One of the biggest challenges in regulated industries – from finance to healthcare and beyond – is finding and protecting variations of highly sensitive, restricted, and uniquely identifiable data across the entire organization. Those data types might follow specific patterns like a social security number, or could vary formats and values, like a customer ID or unique account IDs.
Traditionally, organizations rely on Regular Expressions (RegEx) to identify that data, manually verify it, and manually apply protection around it – from encryption to deletion to quarantine. These traditional data classification approaches can be noisy and challenging:
- It’s difficult to accurately identify common types of sensitive data like customer IDs or credentials
- There are a lot of false positives and a high volume of misclassified data that requires manual intervention
- These approaches tend to be siloed (and limited) by specific data sources
- It’s difficult to scale – especially across unstructured data, data warehouses, and data lakes
BigID was built to address those challenges – leveraging patented machine learning techniques that incorporate graph technology to identify more types of sensitive data in more places, more accurately.
BigID layers traditional data discovery and classification techniques like RegEx with correlation-based graph technology, NLP, and ML to more accurately identify data like customer IDs, healthcare identifiers, patient records, financial records, credentials, user data – and all types of high risk data that an organization collects.
Single Pane of Glass
By enabling a single pane of glass to easily inventory and map all data in one place, customers get one consistent UI to manage, analyze, and protect their data. They can use intelligent automation to improve accuracy, reduce manual tasks, and gain consistency across datasets, activity, and analysis.
Scanning at Scale
A modern microservices architecture means that customers can scale – across high volumes of data and disparate data types. Customers with thousands of data sources, petabytes of data, and billions of customer identities can use BigID to get to value faster, reduce scanning time, and automate time consuming (and error prone) manual processes.
It’s not enough to be able to identify data – organizations need to be able to answer the question “now what?” They need to take action on that data: make sure the right people have the ability to remediate the data in the right way: from masking to deletion to encryption to minimization. Not all data requires the same treatment – and with BigID, customers can use multiple remediation options with dynamic ownership. That means the right people are making the right decisions on the most high risk and valuable data.
In highly regulated environments, protecting data like unique identifiers is critical to achieve compliance, reduce risk, and avoid costly fines. Find out how BigID can help organizations proactively manage, protect, and remediate their restricted data – at scale, and across all types of data.