The Importance of Data Discovery and Classification
Ensuring security of data and compliance with privacy regulations requires understanding what sensitive and regulated data exists and where it resides. Further, the data discovery process must be performed regularly to guarantee accurate scope of data security and privacy compliance efforts. The Covata Data Discovery solution delivers results faster and easier than any other data discovery tools in the market. Also, the Covata Data Discovery tool is purpose-built to search unstructured data repositories that are typically ignored by tools that only search databases.
Manual approaches to data classification are inaccurate and inefficient. Organizations need the ability to access accurate and scalable classification tools which will enable them to integrate disparate silos of information and improve the management, security and compliance of data.
The importance of data classification
How Does Covata Discovery and Classification Work?
Covata Data Discovery installs quickly and is pre-configured to find credit card numbers, patient information, and personally identifiable information (PII) used in several countries. Users can also create custom sensitive data types, a feature useful for locating intellectual property and other sensitive data types specific to your business. A single installation of the Covata Data Discovery solution is able to search for information in local and remote file shares, Microsoft SharePoint, and Office 365 without any additional software. Covata Data Discovery uses keywords, regular expressions (patterns), and post-processing (for example, the Luhn Algorithm) to identify sensitive and regulated information.
Covata Classify is an enterprise data classification solution that automatically classifies and categorizes unstructured data across data centres and clouds. Our solution employs multiple techniques to accurately classify information without compromising system performance or user productivity.
- rules-based analysis of metadata can be used to categorize information based on attributes like file type, location, and file owner
- pattern matching is used to find recognizable data such as credit card numbers, medical record numbers, and personally identifiable information
- machine learning (artificial intelligence) for information that is not easily identified using patterns or attributes
Covata Classify can analyse information on a schedule or in-line. It can also be used to automate governance requirements associated with archival and eDiscovery, and enable cloud migrations.