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

Thales Cloud Protection & Licensing

This blog will explain how Thales is enhancing CipherTrust Data Discovery and Classification (DDC) with ML models that help analyze data, learn from insights, and improve results. CipherTrust DDC uses a ML model for category classification to identify with high probability whether a document is healthcare, finance, legal or HR related.

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Measuring the impact: Unveiling the savings realized in cloud cost optimization 

IBM Big Data Hub

The scale serves as your trusted navigator, providing tangible metrics and keeping you on track. The functionality has been expanded to capture savings and investments across various categories, including accounts, resource groups, regions and action types (among others).

Cloud 69
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As a CISO, Are You a Builder, Fixer, or Scale Operator?

Lenny Zeltser

As you reflect on the past few years of work, determine which of the following categories fits you the most: Builder: You’re great at building a security program (or significant parts of it) from scratch. You enjoy defining the initial structure, standards, templates, processes, guardrails, and metrics.

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How to build a successful risk mitigation strategy

IBM Big Data Hub

An organization is always changing and so are business needs; therefore, it’s important that an organization has strong metrics for tracking over time each risk, its category and the corresponding mitigation strategy. The only thing left to do is to let the risks play out and monitor them continuously.

Risk 79
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On Surveillance in the Workplace

Schneier on Security

Touted as useful management tools, they can augment biased and discriminatory practices in workplace evaluations and segment workforces into risk categories based on patterns of behavior. However, these practices can create punitive work environments that place pressures on workers to meet demanding and shifting efficiency benchmarks.

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Overcome these six data consumption challenges for a more data-driven enterprise

IBM Big Data Hub

Lack of a common business vocabulary across your organization’s data and the inability to map those categories to existing data leads to inconsistency of business metrics and data analytics in addition to making it difficult for users to easily find and understand the data. Lack of a common data catalog across data assets.

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Balancing AI: Do good and avoid harm

IBM Big Data Hub

HR leaders should address potential job changes, as well as the realities of new categories and jobs created by AI and other technologies. Additionally, routine reviews for model drift and privacy measures should be conducted for each model and specific diversity, equity and inclusion metrics for bias mitigation.