 

00:12:24 Chris 

It's true, it's true. It's like me giving you lousy directions to drive from Florida to Washington, and it takes you six months and it should have taken you three days. There's a great example. I poor guidance and poor methodology, is it stretches it out. Things are missed, costs are out of control, but again, if it's done correctly through a thorough analysis. 

00:12:34 Frank 

Point 

00:12:45 Chris 

Then you really define scope. 

00:12:46 Chris 

And you know you have good business process visualization. Then you drive to deliver those processes to that point and and it's. And again, if you do a good job and my team does a great job of of really articulating business process, you gain great efficiency and Moreover you get capacity to turn up the juice again, you can take more volume and you've you've articulated. 

00:13:05 Andy 

Nice. 

00:13:06 Chris 

And really gotten the inefficiency out of the process, and Even so, you don't touch every transaction you touch the exceptions so you get a lot of leverage. But then you're correct if it's done right, if it's done. 

00:13:16 Chris 

Wrong, right? It maybe it's broken, maybe it falls off the table and somebody has to pick it up and has a manual step because they didn't think through it thoroughly. And and now you've got a bigger problem, right? And sometimes companies don't retire the old systems and they're working in two places, so there is a lot of negative that can come for people that don't manage and plan and and deliver these systems. And and again, we've been doing this. 

00:13:37 Chris 

For 27 years, so we're pretty pretty good at it so. 

00:13:38 Andy 

Will you? 

00:13:40 Andy 

Wow. 

00:13:42 Andy 

Well, you you mentioned Chris that you know when you were giving examples of the typical projects links that customers are are often migrating from other platforms. Other ERP ish. Perhaps they do some of the ERP work and then you're moving them into dynamics. And as you say. 

00:14:02 Andy 

Once they get in there, they're going to be able to scale. It sounds like horizontally and and cover more territory than the system that they were using and also scale vertically. Like you said, turn up the juice and and just grow is that. Is that...

In this livestream, Frank and Andy talk about geothermal energy, solar power, and why you should never say not to Clippy.

In this episode of Data Driven, Frank and Andy speak with Peter Voss about Artificial General Intelligence, Personalizing Personal Assistants, and Motorcycles

Sponsor: Audible.com - Get a free audio book and support DataDriven - visit thedatadrivenbook.com!

Peter Voss is the world’s foremost authority in Artificial General Intelligence.

His company Aigo (https://www.aigo.ai/) has created the world’s first intelligent cognitive assistant.

Aigo was funded with a personal investment of $10 million dollars. They currently manage millions of personalized customer service inquiries for household name-brands

Aigo is Peter's company. BAILeY's Introduction (00:00)

The east coast has been blanketed with snow. (01:30)

The Expanse books (03:00)

Coding for curiosity? - Frank (11:50)

"Models don't dynamically learn." - Peter (13:00)

Three waves: Logic programming, Deep learning / neural networks, cognitive architecture / intelligence (14:00)

Intelligence v. sentience? - Frank (15:50)

What about bots being "led astray?" - Andy (18:30)

On programming morality... (21:30)

AI Safety is a better description - Peter (22:30)

Asimov's three laws of robotics - Frank (23:15)

On delimmas - Peter (24:15)

"Morality should be about human flourishing." - Peter (25:15)

Are we using digital means to do something analog? - Andy (27:55)

Peter is trained as an electronics engineer. (28:05)

"Context is always super-important." - Peter (28:30)

"You need a feedback system." - Peter (30:00)

AIGO is Peter's company. (31:00)

The three meanings of personal. (34:00)

"Exo-cortex" (33:50)

On context switches (38:30)

Did you find AI or did AI find you? (41:00)

"I took five years off to study..." - Peter (43:00)

What's your favorite part of your current gig? (44:10)

When I'm not working, I enjoy ___. (45:00)

I think the coolest thing in technology today is ___. (45:30)

I look forward to the day when I can use technology to ___. (46:25)

Something interesting or different about yourself (47:00)

How Not to Die (48:00)

Where can people learn more about Peter? (49:00)

Book reading / listening recommendations? (49:00)

The Mind's I (50:00)

Peter's articles on Medium (52:00)

Get a free audio book and support DataDriven - visit thedatadrivenbook.com! (00:00)

The following transcript is AI generated.

00:00:01 BAILeY

Hello and welcome to data driven.

00:00:03 BAILeY

The podcast where we explore the emerging fields of data science, machine learning, and artificial intelligence.

00:00:11 BAILeY

In this episode, Frank and Andy speak with Peter Voss, peterboat.

00:00:15 BAILeY

Peter Voss is the world's foremost authority, an artificial general intelligence or AGI.

00:00:21 BAILeY

In fact, he is the one who coined the term in 2001 and published a book on the topic in 2002.

00:00:28 BAILeY

He is a serial.

00:00:29 BAILeY

AI entrepreneur technology innovator who has for the past 20 years, then dedicated to advancing artificial general intelligence.

00:00:38 BAILeY

Today he is focused on his company, IGO, which is developing and selling increasingly advanced AGI systems for large enterprise customers.

00:00:47 BAILeY

Peter also has a keen interest in the interrelationship between philosophy, psychology, ethics, futurism and computer science.

00:00:56 BAILeY

I think you will find this interview a fascinating look at the future of AI.

00:01:01 BAILeY

Now on with the show.

00:01:05 Frank

Hello and welcome to data driven, the podcast where we explore the emerging fields of data science, machine learning and artificial intelligence.

00:01:13 Frank

If you like to think of data as the new oil, then you can think of us like well.

00:01:18 Frank

Car Talk because we focus on where the rubber meets the road and with me on this epic virtual road trip down the information highway because we're still locked in quarantine.

00:01:29 Frank

As always, Andy Leonard.

00:01:30 Frank

How's it going and?

00:01:31 Andy

Good Frank, how are you?

00:01:33 Frank

I'm doing well.

00:01:34 Frank

We had a bit of snow.

00:01:36 Frank

We're recording this on Monday, February 1st and the East Coast has been blanketed in some snow.

00:01:37 Peter Voss

Yes.

00:01:45 Andy

Yeah, we got more than we've gotten, probably since 2018 or so. About four inches here in FarmVille and then almost an inch of ice on top of that, which always makes it fun, right?

00:01:58 Frank

Yeah, the ice is worse than the snow on.

00:02:00 Frank

Basically so I went out, walk the dog today and one of the dogs and it was crunch, crunch, crunch.

00:02:06 Frank

So there's a nice layer of ice over everything which is going to make driving later fun, but I do have.

00:02:13 Frank

I do have the an all wheel drive car which is fantastic.

00:02:17 Frank

I will never not own one of those again.

00:02:19 Andy

Nice.

00:02:21 Frank

Yeah, you've seen it's the CRV.

00:02:23 Andy

Yes, yeah, it's nice you did well.

00:02:26 Frank

I dubbed it the Rocinante.

00:02:31 Andy

In case our listeners are not familiar with that, with what Frank is referring to, it is not the old novel.

00:02:40 Andy

Frank is not tilting at windmills instead.

00:02:44 Andy

And if I got that reference wrong, correct me.

00:02:46 Andy

I'll just edit that out.

00:02:47 Frank

Oh, you are right, it's from this AM Oh my God, I forgot new book on Cody.

00:02:48 Andy

Not sure.

00:02:51 Andy

Donkey Quixoti wasn't.

00:02:53 Frank

Yeah yeah Cervantes I was gonna say from Cervantes book and I'm like oh what was the name of that?

00:02:53 Andy

Yeah so.

00:02:59 Frank

Which is the opposite of how most people think, but that's what I do.

00:02:59 Frank

OK, good.

00:03:02 Andy

There we go, but it is actually a reference to both the books and a series, The expanse of which Frank and I are great fans, so.

00:03:12 Frank

Awesome, but you know who's not covered in snow today.

00:03:13 Andy

I like it.

00:03:15 Andy

Who is not covered in snow their guest.

00:03:16 Andy

Our guest.

00:03:18 Frank

Who lives in?

00:03:18 Frank

Yeah.

00:03:20 Frank

I'm assuming sunny or Smokey I guess depending on the time of year California Peter Voss Peter welcome to the show.

00:03:29 Peter Voss

Thank you, yes, it's we've got snow on the mountains here, but it's very sunny.

00:03:36 Peter Voss

It's it's nice and we have a lot less smog these days.

00:03:41 Andy

Very good.

00:03:41 Frank

Nice so you are the.

00:03:46 Frank

One of the world's, or if not the world's foremost authority in AGI or artificially artificial general intelligence, and I believe you are the one that coined the term.

00:03:58 Peter Voss

Yes, correct and 2001 myself and two other people. We coined the term artificial general intelligence AGI to really distinguish the kind of work we were doing from, you know, specialized narrow AI which is.

00:04:18 Peter Voss

Pretty much what everybody else is doing.

00:04:20 Peter Voss

The original dream of artificial intelligence was of course, to have systems that can think and learn the way humans do, but that turned out to be a lot lot harder than people thought.

00:04:31 Peter Voss

So over the years, AI really turned into narrow AI using human ingenuity to figure out how to solve one particular problem, like playing chess or.

00:04:41 Peter Voss

Container optimization or medical diagnosis and then to write a program or to train data to do that to solve that particular problem.

00:04:51 Peter Voss

But it's really the external intelligence of the program or the data scientists that is then encoded.

00:04:58 Peter Voss

To solve that problem, whereas we wanted to get back to the original dream of having a thinking machine that it can figure out how to do these things and and learn more humans do so.

00:05:09 Peter Voss

That's why we felt we had to.

00:05:12 Peter Voss

You know, coin a separate term to distinguish it from narrow AI.

00:05:16 Frank

Interesting.

00:05:18 Frank

So for years, AGI has been.

00:05:21 Frank

Kind of thought the stuff of science fiction.

00:05:24 Frank

I think there was a lot of optimistic people like you said that thought we would have it by now.

00:05:29 Frank

I know this is kind of a loaded question, but one do you think we'll ever get there and two, what's the sort of time frame we're looking at?

00:05:38 Peter Voss

Yes, it's an interesting question, so absolutely, I believe it's it's.

00:05:42 Peter Voss

Possible, and in fact the reason we got together. We wrote a book called Artificial General Intelligence. As I said in 2001 was because we believe the time is ripe to get back to this original dream that the technology had advanced enough. Both hardware and software technology and cognitive psychology. Cognitive science.

00:06:02 Peter Voss

That we now understood enough and had fundamentally had the tools in place to tackle this problem and to say.

00:06:11 Peter Voss

So I I absolutely believe that it can be solved soon, and in fact we will leave.

00:06:18 Peter Voss

We are on on the way of solving this problem now in terms of time frame.

00:06:24 Peter Voss

Normally the way I answer this question is I don't measure it in time.

00:06:28 Peter Voss

I measured in dollars.

00:06:31 Frank

I like that time is money, so I guess.

00:06:34 Frank

That's a reasonable correlation.

00:06:35 Peter Voss

Yeah, and and the reason I do, I say that is because.

00:06:39 Peter Voss

Still, today almost nobody is working on AGI. You know, 99% of all the effort in artificial intelligence is still on narrow AI, so if this continues, it will take a long long time for us to reach human level AGI. But if that changes.

00:07:00 Peter Voss

And you know the kind of funding that's going into deep learning machine learning suddenly was applied to AGI.

00:07:06 Peter Voss

Then I think it could easily happen at less than 10.

00:07:09 BAILeY

Yes.

00:07:10 Frank

Oh wow.

00:07:11 Andy

Very cool, so I'm curious is there any like lead in does?

00:07:16 Andy

Does time and money invested in deep learning and narrow AI?

00:07:23 Andy

Does any of that help move the cost?

00:07:25 Andy

Say further the cause for AGI?

00:07:29 Peter Voss

Slightly, I believe, you know.

00:07:32 Peter Voss

Obviously, any advances in languages and data collection in hardware development and the general experience.

00:07:42 Peter Voss

In that sense, it does help it.

00:07:44 Peter Voss

But in another sense, it's actually the opposite.

00:07:46 Peter Voss

It's actually hindering it because a whole generation of software engineers and data scientists are now coming into the field, believing that deep learning machine learning is a way to do it.

00:08:00 Peter Voss

And all we need is more data, more horsepower and will solve this problem.

00:08:05 Peter Voss

And that's I think barking up the wrong tree, and it's a it's a dead end.

00:08:10 Peter Voss

So in that sense, what's happening today with deep learning?

00:08:12 Peter Voss

Machine learning is actually counter to achieving.

00:08:16 Andy

GI interesting very interesting.

00:08:20 Frank

Was it always that way or it's just the way the market kind of went frenzied over just narrowed AI?

00:08:26 Peter Voss

Why?

00:08:26 Peter Voss

Well, we've had several windows of AI.

00:08:30 Peter Voss

You know the the disappointments over the decades.

00:08:33 Peter Voss

You know, when we had expert systems, people believe that you know they would really, you know, show real intelligence and then it kind of fizzled out.

00:08:42 Peter Voss

And so we've had.

00:08:43 Peter Voss

We've had various windows, and but of course, deep learning machine learning has been so spectacularly successful in several areas.

00:08:52 Peter Voss

You know, image recognition, improving speech recognition, and you know various other fields that just, you know, it's the only game in town as it has been very, very successful.

00:09:04 Peter Voss

But people are also starting to realize what the limitations are of it.

00:09:11 Peter Voss

So yeah, it's it's kind of at the moment.

00:09:14 Peter Voss

The only game in town, and it has really been successful in many.

00:09:17 Andy

Areas, So what are those limitations?

00:09:20 Andy

And how does AGI addressing?

00:09:23 Peter Voss

Yeah, so fundamentally when you think about intelligence, you know if you think about just common sense.

00:09:32 Peter Voss

If we talk to a person and we judge them to be intelligent or to be totally non intelligent, the kind of things we expect is that they can learn.

00:09:43 Peter Voss

Immediately that when you say something a, they understand what you're saying and they integrate that knowledge with their existing knowledge so you know if you say my sister's moving through Seattle next week or something.

00:10:01 Peter Voss

That knowledge needs to fit in somewhere.

00:10:04 Peter Voss

You know you know the person who's talking.

00:10:06 Peter Voss

You may know who the sister is, or you may not know who the sister is.

00:10:10 Peter Voss

You probably know what Seattle is.

00:10:13 Peter Voss

You may have images of, you know, rain pouring down all the time or whatever, but so you integrate that knowledge.

00:10:21 Peter Voss

And if you're not cleared, my maybe the person has two sisters, so then you would ask her, do you mean your older sister you know your younger sister?

00:10:30 Peter Voss

And so we expect an intelligent human to basically do.

00:10:35 Peter Voss

You know what's technically called one shot?

00:10:37 Peter Voss

Learning?

00:10:38 Peter Voss

You hear something once you see an image.

00:10:40 Peter Voss

Once you learn that and you integrate it into your existing knowledge base.

00:10:46 Peter Voss

And if you're not sure how to interpret it.

00:10:49 Peter Voss

Then you ask clarifying.

00:10:50 Peter Voss

Questions until you know what it what it is.

00:10:54 Peter Voss

So you have deep understanding you have disambiguation.

00:10:59 Peter Voss

You have learning instant learning, one shot learning.

00:11:03 Peter Voss

You have long term memory.

00:11:05 Peter Voss

You remember that next week you you know if you paid attention, you will remember that and you have reasoning about.

00:11:12 Peter Voss

30 now deep learning machine learning as it's done today, really doesn't offer any of those.

00:11:20 Peter Voss

So if you if you had a human and you told them something and they didn't remember it, they didn't understand that they didn't ask for clarification.

00:11:27 Peter Voss

You wouldn't think of them as being very intelligent, would you?

00:11:33 Frank

No, I mean, my kids are smart, but when I tell them to bring the trash cans back from the street, they'll conveniently forget.

00:11:39 Frank

But I, I think I know where you're going with that, yes?

00:11:42 BAILeY

All right?

00:11:44 Frank

But the question I have, it sounds like you're trying to and I know this is going to be not really good analogy.

00:11:50 Frank

Or maybe it is you're trying to code for curiosity.

00:11:54 Peter Voss

That's very much part of it, but you know even deeper is understanding.

00:11:59 Peter Voss

Basically, when you have some input, do you?

00:12:02 Peter Voss

Do you understand you know what the implications are, how it fits in with the rest of the knowledge that you have?

00:12:08 Peter Voss

And you know, even that, that's sort of more even more fundamental than curiosity.

00:12:13 Peter Voss

But yeah, curiosity is then wanting to gather more information, so this is inherently an interactive process.

00:12:22 Peter Voss

You know, an intelligent person would ask follow up questions you know they would want to kind of.

00:12:29 Peter Voss

Fill in the pieces of the puzzle and you know that they can be more.

00:12:33 Peter Voss

In fact effective in their communication on their or their job.

00:12:37 Frank

Right so.

00:12:37 Peter Voss

So yes, that's definitely part of it.

00:12:40 Frank

So calling back to your example of someone's sister moving to Seattle you you would ask, you know, I didn't know you had a sister or how many sisters do you have or how many siblings do you have and.

00:12:51 Frank

Where is she moving to?

00:12:52 Frank

Why?

00:12:53 Frank

I guess that's kind of.

00:12:55 Frank

I guess it's all about building that knowledge map inside.

00:12:58 Frank

Your head or then your head being could be a program I guess.

00:12:58 BAILeY

Exactly.

00:12:59 BAILeY

OK.

00:13:02 Peter Voss

Yeah, and deep learning machine learning really doesn't allow for that at all.

00:13:07 Peter Voss

You know you accumulate masses of data and you train a model, but that model is then static.

00:13:14 Peter Voss

It's a read only model.

00:13:15 Peter Voss

You know, it doesn't dynamically learn, so it may have a sort of a knowledge graph, but even that knowledge graph is.

00:13:23 Peter Voss

Is very opaque, it's.

00:13:26 Peter Voss

Yeah, it's not scrutable you know and and this is this is such a big problem with deep learning machine learning that you don't know why it gives a certain response, which is a huge...

In this episode, Frank and Andy speak with Dan Burcaw on Entrepreneurship, Using AI to Stop Customer Churn, and Deploying Code onto Nuclear Submarines.

The following transcript is AI generated.

00:00:00 BAILeY

Hello and welcome to data driven.

00:00:02 BAILeY

The podcast where we explore the emerging fields of data science, machine learning, and artificial intelligence.

00:00:09 BAILeY

In this episode, Frank and Andy speak with Dan Burke or Dan is a serial entrepreneur who has founded four companies each on the forefront of a major technology wave, open source software, the smartphone.

00:00:23 BAILeY

Cloud computing and now machine learning.

00:00:26 BAILeY

Currently he leads Nam Eml, a company focused on helping app developers start and grow mobile subscription businesses.

00:00:34 BAILeY

If you follow Frank and or Andy on social media, you certainly have heard them bang on about their secret project.

00:00:41 BAILeY

I will drop a one word hint here foreshadowing.

00:00:45 BAILeY

Now on with the show.

00:00:48 Frank

Hello and welcome back to data driven.

00:00:50 Frank

The podcast where we explore the emerging fields of data science machine learning, an artificial intelligence, and if you like to think of data as the new oil, then you could consider us Car Talk.

00:01:02 Frank

Because we focus on where the rubber hits the road.

00:01:05 Frank

So with that as my guest on this pandemic road trip, that hasn't happened.

00:01:13

Yeah.

00:01:13 Frank

By my copilot here is Andy Leonard.

00:01:16 Frank

How you doing Andy?

00:01:17 Andy

Hey, I'm doing pretty good Frank how are you?

00:01:20 Frank

I'm doing well, I'm doing well.

00:01:21 Frank

I had a kind of an architecture session this morning, so that went really well.

00:01:27 Frank

It was.

00:01:28 Frank

It was an interesting conversation and I love doing those.

00:01:31 Frank

Those are always fun.

00:01:32 Frank

How about?

00:01:32 Andy

Yeah.

00:01:33 Andy

Yeah, so I'm proofing the next book.

00:01:36 Andy

Proofing is the absolute last chance to remove all of the typos I've left in.

00:01:42 Andy

As I've gone through the last three full edit sessions and there's still some there.

00:01:47 Andy

Frank, I'm convinced that the next book is going to have, you know, have a fair share of those.

00:01:52 Andy

What I'm really concerned about.

00:01:54 Andy

Is making sure that the demos work an yeah that's you know it's it's tedious and it's the LastPass so you know it's like is this over yet? Yeah, I'm sick and tired of reading this guy's writing and it's me so.

00:02:10 Andy

Yeah no.

00:02:10 Andy

But yeah.

00:02:12 Frank

That was the hardest part.

00:02:13 Frank

People asking.

00:02:14 Frank

Like when I wrote a book on Silverlight an aside from it being about Silverlight, the hardest thing wasn't so much writing, it was having to go back and re edit my own stuff and like.

00:02:24 Frank

You know, and I would look at it and be like man like I'm a terrible or.

00:02:28 Andy

That's I have said over and over again to my computer monitor who wrote this crap.

00:02:33 Andy

By a friend if you live.

00:02:33 Andy

But Fortunately for this is a second edition, so an it's one of those second editions where I kept the first 10 or 11 chapters.

00:02:43 Andy

I I changed from my writing language.

00:02:46 Andy

I wrote it like three years ago.

00:02:48 Andy

And I really this grew out of a series of blog posts that I wrote back in 2012. It was all in VB back then, Visual Basic. And so I wrote it that way in 2017 and for the 2nd edition I went back and updated all of that. That's really the only thing I changed was I went to C sharp.

00:03:06 Andy

An I kind of needed to because the rest of the book was going to be in C sharp anyway.

00:03:12 Andy

And so yeah, that's that's kind of how it went.

00:03:15 Andy

And for anybody listen, it thinks wow, Andy is smart.

00:03:18 Andy

He's written a book about C sharp.

00:03:20 Andy

He must know C sharp really, really well.

00:03:22 Andy

I say throughout the book I am not a C sharp developer.

00:03:26 Andy

I feel like I'm working my way up to being a noob, but but.

00:03:29 Frank

Don't you work classes?

00:03:31 Andy

I do wear glasses.

00:03:33 Andy

Yes, yeah.

00:03:33 Frank

So you can see sharp.

00:03:36 Andy

I did.

00:03:36 Andy

They took me awhile.

00:03:37 Andy

Do you have your sound effects running from I?

00:03:39 Frank

Do were back in Zend Caster.

00:03:41 Frank

So for folks listening like I don't remember this being on the live stream.

00:03:45 Frank

If it's not, we're doing this the old fashioned way right then, and don't worry, Andy and I've been live streaming a lot, which you probably noticed, but today we have a very special guest, don't we, Andy?

00:03:48 Frank

Um?

00:03:56 Andy

Yeah yeah, Dan Burke all is awesome.

00:04:00 Andy

He's a co-founder and CEO and I hope I say this right, is it?

00:04:04 Andy

Is it nami? Nami ML Dan.

00:04:07 Dan Burcaw

Yeah nami. Like tsunami.

00:04:09 Andy

Ah OK, I got it right the first time NAMI AML and it's a really smart service for monetizing digital products with subscriptions.

00:04:09 Frank

Well.

00:04:19 Andy

And just he's had a whole ton of experience working in, you know, in marketing for the Oracle Marketing Cloud, working with the mobile product for that.

00:04:31 Andy

So pretty smart Guy joined joined Oracle back during the acquisition of Push IO and.

00:04:39 Andy

Push IO was a leading mobile messaging provider as well.

00:04:44 Andy

And he served there as a Co founder and CEO.

00:04:47 Andy

There's a bunch more in here about Nan, an it all kind of boils down to super smart, successful guy.

00:04:54 Andy

We've had a little bit of banner before we click the record button an I can attest to.

00:04:59 Andy

That is really enjoyable conversation.

00:05:01 Andy

I look forward to this show.

00:05:02 Andy

Thanks for being here, Dan.

00:05:05 Speaker 1

Really happy to be here.

00:05:05 Speaker 1

Really happy to be here.

00:05:06 Speaker 1

Thanks for having me.

00:05:07 Frank

Awesome, so you're a serial entrepreneur and you founded a bunch of companies.

00:05:13 Frank

Um, but my favorite part of the bio I read on you was that.

00:05:18 Frank

You wrote software that ended up on a nuclear submarine.

00:05:23 Speaker 1

Yeah, that's right.

00:05:26 Speaker 1

It's it's hard.

00:05:26 Frank

That that totally away I was like what?

00:05:29 Speaker 1

It it's it's hard to even tell that story sometimes because it's so unbelievable.

00:05:35 Speaker 1

I 17 years old at the time.

00:05:38 Speaker 1

The company that I cofounded was building a flavor of Linux.

00:05:46 Speaker 1

A flavor of Linux that was designed to run on Apple Macintosh hardware.

00:05:52 Speaker 1

And at the time.

00:05:52 Frank

Interesting.

00:05:54 Speaker 1

Then the the reason for that was that Apple was using the power PC chip power PC chip in that moment of time. You know, we're kind of talking in the late 90s. Early 2000s had fantastic price per performance per Watt, which is a metric that a lot of folks in the kind of high performance computing world look at when they're trying to figure out.

00:06:11 Andy

Me.

00:06:18 Speaker 1

How to build these kind of supercomputer clusters?

00:06:21 Speaker 1

And so it just happened at that moment in time, the Mac would had had the best price performance per Watt because of the chips that they.

00:06:29 Speaker 1

We're using and so we we ended up doing a deal with Lockheed Martin and the US Navy to build a cluster of Macs running Linux.

00:06:45 Speaker 1

That were deployed across the US Navy nuclear sub fleet for the purpose of doing sonar image processing, yeah.

00:06:53 Andy

Wow.

00:06:55 Speaker 1

The the the software that I wrote was related to.

00:07:00 Speaker 1

You know how folks on the boat would have to manage these units if there was issues, how would you know?

00:07:07 Speaker 1

Kind of the maintainability repair ability was a big issue when you're actually out at sea and trying to have this stuff run in kind of a mission critical fashion so.

00:07:17 Speaker 1

We ended up.

00:07:17 Speaker 1

I mean it was this was such a crazy project because the hardware was modified hardware.

00:07:22 Speaker 1

It wasn't off the shelf Apple hardware, it was Apple Hardware and then we did a bunch of things to it and then it was Linux and then it was some custom software that made the whole thing operate an.

00:07:35 Speaker 1

So it's it was.

00:07:37 Speaker 1

It was a nutty project, an I'm.

00:07:40 Speaker 1

Looking back on it now, I'm surprised that it had ever shipped quite frankly.

00:07:46 Frank

Spoken like a true engineer, right?

00:07:48 Frank

You're always you always look at your flaws and like Oh my God, that's actually running.

00:07:56 Frank

So so you you where did you go after that?

00:08:00 Frank

'cause it says you know you're a serial entrepreneur and so how did you get into?

00:08:05 Frank

I don't want to steal.

00:08:06 Frank

Kind of our pre canned questions Thunder but.

00:08:11 Frank

Tell me how did you get into A&ML? Or were you doing ML on those on those retrofitted Max?

00:08:18 Speaker 1

No, we weren't.

00:08:19 Speaker 1

We weren't, but but you know, I think that part of the hype that world of high performance computing where a lot of our customers were, you know, national labs or defense oriented things.

00:08:30 Speaker 1

I mean, part of the appeal of what we were offering in that period of time was that they were running algorithms an doing some of this stuff.

00:08:39 Speaker 1

You know, obviously ahead ahead ahead of their time and they need it.

00:08:43 Speaker 1

There wasn't the cloud computing yet, so they were literally just trying to assemble the biggest.

00:08:49 Speaker 1

Supercomputers using off the shelf hardware that they possibly could so we weren't writing the algorithms.

00:08:55 Speaker 1

We were more enabling these algorithms to be run, but I would say the Fast forward is that in terms of my career, is that working on that led to?

00:09:09 Speaker 1

Being involved in sort of the mobile ecosystem from the launch of the App Store and the iPhone back in 2000, seven 2008 and in a way it was very very similar to what we did with the submarines. Because you were dealing with constrained hard.

00:09:25 Speaker 1

Where you always had to care about performance and battery life and battery life, less so on the Subs.

00:09:31 Speaker 1

But some of the same sort of constraints where you're trying to get the best performance you can out of these things and operating in that mobile landscape and building apps for some of the largest consumer brands.

00:09:46 Speaker 1

And then you guys mentioned in the in the intro about push IO.

00:09:49 Speaker 1

This mobile messaging company that we.

00:09:51 Speaker 1

Built, we ended up at Oracle building this mobile marketing engine is part of the Oracle Marketing Cloud an and one of the things that we saw there is that now.

00:10:03 Speaker 1

Fast forward to kind of more modern times and there's such a prevalent use out there of.

00:10:11 Speaker 1

Technology like email, you know email marketing systems and push notifications in the world of mobile in order to tackle kind of a fundamental problem that exists with some of these products, which is the user.

00:10:28 Speaker 1

Download your app, let's say, and they use it and then and then they churn, and then they abandon an and you as a publisher of a product like this, is one of the battles that you're trying to fight is how do I get them back into the experience and so are sort of observation is we were.

00:10:44 Andy

Right?

00:10:48 Speaker 1

You know, done our tenure there and we're looking to do something next.

00:10:52 Speaker 1

And new was a couple of things.

00:10:55 Speaker 1

The first thing we saw was that with the iPhone 10, I think it was.

00:11:01 Speaker 1

Apple released.

00:11:02 Speaker 1

Face ID.

00:11:03 Speaker 1

And that was using algorithms running on the device, so the benefit was you could unlock the phone very, very fast, but also it had some privacy characteristics where Apple doesn't need your face and the kind of the point cloud representation of your face to be up on their servers somewhere.

00:11:21 Speaker 1

That was really intriguing to us.

00:11:23 Speaker 1

The other thing was that we saw that the app economy, so to speak, was in transition from kind of the early days of where it was paid downloads.

00:11:33 Speaker 1

Transitioning to kind of in app purchases, which the game ecosystem has really been been focused on to trying to create more durable, sustainable revenue models through subscription.

00:11:35 Speaker 1

Which is right?

00:11:46 Speaker 1

And so how we sort of arrived at focusing a lot on data at NAMI.

00:11:53 Speaker 1

Is that it?

00:11:54 Speaker 1

It seemed to us like there was.

00:11:56 Speaker 1

If we we would, we really were excited about an idea that if we could.

00:12:02 Speaker 1

Help the guy.

00:12:04 Speaker 1

Is.

00:12:04 Speaker 1

App publishers a mechanism to send way fewer push notifications.

00:12:10 Speaker 1

An email messages because they had a technology stack that could allow them to detect in the experience, right directly on the device that somebody was showing signs of churn, or that somebody was showing some.

00:12:25 Speaker 1

Early intent that they might be a a candidate to be a subscriber, and so just that idea that maybe there's a way that we could be part of cutting down the messaging load by making the actual experiences smarter and more intelligent about what users are doing was where we.

00:12:42 Speaker 1

Started.

00:12:43 Frank

That's interesting.

00:12:43 Frank

That's it.

00:12:44 Frank

What sorts of signals?

00:12:47 Frank

That you can collect given specially with Apple's kind of enhanced privacy policies that they've been been doing.

00:12:55 Frank

An what?

00:12:56 Frank

What sorts of signals kind of indicate churn?

00:13:00 Speaker 1

So you know it is.

00:13:01 Speaker 1

It's a great question.

00:13:02 Speaker 1

When we started out we were thing.

00:13:04 Speaker 1

Gain, we're going to collect all this crazy stuff.

00:13:07 Speaker 1

I mean, we were even thinking at one point in the early prototyping that you know, maybe maybe, what carrier the user is on is some signal.

00:13:16 Speaker 1

Maybe the device form factor, whether it's the really expensive version of the phone or the lower you know there's all these things that we were thinking about, but.

00:13:24 Speaker 1

When when?

00:13:27 Speaker 1

And we're not my cofounder and I are not experts in this field, so one of the things that we did was we recruited our CTO who has a PhD in applied math and had been building data science animal models, kind of in production at, you know, in the real world.

00:13:46 Speaker 1

Applications of places like the Los Angeles Times and Tribune Publishing and one of the first things he told us when he came in was guys like, wait, you're trying to?

00:13:55 Speaker 1

You don't need all these days.

00:13:56 Speaker 1

Points a lot of what you're trying to collect just isn't isn't going to move the needle, and So what.

00:13:57 Speaker 1

Huh?

00:14:03 Speaker 1

It really gets to both on the so we look at, you know from subscriptions we're looking at.

00:14:07 Speaker 1

Kind of two things.

00:14:08 Speaker 1

One is what are signals that show that somebody might be have a propensity to purchase.

00:14:17 Speaker 1

And then, secondarily, that early turn detection, or kind of likelihood to churn.

00:14:23 Speaker 1

And it turns out it's it's pretty simple on some level, because it's really about the behavioral signals around engagement.

00:14:34 Frank

Interesting soon.

00:14:34 Speaker 1

So are they using the app or are they using the app a lot?

00:14:38 Speaker 1

Or they did they used to use it a lot and now they're not using it as much so those are kind of the key?

00:14:44 Andy

Signals, so you're not popping up little boxes and saying, do you want to keep using the app?

00:14:51 Andy

Check yes or no.

00:14:54 Speaker 1

No, I mean it's it's.

00:14:55 Speaker 1

It's funny, you know.

00:14:57 Speaker 1

I have a friend that has that has a company that that powers some of that around the ratings right?

00:15:05 Speaker 1

Do you want?

00:15:05 Andy

Yeah, yeah.

00:15:05 Speaker 1

To make this.

00:15:06 Speaker 1

Yep, and you know they have a really fascinating take on it, which is that.

00:15:11 Speaker 1

Because whenever I see one of those, I hit no, I don't.

00:15:14 Speaker 1

I you know, I just like want to dismiss it an.

00:15:17 Andy

Yeah, yeah.

00:15:18 Speaker 1

Yeah, he's got a strong viewpoint that by by asking a user a binary question it provides them better data for what they're trying to do around kind of customer sentiment an so I just thought I was fascinated by that because whenever I see one of those ratings popped up so I just wanted to like.

00:15:34 Andy

Interesting.

00:15:41 Speaker 1

I want to say no, even if I like the experience on some level, I have a visceral reaction that's just like I leave me.

00:15:47 Frank

No.

00:15:48 Frank

Right, right?

00:15:48 Andy

Well, I wonder if that's

00:15:48 Frank

Well, it's always when you're sorry, ID.

00:15:50 Andy

That's OK, go ahead.

00:15:52 Frank

It's always when you're trying to do something or the kids are screaming like do you want to write this?

00:15:52 Frank

It's always when you're.

00:15:56 Frank

Like no, I want to use this stupid app like even if I like it.

00:15:58 Frank

But what I find myself doing and I've as I'll say not now like like remind me