Data Processing


  • Synthesis and Preparation:
    • Merge data sets from multiple data sources.
    • Clean and repair messy data sets.
  • Data Transformation:
    • Design and implement summary calculations and complex algorithms.

What is Data Processing?

If you could use all the data you collect in its raw form (the form in which you got it), then data processing would be unnecessary. However, very often something needs to be done to the data before you can start to use it. Depending on the state of affairs, your data may need to be:

  • Restructured to be made usable by other systems or analytical tools.
  • Made internally consistent (within and between fields).
  • Made consistent with established business rules.
  • Combined with other data sets.
  • Transformed from one data set into another.