Case Study: Pitney Bowes achieves 30+ hours/month savings and 67% more efficient data cataloging with Select Star

How Pitney Bowes Saves 30+ Hours/Month with Select Star’s Automated Data Cataloging

Pitney Bowes, a global shipping and mailing company, faced slow, manual data cataloging and discovery across a Data Mesh where multiple teams produced and consumed data independently. The Data Management team struggled to untangle ETL queries and find reliable datasets quickly, creating delays and risk to decision-making—so they engaged Select Star’s intelligent data discovery and governance platform.

Select Star automated metadata ingestion, lineage, tagging, and integrations (Snowflake, Tableau, Azure AD SSO) so teams can search, understand, and govern data quickly. As a result, Pitney Bowes’ data management team saves more than 30 hours per month, achieved roughly 67% greater asset cataloging efficiency, and now has 12+ teams using Select Star daily while rolling the solution company-wide.

Pitney Bowes

Vishal Shah

Solutions Integration & Deployment Architect