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Sector-specific law

As explained in Effective Data Analysis

A sector-specific law is a regulation that governs data practices within a particular industry or field because of the nature and risks of its information.

A sector-specific law governs how organizations store, access, and use data within an industry whose information creates particular risks for individuals. section 8.2.1

Common examples include:

  • HIPAA regulates protected health information handled by healthcare providers and insurers, often requiring explicit consent for sharing, access, or use. section 8.2.1
  • FERPA gives students and parents rights to access and correct education records while restricting disclosure of personally identifiable information without consent. section 8.2.1
  • GLBA requires financial institutions to explain data-sharing practices and provide customers with an opportunity to opt out. section 8.2.1

Analytics under sector-specific constraints

A business analytics team can work with data engineering to capture anonymized, aggregated snapshots in dedicated warehouse tables for organizational dashboards, reducing exposure of sensitive information while supporting metric tracking. section 8.2.1

Figure 8.3 Many types of sensitive information are governed by sector-specific laws, both in the US, as in the examples shown here, and around the world.
figure

Compare how sector-specific laws govern sensitive health, education, and financial information in the United States and elsewhere. section 8.2.1

How Effective Data Analysis covers it

How deep it goes
Defines the category and names major laws, but stops short of detailed compliance procedures or legal interpretation.
Examples
Uses healthcare, education, financial services, and anonymized dashboard snapshots as concrete examples.
What you can do after
Operate/configure data workflows to account for sector rules and reduce exposure through anonymized, aggregated data.
How it connects
Connects GDPR and CCPA with HIPAA, FERPA, GLBA, consent, protected health information, anonymization, and aggregation.

Also explained in

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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Effective Data Analysis. The section links point to the parts of the book it draws on.