Case Study: Principal Financial Group reduces compute costs by more than 70% with Matillion

Principal Financial Group - Customer Case Study

Principal Financial Group used Matillion ETL to address the time and resources needed to process thousands of financial documents each day. The company needed to search through large volumes of text for specific words and phrases to produce accurate performance scores for clients.

With Matillion ETL, Principal Financial Group built a natural language engine that processes unstructured data from multiple sources in parallel. Matillion’s dynamic querying capabilities, combined with Snowflake’s regular expression engine, helped reduce compute costs by more than 70%, and the company can now search about 500 billion sentences for more than 400 complex phrases in under 6 hours.

Principal Financial Group

Brody Vogel

Data & Operations Research Scientist