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Data Strategy and Implementation for a Washington DC-based Psychological Organization

DATAECONOMY derived a data strategy for developing a Target state platform that can provide a self-service framework for Business stakeholders. DE worked with multiple stakeholders from Business and IT to derive a comprehensive data strategy, including developing an AI and Machine learning framework for future hypothesis building.

The business had issues with the longer time taken for getting data and quality of data

  • No self-service, it takes longer to get the data needed for analysis, Poor quality of data
  • Different stakeholders have different definitions & numbers for Critical data elements
  • Member and Non-Member data is separate while both of them have many correlations
  • Data is a week old, No Data Visualization Capabilities

DATAECONOMY developed a comprehensive self-service framework with the right Data Governance Solution. We developed an AI / ML Framework for Hypothesis building across the membership and non-membership data to provide capabilities on content recommendations to the members.

Data discovery and collection time were reduced by 40%. The overall cost of ownership was reduced by 50%.