Effective data extract, transform and load (ETL) processes represent the number one success factor for your data warehouse project and can absorb up to 70 percent of the time spent on a typical warehousing project. ETL tools promise quick results, improved manageability and meta data integration with other common design and implementation tools. However, due to the potentially huge amounts of money involved in a tool decision, choosing the correct ETL tool for your project can present a daunting challenge. With a bit of internal questioning in advance followed by a careful review of your key needs against the choices available on the market, you should be able to choose the most effective ETL tool for your project.
ETL tools perform, as you may guess, at least three specific functions all of which focus around the movement of data from one place (file type, server, location, etc.) or system to another. More encompassing than a simple file copy process, this class of software generally reads data from an input source (flat file, relational table, message queue, etc.); passes the stream of information through either an engine- or code-based process to modify, enhance, or eliminate data elements based on the instructions of the job; and then writes the resultant data set back out to a flat file, relational table, etc. As you may have guessed, these three steps are known as extraction, transformation and loading, respectively.
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