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On a given project, data scientists can spend upwards of 80% of their time preparing, cleaning, and correcting data. In this session, we will look at different data cleansing and preparation techniques using both SQL Server and R. We will investigate the concept of tidy data and see how we can use tools in both languages to simplify research and analysis of a small but realistic data set.
About Kevin Feasel ...
Kevin Feasel is a Data Platform MVP and Engineering Manager of the Predictive Analytics team at ChannelAdvisor, where he specializes in T-SQL and R development, fighting with Kafka, and pulling rabbits out of hats on demand. He is the lead contributor to Curated SQL (curatedsql.com (http://curatedsql.com/)) and a contributing author to Tribal SQL (www.tribalsql.com (http://www.tribalsql.com/)). A resident of Durham, North Carolina, he can be found cycling the trails along the triangle whenever the weather's nice enough.