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July 25, 2018 6:35 pm Published by
  • Identify data quality issues at source
  • Validate and assure data consistently
  • Improve the transparency and standardization of data quality routines

  • Reuse rules and algorithms during design and build of new data pipelines
  • Reduce Reduce the cost of change and maintenance across multiple data flows.

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