Learn more about how Ab Initio can help your organization automate its data and governance systems:
Highlights
Automated Data Discovery
Discover the meaning of your data with Ab Initio’s advanced data discovery capabilities.
Ab Initio’s semantic discovery uses advanced algorithms and machine learning to scan your data and automatically create an inventory of its content. This discovered information helps you understand the characteristics of the data and its relationships to other data in the company. Relationship types include a foreign key relationship, a calculation relationship, and relationships to important business concepts such as credit card number, customer name, and country identifier. These automated capabilities can reduce project time by up to 90%, reducing a years-long effort for a large data cataloging project to mere weeks.
Because all Ab Initio products are built on the same fundamental technology and are tightly integrated, our semantic discovery capabilities drive automation across multiple products and use cases. For example, semantic discovery enables the autogeneration of data quality rules, provides a foundation for protecting personal data, enables self-service data ingestion, and much more.
Case Studies
Enterprise Data Quality Management
Sometimes, it’s not enough to just control the data!
For one large US financial institution, unmanageable data was a problem. Their data management was scattered across the enterprise, and different parts of the bank used different systems.
Many of these systems were homegrown using open source and various data management products. One area had a completely separate IT system. With no standard system or method of managing data quality, the company couldn’t trust the results and they couldn’t answer questions from regulators. That made the regulators unhappy, and when regulators are unhappy, no one is happy.
Working with Ab Initio, the financial institution began standardizing their operations and eliminating all point-to-point interfaces and legacy datastores. They built a data lake using Ab Initio’s data governance, data quality, and data lineage capabilities to govern the data and track data quality. Ab Initio’s intuitive, spreadsheet-like interface for rule development greatly simplified the process of developing data quality rules and putting them into production.
Becoming skilled at finding bugs in data leads to a new set of challenges. Financial institutions have a lot of data. Even if only a small percentage of that data has issues, that’s still a lot of issues. It doesn’t take much before the people who fix those issues are overwhelmed with the number of bugs that need attention.
Once again Ab Initio was able to help. With Ab Initio, the financial institution built a complete data quality management solution. More than simply executing data quality rules, the new system let the company manage the entire process of identifying, tracking, and fixing problems with their data and data quality rules without overwhelming anyone with lots of defects.
When a record fails a data validation rule, the system checks to see if there is already an open ticket for that specific failure. If there is, the record is added to the existing ticket. If no ticket exists, a new one is created. That ticket will end up being composed of all the records that fail a specific validation test. Ab Initio assigns that ticket to the appropriate person based on stored reference data, who then drills down into the attached records and determines whether there is a data problem or a rule error.
If the problem is with the data quality rule, the ticket is reassigned. If the problem is with the data, the data owner is responsible for fixing it and is immediately notified. Fixes need to be logged and verified. In the days before the financial institution adopted Ab Initio, assigning responsibility at such a granular level would have been impossible. It was impossible no longer.
With their new system in place, the financial institution can track down data quality issues, fix them, and then verify the fix, all without overwhelming the people responsible. Data issues are routed to data owners, and rule errors are routed to the appropriate business experts who test and debug the rules. This is data quality management at the enterprise level, powered by Ab Initio.