Personal data refers to any information that can identify a person, either on its own or when combined with other data. This includes details like a person’s name, address, phone number, email, identification numbers, and even online identifiers such as IP addresses. Personal data can also be more sensitive, like health records, racial background, political opinions, and financial information.
For example, if a company collects your email address and phone number when you sign up for a service, this is considered personal data because it can be used to identify you.
In general, personal data is anything that relates to an individual and can reveal who they are. Laws like the GDPR in Europe aim to protect personal data by requiring organizations to handle it responsibly and transparently.
The following 8 unique categories, and types are explained here for your further understanding.
- Health Data
- Health data refers to any information about a person’s physical or mental health. This can include medical records, treatments, diagnoses, and details about medical conditions. Since this data is very sensitive, it is given extra protection under laws like GDPR, CCPA, & PDPL.
- Example: Fitness tracking apps that collect data about your daily workouts, heart rate, or sleep patterns process health data.
- Racial or Ethnic Origin
- This category includes any information that identifies a person’s racial or ethnic background, including their ancestry or nationality. It helps to recognize people’s ethnic group, which can sometimes be sensitive.
- Example: A university survey asking students about their racial or ethnic background to collect demographic information for research purposes.
- Political Opinions
- Political data involves a person’s beliefs, affiliations, or opinions about politics. This can include which political party they support, their voting choices, or any political events they have been part of.
- Example: A record of people who donated to a political party or attended a political rally would be considered political opinion data.
- Religious or Philosophical Beliefs
- This includes data about a person’s religion or personal beliefs. It could be information about the religious group they belong to, their participation in religious activities, or their philosophical views.
- Example: A database of people who have registered for religious education classes or are members of a spiritual society.
- Trade Union Membership
- This category covers information about a person’s membership in a trade union, which represents workers in negotiations with employers. Such data is sensitive because it could lead to discrimination or unfair treatment.
- Example: A company storing information about employees who are members of a trade union to help negotiate better wages or working conditions.
- Genetic Data
- Genetic data refers to information obtained from someone’s DNA or RNA, which reveals unique details about their health or physical traits. This type of data is particularly sensitive as it can expose potential health risks or conditions.
- Example: Direct-to-consumer DNA testing services that analyze a person’s genetic makeup to give insights about their ancestry, health risks, or physical traits.
- Biometric Data
- Biometric data is information related to an individual’s physical or behavioral characteristics that can be used for identification. This can include fingerprints, facial recognition, or voice patterns.
- Example: A company using fingerprint scans for employees to enter the office must protect this biometric data carefully.
- Sexual Orientation
- This category includes data that reveals a person’s sexual preferences, experiences, or relationships. It covers information about someone’s sexual orientation or activity.
- Example: Dating apps that ask users to share their sexual orientation to match them with potential partners use this type of sensitive data.
For Your Further Reading:
- Big Data vs. Traditional Data, Data Warehousing, AI, and Beyond
- Big Data Security, Privacy, and Protection, & Addressing the Challenges of Big Data
- Designing Big Data Infrastructure and Modeling
- Data Strategy vs. Data Platform Strategy
- ABAC – Attribute-Based Access Control
- Consequences of Personal Data Breaches
- KSA PDPL (Personal Data Protection Law) – Initial Framework
- KSA PDPL – Consent Not Mandatory
- KSA PDPL Article 4, 5, 6, 7, 8, 9, 10, 11, & 12
- KSA PDPL Article 13, 14, 15, 16, 17, 18, 19, 20, & 21
- KSA NDMO – Data Catalog and Metadata
- KSA NDMO – Personal Data Protection – Initial Assessment
- KSA NDMO – DG Artifacts Control – Data Management Issue Tracking Register
- KSA NDMO – Personal Data Protection – PDP Plan, & PDP Training, Data Breach Notification
- KSA NDMO – Classification Process, Data Breach Management, & Data Subject Rights
- KSA NDMO – Privacy Notice and Consent Management
- Enterprise Architecture Governance & TOGAF – Components
- Enterprise Architecture & Architecture Framework
- TOGAF – ADM (Architecture Development Method) vs. Enterprise Continuum
- TOGAF – Architecture Content Framework
- TOGAF – ADM Features & Phases
- Data Security Standards
- Data Steward – Stewardship Activities
- Data Modeling – Metrics and Checklist
- How to Measure the Value of Data
- What is Content and Content Management?
