Data Quality (DQ)

The Client


The Challenge

The client was experiencing an increased number of data quality (DQ) incidents as a result of business growth and complexity. These incidents were driven by:

  • Lack of processes around sourcing data
  • Inconsistent data definitions
  • Sourcing similar data residing in multiple places
  • Insufficient records on past DQ incidents

The Solution

Cognilytics partnered with the client to deliver a comprehensive solution that solved the current data quality challenges. The solution included:

  • Implementing governance and DQ into SLAs
  • Establishing communication and escalation policies
  • Adopting best practices for managing data quality
  • A data quality reporting and monitoring tool to profile key data elements and issue alerts for suspected violations
  • Implementing traceability for all data elements


  • New products/services can now be brought to market as a result of improved data quality
  • Staff support time costs reduced
  • Speed to Market minimizing developer distraction
  • Business Overhead Savings through client support
  • Process CPU Costs save by system utilization reduction
  • Brand Protection, minimizing customer impact
  • Ensuring credibility of the data in information products
  • Improve decision making transparency/confidence