Data Masking - Further Information

Voracity’s key strength is its ability to not just deliver broad data integration and transformation functionality, but to deliver it within a unified, centralised, integrated platform.

Increased privacy regulation and public awareness have made it more important than ever to handle sensitive data ethically. But what does that mean in practice?

IRI Voracity is a data management platform that provides significant data masking and discovery capabilities.

This (Cloud) Data Management report compares platform-based approaches that support data integration to/from cloud-based deployments.

The basic concept behind the Talend Data Fabric is to allow you to collect, govern, transform, and share your data.

SOLIXCloud is a cloud data management platform from Solix Technologies that provides four primary solutions.

The Qlik Data Integration Platform is essentially a melding of the capabilities provided through the acquisitions of Podium Data and Attunity.

Oracle’s data management capabilities span the establishment of (cloud-based) data warehouses and data lakes.

The Intelligent Data Platform encompasses data integration, quality, governance, MDM, cataloguing, privacy, application integration, and more.

IBM Cloud Pak for Data places particular emphasis on deploying, developing and managing AI and machine learning models.

The Lumada DataOps Suite from Hitachi Vantara supports everything from ingestion through to analysis and dashboards.

Cloudera Data Platform offers data integration, data governance, data cataloguing and transformation capability but not data quality per se.

Ataccama ONE encompasses data integration, data cataloguing, data profiling and data quality, and both reference and master data management.

MarkLogic Data Hub is a fully cloud-native platform for data storage, integration, operationalisation and governance.

Powered by CoSort (or Hadoop), and built on Eclipse, IRI Voracity is a multi-purpose data management platform.

This Market Update discusses, reviews and compares products specialising in the discovery of sensitive data.

Ab Initio Semantic Discovery is a data discovery solution offered as part of Ab Initio’s broader data management platform.

The Lumada Data Catalog from Hitachi Vantara is a data catalogue targeted at both the enterprise data lake and traditional data environments.

Seeker DLP finds sensitive data within files on Windows and Macs, across SMB-based file servers and web servers.

STEALTHbits supports discovery against a comprehensive list of file systems, SharePoint and OneDrive, Exchange, Dropbox, Oracle and Microsoft SQL Server.

DataSunrise supports the discovery of sensitive data across a wide range of both relational and NoSQL data sources.

Solix Common Data Platform acts as a one stop shop for the management and governance of all enterprise data.

Dataguise started by offering sensitive data discovery and masking but now includes, additionally, encryption/decryption and extensive reporting.

MENTIS iDiscover offers a range of modules that cover all necessary functions for discovering, protecting and monitoring sensitive data.

BigID specialises in (sensitive) data discovery and classification and unlike other vendors has been built from the ground up to concentrate in this area.

Enterprise Recon offers enterprise-wide discovery of personal, PII and PCI data in accordance with a wide range of compliance regulations.

Informatica Data Privacy Management is a datacentric privacy, governance and security solution that is focused on discovering and classifying sensitive data.

Global IDs offers data discovery and classification as part of its EDA platform, thereby providing sensitive data discovery and compliance with regulations.

This paper considers the requirements of GDPR and then discusses how MENTIS meets those requirements.

This paper compares the capabilities of IBM, Informatica and MENTIS for the discovery and governance of sensitive data.

This paper is a discussion and technical evaluation of the MENTIS Data and Application Security Platform.

In this paper, we have identified the potential significance of a wide range of data-based technologies that impact on the move to a data-driven environment.

This Market Update compares the capabilities of different data masking vendors that provide anonymisation capabilities.

This paper discusses why data lakes need to be managed and the sorts of capabilities that are required to manage them.

This paper discusses the EU's forthcoming General Data Protection Regulation (GDPR) not from a legal perspective but from the point of view of data management.

This paper argues that using manual methods for data masking are typically inadequate, time-consuming, and costly and offers solutions from data masking tools.

Data masking is now recognised as being increasingly important, not least because of concerns over privacy and security.

Data masking, although it has been around for a number of years, is now recognised as being increasingly important.

In this paper we shall discuss why it is important, why you should consider using a tool, and what features you should look for.

This paper argues that using manual methods for data masking will typically be inadequate, is time consuming and costly.