Estimating Extract, Transform, and Load (ETL) Projects
In the consulting world, project estimation is a critical component required for the delivery of a successful project. If you estimate correctly, you will deliver a project on time and within budget; get it wrong and you could end up over budget, with an unhappy client and a burned out team. Project estimation for business intelligence and data integration projects is especially difficult, given the number of stakeholders involved across the organization as well as the unknowns of data complexity and quality. Add to this mix a firm fixed price RFP (request for proposal) response for a client your organization has not done work for, and you have the perfect climate for a poor estimate. In this article, I share my thoughts about the best way to approach a project estimate for an extract, transform, and load (ETL) project.
For those of you not familiar with ETL, it is a common technique used in data warehousing to move data from one database (the source) to another (the target). In order to accomplish this data movement, the data first must be extracted out of the source system—the “E.” Once the data extract is complete, data transformation may need to occur. For example, it may be necessary to transform a state name to a two-digit state code (Virginia to VA)—the “T.” After the data have been extracted from the source and transformed to
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