Populating the end-result data model as early as possible.Better Extract/Transform/Load (ETL) Practices in Data Warehousing (Part 2 of 2).Many ETL processes have a series of common patterns/activities, whether the end-game is a full-blown data warehouse or some type of operational transaction system or data store. If your job includes retrieving (extracting) data from one location, manipulating/validating (transforming) that data in the middle, and then saving (loading) that data somewhere else, you might find value from some of these tips.
“But what if I don't work in Data Warehousing?”Įven if you don't build full-blown data warehouses, you might still benefit from this article. The second part will apply these tips to a specific data warehouse project using the newest features in SQL Server, and will focus on applying those methods using Microsoft technologies. This first part presents 13 general tips that focus on practice and methodology, although I'll go into a certain level of detail when necessary. Because this general topic is so deep, I'm writing it as a two-part article.
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Because of this, CODE Magazine asked me to write an article on the subject, so, in my traditional Baker's Dozen format, I'll present thirteen tips that you can incorporate into your data warehouse ETL projects. I've worked on many data warehouse initiatives, led several data warehouse projects, and also taught and mentored on the subject.
I've studied the large volumes of material on data warehouse ETL practices and have collected many useful thoughts along the way. When you combine that statistic with the palpable and sobering objective of a data warehouse as the “single version of trust,” good processes are essential. In the world of data warehousing, many industry journals report that Extract/Transform/Load (ETL) development activities account for a large majority (as much as 75%) of total data warehouse work. Those with experience will recommend these as practices, with the idea that following these practices leads to better, cleaner, and more productive outcomes.
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Nearly every professional endeavor contains processes and methods associated with carrying out tasks in that discipline.
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