Data Privacy –

GDPR Compliance

Discover, understand
and catalog your
sensitive data

The pressure is on to analyze every bit of your corporate data, while regulatory responsibility to protect it has never been higher.

Today’s enterprise must collect every piece of data imaginable, make it easily available across the organization via self-service analytics, foster a data-driven culture, and support digital transformation. At the same time, however, every piece of additional data enterprises collect increases their regulatory
burden – and the risk they will run afoul of the regulators.

Governments around the world, at state, national and international levels, are establishing stringent standards for data protection, privacy controls, and rigorous, precise data management.

The European Union’s General Data Protection Regulation (GDPR), its ePrivacy Regulation (ePR), and the California Consumer Privacy Act of 2018 (CCPA), with their formidable requirements, are the most notable and recent examples, that signal what will come.

“According to Forrester, manual discovery is a time-consuming and often error-prone process. Data discovery and inventory tools are distinct from, but related to, data classifiers. These tools help enterprises identify the locations of sensitive structured and unstructured data.” 1

How can organizations effectively leverage data as a critical enterprise asset, while establishing governance controls to minimize the risk and penalties for non-compliance?

Precise data management has always been difficult. In today’s environment, where data sets are rapidly multiplying, and growing in size, governing that data manually is slow and unsustainable, if not outright impossible. Put simply, manual discovery and cataloging of sensitive data is not an option!

The data-driven enterprise must instead manage data proactively, protect sensitive information, remove redundant data and ensure the accuracy and quality of every data element. Discovering where all data resides is key for future organizational compliance and success.

What makes Io-Tahoe different?

Io-Tahoe is an enterprise smart data discovery and AI-driven catalog product. Io-Tahoe provides the only solution that leverages AI to look at the data themselves to automatically discover sensitive data, including, but not limited to PII. It uses artificial intelligence to scale your efforts and reduce your growing data governance burdens to a set of manageable, navigable tasks.

Io-Tahoe can help your organization

  • Govern data from almost any enterprise relational database system, automatically discovering hidden or unknown relationships from database schema and constraints, using Io-Tahoe’s smart data discovery.
  • Get your data catalog fully built, and fast, with multi-faceted AI. Stay up-to-date with versatile Impact Analysis.
  • Catalog and govern data in any data lake, whether it be in Hadoop, Spark or cloud storage, in neat Hive tables, or in unwieldy flat files, using formats ranging from delimited text to Apache Parquet.
  • Get on the road to compliance immediately, using out-of-the-box sensitive data policies. Quickly add your own policies to cover all sensitive data in the context of your industry and business.

Io-Tahoe’s smart data discovery and AI-driven catalog enable end-to-end data management and governance with a full suite of data management capabilities including relationship discovery, redundant data discovery, sensitive data discovery and impact analysis.

Io-Tahoe discovers the relationships in your data – not just the ones documented in your metadata but ones it detects intelligently by analyzing the data themselves. Working within databases and between data sources, our automated discovery helps build out your data catalog, and identify vast amounts of sensitive data – much of which would otherwise go undetected, potentially leaving your organization exposed to significant risk.

Forrester recommend data discovery and classification as the first phase of their Data Security and Control Framework, one area of which is defining the data. This is a critical step; “if you don’t know what you have, where it is, and why you have it, you can’t expect to apply the appropriate policies and controls to protect it.” 1

“According to Forrester, nearly 30% of companies globally are fully GDPR-compliant today. However, based on[their] qualitative research, [Forrester]believe[s] that just a portion of these firms have actually engaged in data discovery and classification exercises as well as built data flow maps and run gap analysis. Instead, many firms have taken a piecemeal approach to GDPR, which is mainly focused on requirements that rely primarily on IT to meet specific compliance requirements, such as the requirements for data breach notification. These approaches are short-sighted, and most likely will need radical revision after the enforcement of GDPR…” 2



Privacy is now a top-of-mind issue for every enterprise executive. Protecting sensitive data to meet regulatory demands, however, is often challenging for one simple reason: they don’t know how to find all the sensitive data they’re supposed to be protecting. Advanced AI-powered solutions, like Io-Tahoe, offer enterprises hope that they can find, catalog, and manage this sensitive data, meet their continually emerging compliance requirements — and do it without disrupting their operations.

Charles Araujo, Principal Analyst – Intellyx

Eight Mandates for GDPR Compliance, and the Dividends Beyond

The “silver lining” in GDPR compliance efforts is a creation of transparency and trust with customers, many of whom have layers of concern and trepidation over how all companies they do business with are handling their data. GDPR compliance efforts offer a chance to clear this air, between organizations and their customers, in a way that’s beneficial to both sides.


  • 1.Forrester, Rethinking Data Discovery And Classification Strategies – Strategic Plan: The Data Security And Privacy Playbook. Heidi Shey. July 10, 2018
  • 2.Forrester, The State Of GDPR Readiness – GDPR Readiness Progresses, But Strategies Depend Too Heavily On IT. Enza Iannopollo. January 31, 2018