Review lookup data load behavior for cache freshness, comparison rules, duplicate reference keys, and unmatched rows before trusting the output.
What Is a Data Warehouse?
A data warehouse is built for questions, not transactions. Facts and dimensions in plain words, why the star schema reads the way people talk, what a date dimension is for, and when you do not need one.
Incremental Loads: Moving Only What Changed
Design an incremental load with reliable boundaries, retained change information, delete handling, and a watermark that advances only after success.
Tabular Models for the SQL Developer
Tabular models for the SQL developer add relationships, measures, security, and reusable semantics above SQL tables; learn when a view is enough.
Summary Tables: Keeping Pre-Aggregated Totals Current
Keep summary tables current with changed-day rebuilds, handle late arrivals and deletes, and reconcile stored totals against detail.
Data Integration Patterns Without Special Tools
Data integration patterns in SQL Server cover full reloads, incremental pulls, change capture, and file drops with clear restart rules.
Data Quality Checks Worth Running After Every Load
Run data quality checks for missing values, duplicate keys, invalid ranges, and count reconciliation before promoting a loaded batch to production.