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  • Deploying an alternative data processing platform that is flexible, cost efficient, and scalable
  • Demonstrating that this platform can provide the foundation for proper transparency, governance, and quality management activities
  • Demonstrating that data can be integrated, properly governed, and published faster than in the current environment


  • Finalizing the architecture, and if necessary facilitating the selection of technologies to cover any remaining gaps
  • Selecting an initial source dataset and building a standard ingestion process into the platform (e.g. via daily batch load)
  • Building processes to profile the data as well as identifying and reporting on quality and route issues
  • Building processes to apply transformation business rules and conform to common entities
  • Providing proper lineage and transparency into any data changes, once data is ingested into the platform
  • Exposing ingested data to a data access layer (e.g. SQL or API) within a daily SLA
  • Transitioning the code/processes to the client

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