In this episode, guest Matt Thompson sits down with TDS to discuss his pandemic work-life experience.

Matt Thompson
https://www.linkedin.com/in/matt-thompson-98355651/

The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Microfinance is a service where financial institutions back small start-ups and would-be entrepreneurs with small loans, oftentimes referred to as microloans. Such initiatives are most popular in the poorest parts of the world.

In this business model, big data is used to assess a customer’s creditworthiness. Big data is defined as large volumes of structured and unstructured consumer data that can be gathered from a user’s entire profile of online activity, be it on social media platforms, product purchases, or electronic check-ins.

Such data is usually collected from various data points, which vary according to the type of online activity performed. An example of this is phone usage data which includes call duration as well as the frequency of calls.

It is this kind of data that will then be used to assess a customer’s ability to repay a loan provided via a microfinancing scheme. What is used is not the direct content of the data, but rather the behavioral patterns associated with the data collected.

Big data analytics is an increasingly integral part of the tech ecosystem and is fast disrupting the financial services industry as well. The ability to transform raw data into meaningful insights is the cornerstone of cross-industry development.

Mansoor Ahmad
https://www.linkedin.com/in/mansoornano/

The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Aristotle Socrates, Head of Data at TextNow, sits down with TDS to discuss his views on machine learning, ai, and what he deems was the most important trend of the last 20 years.

Aristotle Socrates
https://www.linkedin.com/in/aristotle-socrates-9066271b/

The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

In an ideal world, startups progress through inflections of growth and success as customers require more enhancements or features that are needed on a larger scale. The startup’s engineering team has to grow to address these different dimensions and do it with increasing pace and predictability. Scaling an engineering team can seem like a mighty feat. A growing company is going to be in need of a growing engineering team to keep up with the demands of the job. Whether you need three or 30 engineers on your team, it is important that you take the necessary action to get qualified and experienced engineers on your team.

Jeremy Eastwood
https://www.linkedin.com/in/jeremy-eastwood/

The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Your quarterback goes down, and you need a new one. So, you look at the stats on the site to find a guy who had a good couple of weeks. Plus, you saw an interview with the guy, and he seems nice. You just have a feeling about him, so you pick him up and add him to your fantasy football roster. You may have made a mistake.

Picking a player while letting your emotions play a factor is not going to mean you failed completely. Plenty of people have had successful teams with this method. However, using data science to evaluate the potential of a player for the rest of the season is more likely to give you an edge. Data still typically beats your gut feeling.

Kevin Day, Founder at Fantasy Football Calculator, sits down with TDS to discuss the data behind fantasy football.

Kevin Day
https://www.linkedin.com/in/kday33/

The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Have you seen real estate listings that describe a house as architect-designed? It adds a lot to the asking price, but aren't all houses designed by architects? Most are, but they're then rather generically churned out by a construction company. If your house counts as architecture, though, someone designed it for specific needs and tastes.

In the same way, your organization stands to benefit when your data architecture is put together based on your particular data management and analytics needs. But often, we inherit many of the generic components and integrations from the product designs of our technology vendors. If we've customized some of the structure of data architecture, that may have happened ad hoc, over a long time.

Within a successful data architecture, a conceptual design based on the business process is the most crucial ingredient, followed by a logical design that emphasizes consistency, integrity, and efficiency across all the databases and data pipelines. Once the data architecture is established, the organization can see what data resides where and ensure that the data is secured, stored efficiently, and processed accurately. Also, when one database or a component is changed, the data architecture can allow the organization to assess the impact quickly and guides all relevant teams on the designs and implementations. Lastly, the data architecture is a live document of the enterprise systems, which is guaranteed to be up-to-date and gives a clear end-to-end picture. In summary, a holistic data architecture that reflects the end-to-end business process and operations is essential for a company to advance quickly and efficiently while undergoing significant changes such as acquisitions, digital transformation, or migration to the next-gen platform.

Derek Doel
https://www.linkedin.com/in/derekdoel/

The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Over the past few years, Data Science and Analytics have become popularized and more and more ingrained in every aspect of our lives. Data science has spread to almost every industry, but there are still a few where it has just hit the surface, one of which is the gaming industry and the impact of it is growing very fast. Human-oriented games are now evolved into data-oriented games.

The gaming industry is on its rise nowadays. With more than 2 billion players all over the world gaming industry is a resource of enormous revenues and these revenues are expected to grow further on. With a growing number of users, the amount of data to proceed is enlarging. Users’ playing time, interaction time, quitting point, peaks of activity, results, scores, etc. present vast material for analytics.

The use of Data in gaming is to make strategies according to the behavior of the player and constantly collecting data and making predictions and decisions. The new generation of gaming is dependent on data collection by analyzing the behavior of the player and the use of Artificial Intelligence and Machine Learning for better development.

Francisco Rius, Head of Data Science - Minecraft at Microsoft, sits down with TDS to discuss the intersection between art and science.

Francisco Rius
https://www.linkedin.com/in/franciscorius/

The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

The COVID-19 pandemic and the resulting stay-at-home orders have led to significant changes in the way people work. One of these changes involves the increased use of video conferencing as a means of communicating or holding work meetings. In this episode, guest Hisham Hamadeh sits down with TDS to discuss ways that the pandemic might have helped transform how we identify and commercialize treatments for other illnesses.

Hisham Hamadeh
https://www.linkedin.com/in/hisham-hamadeh-5a342ba/

The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Carlton Sapp is the Managing Vice President for the Data Analytics for Technical Professionals team. Dr. Sapp sits down with TDS to talk about all things AI. In addition to managing the data analytics team in Gartner for Technical Professionals, Dr. Sapp provides guidance on systems engineering, digital engineering, digital threads, digital twin, model-based systems engineering, edge intelligence, artificial intelligence, machine learning, modern data management strategies, data ingestion strategies, streaming analytics, data integration, and IoT analytics. Dr. Sapp provides data-driven insights and design strategies based on more than 25 years of practical project experience and research. He is known for using systems thinking approaches to solve complex technical and business challenges. In previous roles, Dr. Sapp designed digital assets, agent-based systems, digital twins, data analytics architectures, advanced analytics architectures, data integration strategies, distributed compute systems, service-oriented architectures, event-based architectures, and machine learning algorithms.


Carlton Sapp
https://www.linkedin.com/in/drcarltonesapp/

The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Today's guest is the great and brilliant Dr. Pavel Dmitriev, VP of Data Science at Outreach.io. This AI-driven sales engagement platform has raised over $250 million since founded in 2011. We talk about all things. Sales engagement- and one thing- that's really interesting in this podcast- is how we get better at doing sales engagement. Sales engagement is not simple for a variety of reasons. Approaching one cold prospect in a way that increases the chance of their conversion is challenging enough — handling the logistics of hundreds or thousands of leads is exponentially harder. That’s why software platforms with email marketing automation features—outreach among them—serve to simplify the process. There are plenty of solutions for sales management that provide autoresponder features, but the real question is—are these templated responses organic enough to enable high conversion rates?

Pavel Dmitriev
https://www.linkedin.com/in/paveldmitriev/

The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q