Data Warehousing Architecture - Designing the Data Staging Area

The staging area tends to be one of the more overlooked components of a data warehouse architecture, and yet it is an integral part of the ETL component design. Learn why it is best to design the staging layer right the first time, enabling support of various ETL processes and related methodology, recoverability and scalability.

How to Conduct Effective Data Warehouse and Business Intelligence Software Evaluations

Denise Rogers discusses the essential tasks in conducting effective software evaluations revolving around data warehousing and business intellegence. Each step has a dependency on the previous one, starting with establishing the framework of the evaluation and adding progressively elaborate data that facilitates a decision making process that is resolute.

HASHBYTES can help quickly load a Data Warehouse

Data warehouse loads can be time consuming - this method can be used in some instances to help speed things up.

Kimball University: Three ETL Compromises to Avoid

Why neglecting slowly changing dimensions, failing to capture metadata and overlooking scope creep can be the undoing of a dimensional data warehousing initiative.

Slowly Changing Dimensions

Data Warehousing 2.0 and SQL Server: Architecture and Vision

Architecture and data warehousing are not static. From the first notion of a data warehouse to a full-blown analytical processing architecture that includes data marts, ETL, near line storage, exploration warehouses, and other constructs, data warehousing and its associated architecture continue to evolve. In 2008, the book on the latest evolution of data warehousing appeared – DW 2.0: The Architecture for the Next Generation of Data Warehousing (Morgan Kaufman). In that book the general architecture for data warehousing in its highest evolved form appeared.

What a Data Warehouse is Not

Recently, I was at a conference, and I heard the following discussion about what a data warehouse was. One person suggested that a data warehouse was really all the old legacy systems connected by software that could access the data. By calling such a contraption a data warehouse, the organization could avoid having to do the hard and complex work of integration. There are so many problems with this federated approach to a data warehouse that they are almost not worth repeating here. But (once again!) here goes.

Kimball University: Six Key Decisions for ETL Architectures

Best-practice advice on software vs. coding, where to integrate, how to capture changed data, when to stage data, where to correct data and what latency levels to shoot for.

Energy Intelligence

Given that companies spend on average between 7 and 12 percent of their annual budgets on energy – a focus on reducing energy consumption can have significant bottom-line impact

How to Calculate Data Warehouse Reliability

This article outlines a more objective and analytical approach to the ETL and data flow architecture selection based on a set of variables with an objective to enhance the reliability of the overall data warehousing solution.