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Guest Post -- GDPR Compliance starts with Data Discovery

AIIM

This is the seventh post in a series on privacy by Andrew Pery. You might also be interested in: Mitigate Data Privacy and Security Risks with Machine Learning. The Privacy and Security Dichotomy. GDPR and Cross Border Data Flows between the EU and the US: Current State of the Law.

GDPR 102
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How Data Governance Protects Sensitive Data

erwin

With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Lack of a solid data governance foundation increases the risk of data-security incidents.

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Maximize your data dividends with active metadata

IBM Big Data Hub

However, as data volumes continue to grow, manual approaches to metadata management are sub-optimal and can result in missed opportunities. Suppose that a new data asset becomes available but remains hidden from your data consumers because of improper or inadequate tagging. Regulatory and compliance.

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Data Governance Makes Data Security Less Scary

erwin

Add to the mix the potential for a data breach followed by non-compliance, reputational damage and financial penalties and a real horror story could unfold. s Information Commissioner’s Office had levied against both Facebook and Equifax for their data breaches. These can be frightening questions for an organization to answer.

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How Machine Learning Can Accelerate and Improve the Accuracy of Sensitive Data Classification

Thales Cloud Protection & Licensing

In a recent study , IDC predicted the global datasphere will more than double in size from 2022 to 2026, and that 80% of that data will be unstructured. Traditional approaches to data classification use manual tagging which is labor-intensive, error-prone, and not easily scalable.

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What is metadata management and why is it important?

Collibra

.” 2020 Trends in the Data Management, Dataversity. Organizations need metadata management in their data management practice because there is: . Increasing need for data governance, regulatory and compliance requirements and data enablement. Implementing metadata management.

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Four use cases defining the new wave of data management

IBM Big Data Hub

Some of these, such as the continued sprawl of data across multicloud environments have been looming for years, if not decades. The challenge, of course, is the added complexity which hinders the actual use of that data for analysis and AI. Data governance and privacy. Read the eBook. Start a trial. 28, 2021. [2].