Common Data Mistakes

Wrong way, if you see these mistakes turn back!
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This isn’t meant an an exhaustive list but just the most common errors I’ve seen over the years.

  • Taking the average of values that are already an average
  • Trying to join database tables on fields with different data types
  • Processing data you will later discard, do filtering early on
  • Using averages when mean or mode is better (the average person has 1,9999 legs)
  • Forgetting seasonality in data
  • Accidentally filtering out data by incorrect combining of AND/OR statements
  • Errors caused by fixed length string in databases (often space padded like ‘DataPoint ‘)
  • Accidentally missing data by being provided data from a source that already has hidden filters applied
  • Losing data when joining tables in SQL due to missing data in one table (use outer joins)
  • Poor data quality (countries stored as UK, GB, England etc. in the same field, phone number with 00 and + prefixes)
  • Null data breaking report filters and SQL where statements
  • Misusing null in Boolean fields (1 is true, 0 is false and null is unknown)
  • Storing data as generic data types (dates as text, numbers as text, Boolean as integers and so on)
  • Storing the same data point in different tables with different data types
  • Being inconsistent in naming conventions (my_table, MyTable), pick one and stick to it
  • Using cryptic names for fields instead of names that make sense (max_temp is OK m_tmp is ambiguous)

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