Pitney Bowes (NYSE:PBI) is a global shipping and mailing company that provides technology, logistics, and financial services to more than 90 percent of the Fortune 500. Small business, retail, enterprise, and government clients around the world rely on Pitney Bowes to remove the complexity of sending mail and parcels.
Too much time manually cataloging data assets
As part of the Data Management team, Vishal Shah, Solutions Integration and Deployment Architect, is tasked with supporting Pitney Bowes’ end users, including developers, data scientists, and other internal data consumers looking for pieces of data.
But before Select Star, it wasn’t easy. Pitney Bowes’ data was organized in a Data Mesh pattern—multiple teams producing and also consuming data independently. Manually untangling ETL queries to understand how different data assets were connected was time-consuming and overwhelming for Vishal and his team.
The data management team needed a more efficient way to query datasets and find answers to data questions. Pitney Bowes’ end users frequently need these insights to inform strategic decisions. Inaccurate or mismanaged data results in costly delays.With so much at stake, Pitney Bowes needed a better way to organize, discover, and govern data.
I’m saving at least 30 hours a month easily just by automating schema changes. If I factor in the time to get new assets added to the catalog, we’re talking about additional days of time savings.
Solutions Integration & Deployment Architect, Pitney Bowes
Select Star for data discovery and governance
Select Star, an intelligent data discovery platform, solves Pitney Bowes’ biggest challenges and helps their data management team organize and understand data. Delivered on AWS Cloud, Pitney Bowes uses Select Star to:
Organize and govern data
Customizable tagging and dynamic metadata help users quickly find the exact information they need to complete tasks and even create repeatable procedures for querying data sets
Understand the impact of column changes
The data lineage view lets users see how changes in one table will affect others. This allows Vishal’s team to trace errors upstream dependencies and identify all of the assets downstream that might be affected
Capture tribal knowledge
By automatically detecting and displaying how a data set is being used inside the company, Pitney Bowes’ developers know at a glance which field they should use for each specific use case.
Ensure data security
Select Star is AICPA SOC 2-compliant, providing peace of mind to Pitney Bowes’ data management team.
I'm saving at least 30 hours a month just by automating schema changes via Select Star. If I factor in the time to add new assets to the catalog, we're talking about additional days of time savings.
Eliminate manual processes
One-click integrations with Snowflake, Tableau, and Azure AD SSO helped end onerous manual processes of metadata ingestion and reduce the risk of human error
Search for, find, and understand data
An intuitive user interface makes it easy for end users to glean the insights they need.After only one month with Select Star, Vishal’s team was able to accomplish what they couldn’t do in a year with IBM Watson Data Catalog—they had configured a functional, powerful, and highly efficient data catalog for everyone at Pitney Bowes.
Data management team saves 30+ hours/month
Pitney Bowes’ developers can now easily search for the data they need without relying on manually looking into complex SQL queries. With Select Star’s powerful automation, it’s much faster for Pitney Bowes’ teams to find answers to their data questions.
The data management team now spends a substantially reduced amount of time on data troubleshooting. Vishal estimates that his team saves more than 30 hours each month thanks to the self-service platform. He also says that Select Star has helped improve his team’s asset cataloging efficiency by upwards of 67%.
Already, more than 12 teams at Pitney Bowes use Select Star on a daily basis. He’s currently rolling out the solution company-wide.