Avoid Common Pitfalls in Data Quality Programs

Jeremy Skaling, Head of Product Management


Recently I participated on a panel at an industry event where the group was asked to comment on common pitfalls with data management projects. I identified three key challenges that firms face:

  • • Not having proper data governance plans and organizational support
  • • Implementing data checks at the wrong location and/or having the wrong people reviewing them
  • • Not tailoring data quality checks to a company’s business or the needs of the consumers

These are pitfalls that we observe often, which can be efficiently solved with the right solutions and resources in place. Products designed to address data governance are evolving with enhanced usability, workflow and the ability to segregate responsibilities across departments or groups within a department. At Eagle, we are elevating data governance with enhanced metadata tools and business intelligence capabilities. These capabilities will provide robust dashboards to report on data quality, including heat maps to hone in on data validations.

During the panel, I also shared an example of a large insurance client that is using Eagle to support their enterprise data management initiatives. Relevant to the discussion was our conversation about their evolving data management and technology needs. As we were discussing their use of Eagle to support data management, their senior architect mapped out their technology platforms that support business applications and business services on a white board. Next to this diagram, he wrote the acronym ETL for “Extract, Transform, Load” but crossed out the ‘T.’ His vision is that technology should handle the functions of extracting and loading data but that the business owns the translations, enrichments and quality checks.

This viewpoint rings true to us at Eagle and we understand the importance that technology plays in helping businesses ‘Transform’ their data. A main concern of ours is delivering consistent and accurate data fed from a variety of sources. Whether a client needs centralized data to support business processes such as client reporting, AUM rollup or performance measurement or if they need a hub to pass data on to appropriate departments or business functions, we are committed to enabling accurate data flow. Part of this data flow is the importance of defining when and where to enrich data and when and how to invoke the appropriate business rules. Providing the business rules to the users responsible for supporting business applications and business services will empower them to meet the ever-changing demands of the business.

 

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