You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data.
This session will help you to develop datasets for exploration, analysis, and machine learning. The author Renee Teate will answer questions about her piece SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis.
Speaker:
Renee M. P. Teate, Director of Data Science, HelioCampus
Moderators:
Aakansha Neema, Senior Data Scientist, SAP
Anjali Unnithan, Data Scientist, SAP
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SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that’s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls.