Fannie Mae is a $110 billion company and leading source of financing for mortgage lenders. As a data-centric business with high-velocity apps generating more than 10 million new files each day, the company needed to transition to a more agile and responsive data lake – creating a modern and efficient data environment that delivered the right data to the right person at the right time.

Infrastructure Transformation Accelerates Insights

As part of its move to a modern data infrastructure, Fannie Mae integrated Lumada Data Catalog for its extensive APIs and ability to support high-volume applications generating millions of files a day. Custom search properties deliver desired data quickly and efficiently, and metadata versioning allows for the capture and display of technical metadata provided by the ingesting application.  

Lumada Enables Better Business Outcomes

With Lumada Data Catalog, Fannie Mae can accelerate data discovery and tagging, secure sensitive information, infer hidden relationships, and accelerate data democratization. The company now provides a self-service data-catalog marketplace for business users, and with the automatic processing of the datasets, millions of files are being cataloged each day delivering smarter insights.

“With Waterline, we were able to fully automate and accelerate the cataloging and searchability of data to deliver game changing value to the business,” says Prakash Jagananthan, Data Management Leader at Fannie Mae.

Read the Fannie Mae case study.

Image Credit: Hitachi Vantara / Getty Images