Agents
CASE STUDIES
Nationwide Automates Enterprise Data Quality at Scale with Anomalo
What were the key results of Nationwide's data quality automation with Anomalo?
3,000+
Anomalo has found more data quality problems with its out-of-the-box, turnkey solution than Nationwide’s 3,000 rules.
100
of 5,000 databases fall into the top tier. Out-of-box data observability can be applied to all databases and then leverage deep data quality monitoring across the most important data assets.
About Nationwide
Over the past 90 years, focusing on customers and valuing people have helped Nationwide become one of the largest insurance and financial services companies in the world.
Tech Stack
Data Warehouse: 
Data Catalog: 
Size
10,000+ Employees
Industry
Insurance
The Challenge
Complex Data Assembly Lines, Brittle Manual Rules
Nationwide handles critical financial data at a enterprise scale. Their data estate clocks in at over 13,000 databases across the enterprise, about 5,000 in production. Data at Nationwide flows through many complex transformations before being used for analytics and compliance. “You can think of it as the assembly line for a car,” said Mike Randall, Director of Enterprise Data Governance at Nationwide.
Mike has been working in data quality at Nationwide for over 30 years. “I started out looking at BIN numbers to make sure they were keyed in correctly. I had a terminal in front of me, I had policies in front of me, I had books.” Before Anomalo, Nationwide’s marketing team alone had 3,000+ custom business rules to maintain. The result was that data quality was mostly “reactive,” Mike said. Issues might not be detected until the final output went to a report or regulator.
The Solution
Anomalo’s AI-Powered Monitoring + Databricks and Alation Integrations
The enterprise data office evaluated several different solutions for data quality, but what stood out was Anomalo’s AI-powered monitoring. It learns which data changes represent normal fluctuations, and which are true deviations worth investigating. “I put my name behind the Anomalo selection because Anomalo was the one bringing statistical analysis to the field,” Mike said.
Crucially, Anomalo also had deep partnerships and integrations with Databricks, Databricks Unity Catalog, and Alation, all key parts of Nationwide’s infrastructure.
The Results
How did Anomalo impact data governance at Nationwide?
“When we first brought Anomalo in, we put it on our most important analytics databases, and within that the most important table,” Mike said. “We had a really quick standup —within months we were up and running. It was probably the fastest I’ve ever seen anything at Nationwide move, in my 31 years.”
Since implementing Anomalo, Nationwide has been able to find and stop issues at the source, before they affect downstream reports and analytics. “We have some really good examples where Anomalo has detected a problem, it saved us from sending a bad report to regulators because of some business data, and we’ve been able to kick jobs off to fix the problem,” Mike said. Now that the right tools are in place, it’s much easier for everyone to work together and implement best practices.
Unlock the full case study to see how Anomalo found more data quality problems with its turnkey solution than Nationwide’s 3,000+ rules
What is Nationwide's policy for data quality and asset cataloging with Anomalo and Alation?
Nationwide's Data Risk community has created a policy stating that for their most important assets, they must be cataloged in Alation and have data quality managed with Anomalo. This standard and policy was a significant achievement for data governance at Nationwide, as expressed by Mike Randall, Director of Enterprise Data Governance.
Frequently Asked Questions
- 1 What was Nationwide's primary challenge with data quality before Anomalo?
-
Based on the meta description, Nationwide relied on 3,000 rules to manage data quality, but Anomalo's solution was able to identify even more data quality problems, suggesting limitations with their previous rule-based approach.
- 2 How does Anomalo's solution compare to traditional rule-based data quality systems?
-
Anomalo offers an out-of-the-box, turnkey solution that autonomously finds more data quality problems than extensive manual rule sets, as evidenced by its performance against Nationwide's 3,000 rules.
- 3 How does Anomalo enable automated enterprise data quality at scale?
-
Anomalo provides an autonomous data management system designed to automate data quality processes across large enterprises. This allows organizations like Nationwide to efficiently detect and manage data quality issues at scale.