Course curriculum

  • 1

    SQL Powers and Limitations

  • 2

    Working with Fallible Humans and Precise Machines

    • Examples of how SQL’s literalism can trip you up

    • Good data, bad data, no data - and what to do about it

    • Using wildcards to compensate for sloppy data input

    • Case Study: 43,000 Column Headers, and the 14-named man
  • 3

    Getting to Know Your Data with Curiosity and Play

    • Wrapping your mind around what’s happening in the data

    • How playing with your data can improve your queries and prevent bad mistakes

    • Extrema power: The importance of null, max, min

    • Identifying data requirements

    • Translating data questions into SQL code requirements

    • Telling bigger stories by joining multiple datasets

    • Case Study: How to spot and handle fraud in your data
  • 4

    Generating Insights and Telling Stories with Data

    • Using data to tell stories: No more glazed eyes

    • Getting inside the boss’s head: What the boss wants to know

    • Case study: Shell companies, fake directors, and the apartment with 1,000 businesses
  • 5

    Learning About a Company’s Data Culture and Democratizing Analytics

    • Befriending your database admins

    • Injecting wisdom into an organization’s data practices

    • Sharing is caring: How to use SQL libraries and code snippets

    • Inspiring a passion for data on the team