Occupational Data and Automation Risk
ETL Summary
Extract: Data Source #1: May 2018 National Occupational Employment and Wage Estimates 2018 File Type: XLSX https://www.bls.gov/oes/current/oes_nat.htm Data Source #2: Automation Risk and State Work Populations File Type: CSV http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf
Transform: Join both data sources through occupation codes (as a string)
Load: Final database Relational SQL (pgadmin) Benefits of Relational: Support to Operations Set on Theory/Dynamic Views There are a lot of ways to cut the data included in this set depending on the focus of your analysis suggesting that a relational database would be most effective