The Data Standard

In this episode, we were honored to welcome as our guest Anita Ward, an applied anthropologist and Chief Development Officer of Salary Finance. Our conversation with Anita was about so much more than Anthropology and data. We talked about Salary Finance’s social purpose and how their work is bringing financial literacy and financial dignity to millions of people. Anita started by graciously sharing her emotional story of growing up without a home address. She got her first taste of financial empowerment from her first job at a McDonald’s in Las Vegas at just fifteen years old. Watching her parents struggle to find their financial footing, Anita knows firsthand the insecurity and taboo that surrounds families who experience financial hardship. She also shares new research that shows just how much employees’ financial stress is costing employers and what they can do about it. We’ll chat about how Salary Finance’s financial tools and borrowing options are helping employees rebuild their finances and their credit.


Anita Ward
https://www.linkedin.com/in/anita-ward-4567a39/

The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.

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

As the Global Artificial Intelligence Lead and innovation lead within PwC’s Emerging Technology practice, Dr. Anand S. Rao is responsible for research and commercial relationships with academic institutions and start-ups, research, development, and commercialization of innovative AI, big data, and analytic techniques. With over 35 years of industry and consulting experience, he leads a team of practitioners who advise C-level executives and implement advanced analytics and AI-based solutions on a variety of strategic, operational, and ethical use cases. Drawing from his Ph.D. and research career in AI, as well as his subsequent experience in management consulting, Anand sits down with TDS to discuss the commitment to responsible ai.

Anand Rao
https://www.linkedin.com/in/anandsrao/

The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.

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

In today’s information-driven business environment, data is the fuel for growth. The more decision-makers know about their employees’ needs, changes in the industry, and the demands of customers, the more prudently they can strategize for future expansion. Big data has unlocked fresh possibilities, providing remarkable insights into market conditions and a heightened awareness of unfolding opportunities.
Collecting large quantities of data and finding analytical insights has become an integral part of how organizations of all kinds evaluate their progress and develop growth strategies. With the tremendous capacities for storing information in cloud-based solutions, businesses have the means to acquire a more detailed understanding of everything from the efficiency of manufacturing to the effectiveness of marketing campaigns.
Organizations can draw on data tools to discover areas that are currently ripe for improvement and garner a peek at the challenges and opportunities that lie ahead. With predictive analytics and machine-learning systems, businesses gain a sense of how existing problems or emerging ideas for growth will play out in the future. Those findings allow leaders to make smarter decisions and achieve long-term, sustainable success. In this episode, guest Dave Cook sits down with TDS to discuss how emerging companies should use their data.

Dave Cook
https://www.linkedin.com/in/cookdave703/

The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.

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

These days it’s a given that data needs to flow between systems, teams, and partners in order to deliver digital customer experiences and drive competitive insights – but very few companies take a strategic approach to governing these data flows across their business ecosystems. In this episode, guest Abhi Sharma sits down with TDS to discuss the ecosystem of data.

Abhi Sharma

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

The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.

https://datastandard.io 

https://www.linkedin.com/company/the-data-standard 

https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q 

In this episode, guest Jason Hughes sits down with TDS to discuss how post 2020 has brought a separation of data analytics and data infrastructure. If you are daunted by the needs of your data infrastructure then it’s worth listening to how Jason and his team are approaching the problem.

Jason Hughes

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

The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.

https://datastandard.io 

https://www.linkedin.com/company/the-data-standard 

https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q 

In this episode, guest Myles Guanzon sits down with TDS to discuss the ways that digital platforms are innovating the healthcare industry. Myles Guanzon is a servant engineering leader with a strong passion for data-driven, lean product development, Myles comes from a non-traditional engineering background. His career started in DevOps with server management and progressed by learning web development and co-founding a design agency to develop web applications for clients, including NASA. Today as the VP of Engineering at Omada Health, Myles leads the B2C teams that are responsible for engaging its members into lifelong health.

Myles Guanzon

https://www.linkedin.com/in/myles-guanzon-9ab50020/ 

The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.

https://datastandard.io 

https://www.linkedin.com/company/the-data-standard 

https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q 

Lon Baker, COO of VirtualPBX, has decades of experience in telecommunications, both as an entrepreneur and as a prominent figure of the company he now leads. His ambition and hard work have propelled VirtualPBX to be a global provider of voice, video, and texting services for businesses of all sizes. He has reshaped the way in which VirtualPBX serves its customers and has played a pivotal role in the company’s recent migration from its legacy platform of the 2000s to the current API-based Dash platform it now uses. There is no individual better suited to speak about data and cloud platforms.

Lon Baker

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

The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.

https://datastandard.io 

https://www.linkedin.com/company/the-data-standard 

https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q 

Scalability, scalability, scalability, scaling, these words represent the same concept: the ability for data processing systems to increase their processing capabilities as data increases. Scalability, therefore, corresponds to the ability of systems to evolve in order to process data of a different nature in large quantities and in always faster. If latency is taking too much progress and some internal or external customers are complaining about the slowness of your systems, it's time to focus on the issue of scalability. In this episode, guest Ken Tidwell sits down with TDS to discuss data scalability.

Ken Tidwell

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

The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.

https://datastandard.io 

https://www.linkedin.com/company/the-data-standard 

https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q 

Data comes in many forms, all of it messy. Whether we’re talking about missing data, unstructured data, or data that lacks regular structure, you need methods to cleanse data before you can process it to improve its quality.

In this episode, guest Sean Gupta sits down with TDS to discuss data models, risk assessment, and machine learning role in the healthcare industry. Sean also discussed why machine learning predictions based on criminal history perform better than models based on DASH features.

Sean Gupta

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

The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.

https://datastandard.io 

https://www.linkedin.com/company/the-data-standard 

https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q 

Data comes in many forms, all of it messy. Whether we’re talking about missing data, unstructured data, or data that lacks regular structure, you need methods to cleanse data before you can process it to improve its quality.

In this episode, guest Sean Gupta sits down with TDS to discuss data models, risk assessment and machine learning role in healthcare industry.  Sean also discussed why machine learning predictions based on criminal history perform better than models based on DASH features.


Sean Gupta
https://www.linkedin.com/in/arijitseangupta/

The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.

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