Q:

I am providing information for a proof of concept (my first time) on an ETL tool for a major data conversion project. Could you tell me the most important issues I should be exploring within the proof of concept?

A:

Sid Adelman’s Answer: There are three major points to consider for an ETL tool. The first is how effective and productive the tool is (for your people) in their ability to extract, transform, cleanse (don’t forget that your data is pretty dirty) and load. Their acceptance and comfort with the tool are critical for its eventual use. The second is the performance of the ETL tool with your hardware, operating system and RDBMS. This is especially important if you have a large database to load. The final point is the capability and usefulness of their meta data function and how well it works with the meta data of the other products you will be using such as your modeling tool and access and analysis tool.

Mike Jennings’ Answer: Some of the more important issues to consider in your proof of concept are: Does the ETL product

  • Facilitate greater productivity, expedient data movement and improved quality of the data;
  • Significantly reduce the cost of ETL processing (savings from reduced system utilization plus development and testing costs);
  • Significantly reduce the data errors;
  • Reduce the training time and shorten the learning curve to allow broader usage by non-technical employees;
  • Enable standardization and definition of all data;
  • Have the ability to create documentation;
  • Provide productivity gains from maintaining code-centric extraction processes.
  • Take advantage of a meta data-centric repository both for ETL and integration with our products (e.g., data modeling, data quality, data profiling, reporting)?

Clay Rehm’s Answer: Yes – there are many for an ETL tool, especially performance.

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