What I am trying to do: As a data management professional working with large medical research consortium, I often encounter the situation when massive amounts of data, stored in multiple tables, needs to be combined into specific data sets based on particular criteria, or to be extracted and reported based on specific trials. The resulting datasets often become wider by incorporating fields from multiple tables, or longer by uniting multiple trials. Occasionally, the dataset thus obtained needs to be further manipulated by extracting or excluding certain subsets. This lesson is aimed to teach the researchers about the concepts of JOIN, UNION, INTERSECT and MINUS operators.
My Spiel:
Big data is everywhere. We are surrounded by the amounts of data that needs to become information in order to bring us new knowledge. Learning how to master the querying of the data can save you many hours of tedious separation of the wheat from the chaff.
We will learn how to create datasets from multiple tables based on common fields, how to combine several sets based on specific criteria, and how to subtract one dataset from the other to eliminate undesired results.