The Data Standard

Data Models with Sean Robinson
Sean Robinson, Lead Data Scientist at Graphable sits down with TDS to discuss Data Models and his company Graphable.

Episode Summary

Today’s TDS episode is all about data and data models, and why they matter. Deciding how to model your data ahead of time can pay off down the road. It helps ensure that the people who are using the data get what they need from it and can reduce technical debt. Data modeling is a way of mapping out and visualizing all the different places that a software or application stores information, and how these sources of data will fit together and flow into one another. This is a hugely important stage in the design process for any business-critical IT system. When developers are figuring out how a new system will work, they establish what the most pressing needs of a business are, what kind of data they’ll need to access in order to meet those needs, and how the data will be used. From there, they can start to create a diagram (or model) of how each pocket of data will flow into each other, and how they’ll interact.

Meet The Host

Catherine Tao

Data scientist at The Data Standard

Catherine Tao is a tech enthusiast looking for new methods for building connections with businesses around the world. Her extensive knowledge of data science allowed her to develop new solutions and implement them into existing ecosystems. She is currently working as a Data scientist and Exclusive Podcast Producer at The Data Standard.

Meet The Guest

Sean Robinson

Lead Data Scientist at Graphable

A versatile data scientist with significant experience optimizing processes in a leading financial institution and a specialization in graph analytics for financial crimes. Highly adept at aligning the vision of stakeholders to implement data-driven transformations within corporate structures. Seeking the next professional challenge that blends domain knowledge, computer science, and mathematics with a natural aptitude for connecting with people to enable organizations to thrive in an increasingly data-driven business landscape.