Update and Deletion Anomalies
When a fact is stored in many rows, partial updates create contradictions and deleting a row can erase a fact kept nowhere else. Normalization prevents both.
-
-
Denormalization
Denormalization copies facts into more places so reads get simpler or faster. The price: every copy must be kept consistent by something other than the schema.
-
Operational vs Analytical Data Models
Operational and analytical models face different pressures for writes, scans, meaning, and history. See what each protects and how to connect them.
-
Cosine Similarity
Cosine compares vector directions. Normalization changes distance rankings, coordinate scaling changes meaning, and retrieval thresholds need evaluation.
-
Normalize (in Feature Engineering)
With fold-local scaling, k-nearest neighbors rose from 0.6215 to 0.7175. Logistic regression was 0.7282 in both raw and standardized form; forest results were nearly unchanged.
-
Data Modeling for OLTP and OLAP Systems
How row meaning, identity, dependencies, aggregation, and time shape operational and analytical data models.