The practice of data science requires data — data that comes in all forms, formats, platforms and structures. Because of this complexity we commonly hear that data scientists spend as much as 80% of their time ‘wrangling’ data and only 20% producing actionable outcomes. We invite you to attend this session to see how the Pareto rule can be flipped by a demonstration of data virtualization tools within data science notebooks, using Python and R.
About the Speakers
Ed Robbins has been on the Denodo team as a solution engineer for 4 years. He has been led and been engaged with Fortune 1000 companies to drive highly successful projects in the course of his career. Prior to joining Denodo he was with Oracle for 20 years with a focus on BI/Analytics, Data Integration (ETL), and Data Warehousing. Ed resides in Chicago, IL
Tom LaSalle has spent the better part of his career on data integration architecture patterns known as middleware. This includes internal process, data, and application integration as well as B2B integration. With this experience and highly successful customer implementations leveraging On Premise, Cloud and Hybrid integration topologies, Tom brings both a pragmatic and visionary point of view for clients who are evolving their data architectures toward digital transformation. Tom resides in Columbus, Ohio.
Presentation Materials
A recording of this talk is available on the Columbus Data Science YouTube channel