Design Tip #171 Unclogging the Fact Table Surrogate Key Pipeline

We characterize the ETL system as a back room activity that users should never see nor touch. Even so, the ETL system design must be driven from user requirements. This Design...

Quadrant Magic ETL 2012

Selon le dernier Quadrant Magic ETL, version Octobre 2012, réalisé par Gartner et améliorée par toolbox.com, en mettant en évidence la comparaison entre 2011(point orange) et 2012 (point rouge), Informatica et IBM  maintiennent...

Design Tip #142 Building Bridges

This Design Tip continues our series on how to implement common dimensional design patterns in your ETL system. The relationship between a fact table and its dimensions is usually many-to-one. That is,...

Design Tip #137 Creating and Managing Shrunken Dimensions

This Design Tip continues my series on implementing common ETL design patterns. These techniques should prove valuable to all ETL system developers, and, we hope, provide some product feature guidance for...

Design Tip #127 Creating and Managing Mini-Dimensions

This Design Tip describes how to create and manage mini-dimensions. Recall that a mini-dimension is a subset of attributes from a large dimension that tend to change rapidly, causing the dimension...

Six Key Decisions for ETL Architectures

This article describes six key decisions that must be made while crafting the ETL architecture for a dimensional data warehouse. These decisions have significant impacts on the upfront and ongoing cost...

Slowly Changing Dimensions

The notion of time pervades every corner of the data warehouse. Most of the fundamental measurements we store in our fact tables are time series, which we carefully annotate with time...

Subsystems of ETL Revisited

The Kimball Group has been exposed to hundreds of successful data warehouses. Careful study of these successes has revealed a set of extract, transformation, and load (ETL) best practices. We first...

White Paper: An Architecture for Data Quality

In this white paper, Ralph proposes a comprehensive architecture for capturing data quality events, as well as measuring and ultimately controlling data quality in the data warehouse. This scalable architecture can...

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