Learn how to use masking, shuffling, and encryption to meet the latest data privacy regulations and prevent unauthorized access to sensitive data.
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This guide reviews the 3 key capabilities to look for in a data quality tool so you can manage complexity and engage the right people in the data quality process.
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This guide shows you how to embed real-time data quality in business processes and applications so you can rein in the cost of bad data.
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Data portability is the capability to move data from one platform or service to another.
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This guide helps you define the problem and start to solve it. What is data quality? Why does it matter? What impact could it have on your organization?
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This Definitive Guide to Data Quality outlines how your organization can ensure good quality data for correct, actionable business intelligence.
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The General Data Protection Regulation (GDPR) harmonizes data protection regulations and policies, and offers a detailed guideline on which aspects of data governance to focus on in order to protect the personal data of subjects. Learn how to enforce compliance across your organization with the right data tools.
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The General Data Protection Regulation (GDPR) holds organizations & their vendors accountable for the protection of personal data. To ensure accountability & to assign clear responsibilities, legal data sharing agreements need to be set up. Learn to avoid messy situations during a breach & help protect personal data.
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The General Data Protection Regulation (GDPR) requires that organizations make data access and/or deletion easily available for data subjects. This requires companies to manage information lifecycle management (ILM), from creation through disposal, including consolidating data fragmented across systems.
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Analytical models feed off customer profiles to predict future behavioral patterns. The introduction of the General Data Protection Regulation (GDPR) requires ensuring that these do not interfere with the rights of data subjects. Learn how to make sure your organization is compliant.
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Due to the General Data Protection Regulation (GDPR), organizations have to focus on data lineage of subjects, and track personal data through systems. By understanding lineage, organizations can tell who, when, and which system caused data to change, increasing data quality and security.
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The General Data Protection Regulation (GDPR) pushes organizations to establish controls that allow data subjects to address personal information quality issues in a timely manner. Automated solutions and self-servicing tools can make it easy.
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Vendor risk assessment is a subset of data protection impact assessment impacted by the General Data Protection Regulation (GDPR). Most organizations examine internal systems, but often overlook third parties — suppliers and service providers.
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The General Data Protection Regulation (GDPR) mandates a data protection impact assessment (DPIA) when data processing could pose a high risk to data subjects’ rights. A DPIA analyzes if a change to the process may compromise a subject’s privacy.
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The General Data Protection Regulation (GDPR) recognizes that some personal data can reveal a person’s identity, while other data may be processed or stored in a way that keeps the identity confidential. Data masking is an important part of GDPR compliance.
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It’s important to establish data collection standards with the General Data Protection Regulation (GDPR) coming into effect Data comes from everywhere in the big data era, so standards have to be set from both technology and process perspectives.
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Being able to identify critical datasets and critical data elements is crucial for GDPR compliance, but it’s not always easy. It requires a clear understanding of personal data and how it is stored, used, and protected.
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In the context of General Data Protection Regulation (GDPR), data owners are accountable for the quality, integrity, and protection of the data they own. Establishing data owners is an important step for GDPR compliance.
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With GDPR coming into effect, creating data taxonomy—the classification of data into categories and subcategories—is vital. Data taxonomy makes it easier to run profiling, clean data, and employ common terminologies and semantics across systems.
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The GDPR has caused many organizations to revamp their data governance. Even organizations not in the European Union (EU) but that process EU client personal data must be GDPR compliant. Learn how to develop policies and controls that meet GDPR standards.
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Data management refers to the professional practice of constructing and maintaining a framework for ingesting, storing, mining, and archiving the data integral to modern business. Discover 7 types of data management, the benefits of doing it right, 3 best practices, and how to find the right tools.
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This white paper shows you how to spot bad data and debunks the 6 most common data quality myths.
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Research Director Timm Grosser at BARC and Jean-michel Franco, Talend GDPR expert, walk you through the surprising results of a BARC/CXP survey of European organisations.
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Data governance establishes processes that ensure data quality and security across an organization. Learn why it’s important and how to get started.
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The General Data Protection Regulation (GDPR) addresses the security of the processing personal data. This requirement for data protection also applies to end-user computing (EUC) applications. Companies need to convert to another automation system or manage data protection within an EUC app.
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