DISCOVERY & CLASSIFICATION

Discover and Classify Sensitive Data

Privacera uses AI-driven data discovery to identify, classify and build a catalog of sensitive data to provide a comprehensive view across heterogeneous cloud and on-premises services.

Understand Your Data at a Glance

You can’t govern or secure data that you don’t know exists. That’s why it is critical to identify and classify sensitive data as it is ingested, before it is accessed by users. With a comprehensive view of sensitive data, you are empowered to make the right decisions about who should and shouldn’t have access to it.

Discover and Classify Sensitive Data

Traditional discovery tools rely only on metadata to discover sensitive data which results in high rates of false positives.

Discover

Privacera differs from traditional data scanning tools by incorporating rules, machine learning and natural language processing to understand the context and accurately classify your sensitive data.

How Discovery and Classification Works?

Connect to Your Cloud and On-Premises Storage and Databases

Automatically connect to cloud and on-premises storage services and databases such as Amazon S3 and Azure Storage.

Apply Machine Learning Models and Rules

Privacera uses machine learning models and rules to scan, identify and tag sensitive data in real-time as it is uploaded to the cloud or object storage.

Create Automated Workflows and Reviews

Create automated workflows for sensitive data based on predefined policies or surface sensitive data for manual review if desired.

Create a Sensitive Data Catalog

Create a catalog of data classifications in a scalable metadata store for a comprehensive view.

Generate Reports and Alerts

Generate reports to give compliance and governance teams instant visibility and get alerts if sensitive data is moved.

Frequently Asked Questions

What type of files does Privacera work with?

Privacera works with over 50 file types, including structured types (Apache Avro, Apache Parquet, CSV), semi-structured types (JSON, XML), and unstructured types (documents, PDF).

How do you reduce false positives?

Privacera enables you to configure confidence levels for discovery and classification. Depending on confidence level, certain discovery results are surfaced for manual review. A data steward or a data owner can accept or reject the classification results. The Privacera classification engine learns from manual reviews and reduces the rates of false positives over time.

How do you support custom data types?

Governance and compliance teams can easily build custom rules or machine learning models for custom data types.

Do you take actions based on discovery results?

Privacera can help quarantine data or anonymize sensitive data if sensitive data is discovered in a specific system. Users can also create automated workflows for sensitive data based on predefined policies.

Resources & Latest News

Whitepaper

Security and Privacy for Modern Data Platforms

Learn how to enable comprehensive security, privacy and governance in big data and cloud environments using Privacera.

DOWNLOAD

Privacera for Amazon EMR

Use this link to request a Docker package to install fine-grained access control to Amazon EMR.

Datasheet

Discovery and Classification

You can’t govern or secure data that you don’t know exists. That’s why it is critical to identify and classify sensitive data as it is ingested, before it is accessed by users. Privacera incorporates rules, machine learning and natural language processing to understand the context and accurately classify your sensitive data.

See Discovery & Classification in Action