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August 14th, 2013

After discussing Data Extraction and Design we now move onto the third piece of the puzzle - Data Transformation, also known as Cleansing. In this phase, the data that was extracted from its original source, is analyzed and “cleansed” for accurate loading into the new destination. Data is checked for integrity and any necessary business rules are applied as the data is processed. Data Quality plays a huge part in this phase. There are six parts to Data Quality:

  • Completeness – ensuring all data fields are populated that need to be
  • Conformity – checking that the data is in the standard format
  • Consistency – all data is consistent and non-conflicting
  • Accuracy – all data is correct
  • Duplication – data is in the same format
  • Integrity – data retains relationship link information

Other areas to look for when performing a Data Quality check:

  • Duplicate records
  • Irregularities and discrepancies
  • Integrity constraint errors
  • Missing or invalid data
  • Obsolete information

Data Transformation is made up of two elements, data mapping and code generation. First, the data is mapped from the source to the destination, which determines any transformation of data which must be done. The code generation piece is an executable piece of software that is run and performs the actual transformation. The timespan for this phase varies with the size and complexity of your data. Once your data is through the Transformation phase, it’s ready for the Load phase.



Wikipedia - The Free Encyclopedia, "Extract, transform, load." Accessed July 8, 2013. http://en.wikipedia.org/wiki/Extract,_transform,_load.

Wikipedia - The Free Encyclopedia, "Data Transformation." Accessed July 8, 2013. http://en.wikipedia.org/wiki/Data_transformation.

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