seven steps of data quality graphic

Make the case for a predictive and self-service data quality tool

New white paper from First San Francisco Partners and Collibra


Create an enterprise vision for data quality

No matter what industry you work in or what role you have, you know that being able to rely on the accuracy of your business’ data — and its availability — is essential.

High-quality data adds value to your organization, benefiting your operational and analytics activities and how you sell products and services to customers.

Our “Make the case” white paper, written by Sarah Rasmussen, FSFP’s Collibra Practice Lead and Engagement Manager, emphasizes the benefits of having a dedicated data quality area and its role in defining data standards and practices.

Sarah outlines seven activities that are needed to ensure data is assessed, monitored and measured against expectations for use and how a self-service, enterprise data quality tool, such as Collibra Data Quality & Observability, simplifies these activities:

  • Data profiling
  • Data quality assessment
  • Data cleansing and standardization
  • Data quality monitoring
  • Data issue management
  • Data issue remediation
  • Data quality performance and impact reporting

data quality white paper

Explore the seven activities that ensure high-quality data

Get the new white paper from First San Francisco Partners and Collibra to make the case for a robust data quality function in your organization.


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