Data Governance
Ownership, lineage, quality, catalogues and who may see what.
3 to work through
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intermediate
A dashboard has been wrong for three weeks. Nobody knows which upstream produced the table it reads. What is the governance failure, and what fixes it?
2 min answer -
intermediate
Two teams compute "active user" differently and both numbers appear in board reporting. Which governance mechanisms address this, and which would not?
2 min answer -
advanced
In a large enterprise, multiple teams write directly to the same core business tables and change schemas independently. What problems emerge, and what governance changes fix them without stopping delivery?
3 min answer
4 terms in this topic
Data Catalog
A searchable inventory of datasets with their schema, owner, meaning, freshness, quality and classification.
practiceData Governance
Making data ownership, meaning, quality and access explicit — the mechanism that keeps a data platform trustworthy as it grows.
practiceData Lineage
A record of where each dataset came from, what transformed it, and what depends on it — traced at table and ideally column level.
practiceExpand and Contract Migration
Changing a schema through a sequence of individually backward-compatible steps, so old and new application versions can run simultaneously.
Neighbouring topics
Data Architecture
General material on structuring, storing and governing data.
Relational Modelling
Normalisation, keys, constraints and the invariants a schema enforces.
NoSQL Stores
Key-value, document, wide-column and graph — what each buys and forbids.
Indexing
Designing indexes per query shape, and paying for them on every write.
Query Optimisation
Reading a plan, fixing statistics, and finding the real bottleneck.
Transactions & Isolation
ACID, isolation levels, and the anomalies each level permits.
Replication
Primaries, replicas, lag, and synchronous versus asynchronous durability.
Partitioning & Sharding
Splitting data across machines, and the one-way door of a partition key.
Caching Strategies
Cache-aside, read-through, write-through and where each belongs.
Cache Invalidation
Stampedes, penetration, staleness windows and versioned keys.
CQRS
Separating the write model from the read models that serve queries.
Event Sourcing
Storing the change log as the system of record, and what that costs forever.
Change Data Capture
Turning a database's replication log into a stream, and its coupling risk.
Data Warehousing
Dimensional modelling, star schemas and analytical workloads.
Data Lakes & Lakehouses
Open formats on object storage with transactional metadata on top.
ETL & ELT
Where transformation happens, and how much raw history you keep.
Streaming Data
Windowing, watermarks, late arrivals and exactly-once semantics.
Data Lifecycle & Retention
How long data is kept, where it ages to, and how it is actually deleted.
Polyglot Persistence
Choosing a store per workload, and the operational cost of variety.