Dive Into the Data Lake

Without the right answers, so they're still a surprise when you play.

1. Question 1

   What's the big idea behind a data lake?

   • Storing raw data of any kind at scale, ready for later use
   • Storing only cleaned, modelled data for monthly reports
   • Replacing every database with one giant spreadsheet
   • Holding only structured sales tables in fixed predefined schemas

2. Question 2

   A data lake applies structure when data is read, not when it's loaded. What's this called?

   • Schema-on-write
   • Schema-on-read
   • Lazy normalisation
   • Deferred indexing

3. Question 3

   Your lovely lake has turned into a 'data swamp'. What most likely went wrong?

   • It ran out of storage space
   • Too many people were allowed to read it
   • Data was dumped in without governance or metadata
   • It stored unstructured data alongside tables

4. Question 4

   Which best describes data governance?

   • The IT team's job of backing up servers nightly
   • A one-off clean-up project before an audit
   • Software that automatically deletes old files
   • Policies, roles and rules for managing data as an asset

5. Question 5

   What does a data catalogue mainly help people do?

   • Find, understand and trust available datasets
   • Automatically fix spelling errors in customer records
   • Speed up queries by compressing tables
   • Turn raw data into finished dashboards

6. Question 6

   Sales says 'customer' means anyone who's bought; Marketing includes sign-ups. Which tool settles the row?

   • A data backup
   • A data dictionary
   • A data pipeline
   • A data lake

7. Question 7

   Who is usually accountable for the quality and meaning of a dataset day to day?

   • The cloud hosting provider
   • Whoever queried it most recently
   • The data steward
   • The chief executive personally

8. Question 8

   A report shows odd figures. What lets you trace where that data came from and how it changed?

   • Data compression
   • Data sharding
   • Data masking
   • Data lineage

9. Question 9

   What's a key business benefit of combining a lake with good governance and a catalogue?

   • Faster, trusted self-service analytics
   • No need for any security controls
   • Data never needs updating again
   • Every user can edit every dataset freely

10. Question 10

    Under GDPR, how does governance help with personal data in a lake?

    • GDPR doesn't apply to raw data
    • It tags and controls personal data so access and deletion are managed
    • It moves all personal data outside Europe
    • It lets you skip consent if data is anonymous-ish