
Dive Into the Data Lake
Grab your snorkel: it's time to find out why a well-governed, well-catalogued data lake beats a murky data swamp.
- Технологии
- Възрастни
- Средна
- Забавна
- 10 въпроса
- около 5 мин
- Обратна връзка след всеки въпрос
Един срещу друг
За деца и големи деца
Виж въпросите
Без верните отговори, за да са изненада, когато играеш.
Въпрос 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
Въпрос 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
Въпрос 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
Въпрос 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
Въпрос 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
Въпрос 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
Въпрос 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
Въпрос 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
Въпрос 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
Въпрос 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






