Week 6

From the 5 Rules of Data Normalization poster:

• Unnormalized data
  • redundant and repetitive data (jagged length rows)
• 1st Normal Form (1NF) – eliminate repeating groups
• 2NF – eliminate redundant data
• 3NF and 3.5NF BCNF (Boyce-Codd NF) – eliminate columns not dependent on key
  • 3NF on the poster is really BCNF
  • oath: Each attribute in a table must be a fact about the key, the whole key, and nothing but the key, so help me Codd.
• Higher normal forms
  • 4NF – isolate independent multiple relationships
  • 5NF – isolate semantically related multiple relationships

• Recommendations DB for Books, TV shows, movies…
• Student-run Rock museum - WARTHIN (local - Vassar)
• Business accelerator / Venture Capital (source: non-profit.org)
• Olympic-related (countries, events, ticket sales) (Kaggle)
• Music Library - collections, composer, key, genre
• Alumni - maybe CS-specific? (like Vassar Net)
• Last.FM (Spotify, YouTube) - common tracks among users, most common for an individual user
• Pokeman DB
• Animals used in Scientific Research, what we do to them, etc. (local to Vassar)
• Start-up DB - what kinds, trends for success/failure
• Rate My Professor - integrate with AskBanner
• Deece DB (menus, by day, when are certain foods served?)
• Boardgame DB (search for board games based on attributes)
• Data Analysis - from Government, pre/post pandemic, etc.
• NFL DB - statistics, analysis, consistency among players
  • variation: at the team level, predictions

• what database project would you like to work on?
  • it doesn't need to be one of the ones we brainstormed–that was just to get us thinking about the possibilities
• who would you like to partner with? (ideally groups of two)
• do you need help finding a partner?