Because you can’t act on data you can’t see…



As data continues to grow in volume, variety and velocity, organizations may have hundreds or thousands of data repositories, from file servers and databases to data warehouses and data lakes, both on-prem and cloud-based. They share data among employees and partners. A single individual’s data may be in multiple repositories. Finding sensitive data accurately, quickly and completely is more difficult than one might think.

100% of organizations that use Dataguise discover sensitive data they did not know existed in their data repositories. Some find entire data repositories. When compared to other solutions, Dataguise has been around longer, supports a broader range of data types and repositories, delivers lower false-positive results, and more reliably scans data at scale. Dataguise gives organizations the confidence to act on data in the best interests of the business and the people who trust them with their data.

Data privacy continues to grow as a concern for both individuals and organizations. Over the years, various governmental regulations and industry standards have been created to address specific types of sensitive data—such as the Payment Card Industry Data Security Standard (PCI DSS) or the Health Insurance Portability and Accountability Act (HIPAA). In the US alone there are hundreds of state and federal laws regarding digital commerce or communication that may apply to an enterprise, but there is no single overarching, cohesive law like the European Union’s General Data Protection Regulation (GDPR)—at least, not yet.

Regulatory compliance is one of the top use cases for a data discovery tool. Organizations are being called out every day in the news for their mishandling of sensitive data, and they are paying for it, in terms of brand reputation, customer relationships, and profitability.


Security and risk pros can’t expect to adequately protect customer, employee, and sensitive corporate data and IP if they don’t know what data exists, where it resides, how valuable it is to the firm, and who can use it. – Forrester ResearchRethinking Data Discovery and Classification Strategies July 10, 2018

Until now, consumers have been willing to lend their data (or have unknowingly given it away) to get convenience or information in return. Once they fully realize the consequences of this bargain they will be looking to government and business to safeguard data and hand control back to them, the customer. – ForbesData Privacy Will Be The Most Important Issue In The Next Decade, November 26, 2019


  • Handles high volumes of disparate, constantly moving, and changing data with time stamping to support incremental change and life cycle management.
  • Supports a fluid or flexible information governance model that has a mix of highly “invested” (curated) data as well as raw, unexplored (gray) data such as IoT (Internet of Things) data, clickstreams, feeds, and logs.
  • Handles a variety of data stores such as traditional relational databases and enterprise data warehouses as well as non-relational big data sources (Hadoop) and file repositories (SharePoint and file shares).
  • Processes structured, semi-structured, and unstructured or free-form data formats.
  • Provides automated detection and processing of a variety of file formats and file/directory structures, leveraging meta-data and schema-on-read where applicable.
  • Provides deep content inspection using techniques such as patent-pending neural-like network (NLN) technology, and dictionary-based and weighted keyword matches to detect sensitive data more accurately.