Tag
Data Warehousing
10 post(s) tagged with Data Warehousing.
Choosing an Analytical Architecture Without Starting with the Product
A requirements-led comparison of data warehouses, data lakes, lakehouses, and combined analytical architectures, including how these ideas appear in Microsoft Fabric.
Designing a Warehouse That Can Be Operated, Not Just Built
How service objectives, monitoring, capacity planning, recovery, security, and controlled change turn a deployed data warehouse into a dependable analytical service.
ETL, ELT, and the Work Required to Make Data Trustworthy
How ETL and ELT differ, what dependable data transformation involves, and how validation, restartability, and reconciliation turn a completed load into credible evidence.
Keeping Historical Context in a Data Warehouse
How to decide whether warehouse data should show the current view, retain earlier business context, or restate history when records arrive late or require correction.
Designing a Dimensional Model That Reflects the Business
A practical guide to selecting a business process, declaring the grain, identifying dimensions and facts, and designing analytical models that support valid decisions.
From Source Systems to Business Insight: The Layers of a Data Warehouse
A practical guide to the ingestion, staging, transformation, warehouse, semantic, and consumption responsibilities that turn source data into trustworthy analytical information.
Start with Decisions, Not Tables: Planning a Data Warehouse
A practical guide to defining the decisions, business processes, ownership, scope, and delivery approach that should shape a data warehouse before technology choices begin.
What a Data Warehouse Is Really For
A practical explanation of the problems data warehouses solve, how they differ from operational systems, and when building one may not be justified.
Completing a SQL Sales Analytics Project
A practical review of an end-to-end SQL sales analytics project, its business findings, technical outcomes, remaining limitations, and next steps into Microsoft Fabric and Power BI.
Designing an Analytics-Friendly Data Model
A practical dimensional-modelling case study that transforms AdventureWorks OLTP sales data into a validated star schema for analytical reporting.