AI Radicals

How does the NBA use data to compete and improve? When it comes to driving business growth with data, transparent communication makes success a slam dunk. By sharing innovative ideas and best practices across the business, one all-star team elevates the success of others across the entire organization.

Michael James, SVP and Head of Data Strategy and Analytics at the NBA, is committed to creating a better fan experience and making better business decisions through collaboration. In this role, he bridges executive leadership and technical expertise to create a data-driven culture in constant pursuit of innovation. Satyen and Mike discuss the NBA’s digital transformation, the future of GenAI in the league, and attracting more people to sports business analytics.

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“We have very active communication with our teams. You build up a relationship over time and you start to realize, ‘If this person is sharing this thing that worked, we have a good sense of who else might be able to benefit from it.’ We'll make sure to package that up in a way that is not only informative, ‘Here's what the team did,’ but also has the tangible next steps. ‘Here's what you can actually do with this to drive the business.’ And it's no different on the data side. We've built a ton of data products through the years at the league level for our teams, also for different departments within our league office as well. But, the goal of all of those products is to make sure that we are driving better business decisions, we're driving a better fan experience, and, ultimately, that's going to lead to more revenue.” – Michael James

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Time Stamps:

*(13:16): Sharing the (data) ball among the league

*(17:34): Establishing best practices across an enterprise

*(37:08): Measuring performance to measure culture

*(41:16): Improving DEI in data

*(46:57): Satyen’s Takeaways

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Sponsor

This podcast is presented by Alation.

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* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/

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Links

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As data radicals, we want to deliver insights that enable our organizations to know more, which we often do by providing an answer. Instead, we should be thinking about frameworks we can implement to communicate our ideas in simple and consumable ways.

Dave Kellogg knows the importance of a framework. Dave is one of the leading enterprise executives in software today and currently serves as the Executive in Residence at Balderton Capital. His blog, Kellblog, is a highly regarded content hub for software leaders, drawing on his experience as an angel investor, board member, advisor, and thought leader. Satyen and Dave discuss the evolution of the data industry, problem solving with frameworks, and mapping your business in a complicated world.

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“People need the world simplified for them, and if you don't do it, somebody else will. A confused buyer is just going to buy from the market leader. If you're running a startup, you're definitionally not that. The burden of simplicity is on you. If you want to be successful, you need to have a very simple explanation of why someone should buy your stuff.” – Dave Kellogg

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Time Stamps:

*(03:58): The evolution of BI and the BI customer

*(22:25): Solving complex problems with simplifying frameworks

*(32:41): Defining “data intelligence”

*(43:16): The DNA of a D&A career

*(47:44): Satyen’s Takeaways

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Sponsor

This podcast is presented by Alation.

Learn more:

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* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/

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Links

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Follow Dave on Twitter

Read Dave’s blog

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If you’re on a journey of fitness, you know that perfectionism is your enemy. The same goes for data. There will always be another achievement that you wish to reach. Instead, focus on creating habits that will lead you to better data decisions and long term health.

Ameen Kazerouni knows this journey well. Ameen has spent his career at the intersection of science, data, and technology to create intuitive, data-driven experiences. In his role as CTO of Orangetheory Fitness, he is driving consumer wellness journeys by turning workout data into feedback and personalized recommendations. In this episode, Satyen and Ameen discuss data-driven exercise, keeping humans in the feedback loop, and AI data governance.

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“We make a lot of investment in demystifying the Orangetheory workout. And there's a lot of parallels to data, and I love that because when you think about data in an organization, ‘Well, it's going to be a multimillion dollar investment.’ And it can get so overwhelming that instead of being like, ‘Let's start piece by piece,’ the instinct becomes, ‘Let's just keep guessing instead.’ Which is never a good idea. You should never, ‘Let's just revert to not using data at all because it's going to be really difficult to use data perfectly.’ It's the same thing with fitness. You don't revert to doing nothing at all because meeting all the requirements will be hard. Showing up and getting started is what gets you going.” – Ameen Kazerouni

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Time Stamps:

*(04:42): AI in the workout

*(13:56): Data as a habit

*(25:45): AI data governance

*(38:36): The future of connected health

*(44:08): Satyen’s Takeaways

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Sponsor

This podcast is presented by Alation.

Learn more:

* Subscribe to the newsletter: https://www.alation.com/podcast/

* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: 

https://www.linkedin.com/in/ssangani/

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Links

Follow Ameen on LinkedIn

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We’ve all heard the term “data literacy” by now. Although there is general consensus regarding the importance  of knowing how to read, write, and communicate with data, some folks may take issue with the term itself. Wendy Batchelder, CDO at Salesforce, wants to reframe the conversation and focus on how people can leverage data to do their jobs better.

Wendy is a technology executive who has spent her career tackling business problems with technical solutions and transforming diverse team members into leaders. In her current role at Salesforce, Wendy is helping the right people access the right data at the right time — with the right controls. In this episode, Satyen and Wendy discuss the problems with data literacy training, the power of answering “so what?” questions, and the value of advocating for DEI in tech.

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“You have to drop the jargon and get down to what are you trying to explain? If you're trying to help people to use more data for decision making, then just introduce the data. Don't sit down and say, ‘We're gonna talk about data literacy,’ because everyone's eyes gloss over and you lose their interest and their attention. It just doesn't give you a lot of respect. Part of our job as data experts is to help people to use data better and that's the conversation that should be had. But, the second you say things like data literacy, the tone of the conversation totally shifts.” – Wendy Batchelder

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Time Stamps:

*(06:41): Data strategy at Salesforce

*(26:37): Keeping up with connectivity

*(28:40): Data literacy denial

*(35:22): DE&I in data

*(47:18): Satyen’s Takeaways

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Sponsor

This podcast is presented by Alation.

Learn more:

* Subscribe to the newsletter: https://www.alation.com/podcast/

* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/

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Links

Follow Wendy on LinkedIn

Read Wendy’s book Data Governance Handbook

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Before search engines, we had to rely on memory and investigation to answer our questions. Then, search engines made answers instantly available. Now, in the age of AI, we have to engineer our questions to get the best results.

Frank Farrall, Deloitte's Strategy & Analytics Ecosystems and Alliances Leader, knows that asking the right questions is just as critical as knowing the answers. Frank is a global business builder with 20 years of experience helping clients and startups become billion-dollar businesses through AI and digital transformation.

In this episode, Satyen and Frank discuss identifying worthy investments, the sexiness of prompt engineering, and efficient engagement with AI.

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“I think in a lot of cases, prompt engineering will at least become a skill that knowledge workers, creative workers use to get an outcome from the technology. I think some people will be highly, highly specialized. I actually think prompts are going to have value in organizations and I think prompt libraries and how you manage prompts will become a set of IP and something that's highly valuable inside organizations. I think prompt engineering has a very significant future ahead of it. I think all of us are going to have to learn some level of prompt engineering to be effective in the future.” – Frank Farrall

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Time Stamps:

*(02:42): Defining the AI ecosystem

*(07:55): How to identify a worthy investment

*(23:23): How “sexy” is prompt engineering?

*(41:44): The future of generative AI

*(44:43): Satyen’s Takeaways

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Sponsor

This podcast is presented by Alation.

Learn more:

* Subscribe to the newsletter: https://www.alation.com/podcast/

* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: 

https://www.linkedin.com/in/ssangani/

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Links

Follow Frank on LinkedIn

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As folks in the data space, we’re introverts by nature. But, getting out of our comfort zone can open you up to endless possibilities. As one person who’s gone from CIO to CEO can tell you, the key to growth is getting comfortable with feeling uncomfortable.

That person is Mike Capone, CEO of Qlik, where he’s revolutionizing the business intelligence landscape through data. In this episode, Mike shares with Satyen how his decades of experience in product development, data science, and go-to-market operations influence his role as CEO today. Satyen and Mike discuss transitioning from CIO to CEO, navigating economic downturns, and stepping out of your comfort zone.

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“Now is the time to get closer to your best customers. They're the ones who sustain you through these periods of economic ups and downs. The reality is for both of us and both of our companies, companies need data and analytics now more than ever. How are you going to navigate this uncertainty? You're going to navigate it through data. The conversation like, ‘Hey, we don't want to spend any more money on data and analytics because the environment is tough right now,’ is actually counterintuitive. The reality is you need data and you need real-time data to get through it because your old data models are useless.” – Mike Capone

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Time Stamps:

*(02:51): The growth of Qlik

*(08:37): The relationship between private equity and software

*(20:00): From CIO to CEO

*(27:29): Navigating rough economic times with data and analytics

*(33:10): Maintaining long-term landscape leadership

*(40:24): Satyen’s Takeaways

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Sponsor

This podcast is presented by Alation.

Learn more:

* Subscribe to the newsletter: https://www.alation.com/podcast/

* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: 

https://www.linkedin.com/in/ssangani/

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Links

Follow Mike on LinkedIn

Follow Mike on Twitter

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As human beings, we’re not accustomed to talking about data. In order to learn about new subjects, we traditionally use stories. However, bridging the gap between data and stories allows us to cross that barrier and create data-driven organizations.

In this episode, Satyen interviews Ashish Thusoo, GM of AI and ML at AWS. Previously, Ashish was the Founder and CEO of Qubole, a pioneering cloud data lake platform. He also served Facebook as the Engineering Manager of Data Infrastructure where he co-created Apache Hive with the aim to democratize data access and analytics. Satyen and Ashish discuss the accelerated push to the cloud, building a data culture, and how the economic climate is impacting customers.

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“You have to remember, human beings are trained from the get-go to talk about stories, not data. That's how we learn. It takes special discipline to bring the conversation back to data, saying that, ‘You have this anecdote somewhere. Get me the data that proves or disproves it.’ That specific mindset has got to be inserted in the organization, and that's how it becomes data-driven. It's a very fine line, but if you cross that line, essentially you become a data-driven organization. But, if you stay on the side of anecdotes and stories, then you can't bridge that.” – Ashish Thusoo

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Time Stamps:

*(02:33): The SQL excitement that powered Hive 

*(13:42): The evolution of Qubole’s founder hypothesis 

*(22:48): Navigating Amazon with AI/ML 

*(31:41): The future of AI/ML investment

*(42:01): People are the foundation of the data culture

*(45:57): Satyen’s Takeaways

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Sponsor

This podcast is presented by Alation.

Learn more:

* Subscribe to the newsletter: https://www.alation.com/podcast/

* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/

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Links

Follow Ashish on LinkedIn

Learn more about AI/ML services on AWS

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When building a data platform, it’s important to stay true to your vision. Whether that's through creating a definitive user experience or an open platform that allows people to build upon it, you’re constructing a cathedral. This cathedral is sophisticated and dependable, and allows for a bazaar of business intelligence, machine learning, and AI use cases.

In this episode, Satyen interviews Matei Zaharia, Chief Technologist and Co-founder of Databricks. Matei is an open source trailblazer and the creator of Apache Spark, a widely used framework for distributed data processing. He is also an Associate Professor of Computer Science at Stanford University where he leads various data management and machine learning projects. Matei and Satyen discuss the Databricks and Alation partnership, exploring how platforms can help companies own their data, and consider the value of democratizing open source large language models.

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“One of the early stories about open source has been this thing about the cathedral and the bazaar. The cathedral is the thing that's all designed by one person, maybe. It's extremely coherent and so on, but also takes forever to build. And when you go there, there's one message you're hearing. And then the bazaar is the open thing. You don't know who's going to show up each day, but there'll be some really interesting goods and things that you just wouldn't see anywhere else. If you just want to get started and get stuff done, follow the defaults in the product and it'll work. But, we want to be open to some of that innovation and let people bring that in.” – Matei Zaharia

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Time Stamps:

*(01:33): The story behind Spark

*(11:56): Solving for user problems versus product vision

*(20:12): The cathedral and the bazaar of open source

*(24:04): Matei explains the Databricks Unity Catalog

*(31:04): The Databricks and Alation partnership

*(43:36): The data culture at Databricks

*(48:21): Satyen’s Takeaways

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Sponsor

This podcast is presented by Alation.

Learn more:

* Subscribe to the newsletter: https://www.alation.com/podcast/

* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/

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Links

Follow Matei on LinkedIn

Follow Matei on Twitter

Learn more about Databricks’s Unity Catalog

Learn more about Alation + Databricks

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Once considered the outcast of Silicon Valley, data has metamorphosed as a cool kid that everyone wants to be friends with. In the last decade, data has solidified itself as the key to success in business. The same shift can be said for India who primarily operated behind the scenes, has emerged as a leader in innovation.

In this episode, Satyen sits down with Jitendra Putcha, EVP and Global Head of Data, Analytics, and AI at LTIMindtree. As an industry leader for over 20 years, he has solved data and analytics challenges for global companies by creating innovative next-generation solutions. Satyen and Jitendra discuss data platform modernization, data quality initiatives, and the future of AI and data science.

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“Gone are the days of looking at India as the back office and factory models, to looking at this is an opportunity. There are two, three reasons for it. One reason is about the startup ecosystem and the unicorns we started building, created aspirations for people and created curiosity for individuals even during school itself. Which wasn't the case a couple of decades back. That's one. The second is the promotion during school itself to encourage people to be driving incubation startups and throw their ideas has dramatically increased, there are many forums today. So, that's the second one. The third one, even the large SIs like us, today we have what we call entrepreneurs. Within our own ecosystem, people can come out with an idea, put an entire canvas and business plan, go to the board, get the funding, create that as an incubator, and go and test the market. If it is working, create that as an entire product line. I think when the young generation is able to get exposure, already been educated, and also they see in their workplace this kind of opportunity, I think that's the biggest benefit the younger generation is able to do, which probably wasn't the case before.” – Jitendra Putcha

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Time Stamps:

*(09:57): The evolution of service providers

*(13:22): The transformation of the Indian talent base

*(30:52): The data marketplace and “data as a service”

*(46:35): Defining the ROI of data tools

*(53:17): Satyen’s Takeaways

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Sponsor

This podcast is presented by Alation.

Learn more:

* Subscribe to the newsletter: https://www.alation.com/podcast/

* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/

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Links

Follow Jitendra on LinkedIn

Follow Jitendra on Twitter

Learn more about Snowflake Summit

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There are some things that just can’t be quantified by data; imagine trying to portray your childhood in a spreadsheet! Yet these experiences are valuable. How can data teams capture qualitative information – and use it to steer the business? It starts with getting your data team out of the building. Only then can they gain insights about customer pain points and what the data is failing to tell us.

In this episode, Satyen interviews Tricia Wang, a “tech ethnographer” and co-founder of Sudden Compass, a consulting firm helping companies improve their business through thick data. She also co-founded CRADL (Crypto Research and Design Lab) with the mission to create inclusive and sustainable growth of the crypto ecosystem. Satyen and Tricia discuss the power of thick data, the value of digital personhood, and the dangers of quantification bias.

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“Your job as a Chief Data Officer or a data leader in the company is, data is only part of your job generating the quantification to reflect back to the company. The other half is the bleeding edges around communication and helping the rest of your business, your business counterparts, to understand the value of this in a way that isn't scary and where they can see that it actually is going to improve their business. [...] But that takes a really brave kind of leader to work that way because it's not just about having the light shine on you, but it's about you making others and your company successful.” – Tricia Wang

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Time Stamps:

*(01:35): The role of a tech ethnographer

*(15:29): Tricia gives a rundown of thick data

*(23:06): Understanding customers by getting out of the building

*(32:36): Why quantification bias is dangerous to growth

*(44:48): The importance of digital personhood

*(57:22): Satyen’s Takeaways

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Sponsor

This podcast is presented by Alation.

Learn more:

* Subscribe to the newsletter: https://www.alation.com/podcast/

* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/

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Links

Follow Tricia on LinkedIn

Follow Tricia on Twitter

Watch Tricia’s TED Talk

Visit Tricia’s website

Learn more about Sudden Compass

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