Quality & Governance
Data Quality
Definition: Data quality refers to data conditions based on accuracy, completeness, reliability, and relevance. High-quality data meets the needs of its intended use in operations, decision-making, planning, and analytics.
Key Aspects:
Accuracy: Ensuring data correctly reflects real-world entities or events.
Completeness: Data should be sufficiently complete for the task at hand, lacking no critical information.
Consistency: Data should be consistent across different datasets and systems, with no contradictions or discrepancies.
Timeliness: Data should be up-to-date and available when needed.
Relevance: Data collected and stored should be relevant to the purposes for which it is used.
Strategies for Improving Data Quality:
Data Profiling and Cleaning: Regularly assess data for errors and inconsistencies and perform cleaning to correct or remove inaccuracies.
Data Validation: Implement validation rules to prevent incorrect data entry at the point of capture.
Master Data Management (MDM): Use MDM to ensure consistency of core business entities across the organization.
Data Quality Metrics: Develop metrics to monitor data quality and identify areas for continuous improvement.
Data Governance
Definition: Data governance encompasses the practices, processes, and policies that ensure the effective and efficient management of data assets across an organization. It covers data accessibility, consistency, usability, and security, ensuring that data across systems is managed according to specific standards and compliance requirements.
Key Components:
Policies and Standards: Establishing clear guidelines for data handling, storage, and sharing, including standards for data formats, quality, and security.
Data Stewardship: Assigning data stewards responsible for managing data assets, monitoring data quality, and enforcing data governance policies.
Compliance and Security: Ensuring data complies with relevant laws and regulations (e.g., GDPR, HIPAA) and implementing measures to protect data from breaches and unauthorized access.
Metadata Management: Managing metadata to provide context for data, including origin, usage, and quality, making it easier to understand and utilize data across the organization.
Popular Laws
GDPR (General Data Protection Regulation) It's designed to protect EU citizens' privacy and personal data and harmonize data privacy laws across Europe.
CCPA (California Consumer Privacy Act): A state statute intended to enhance privacy rights and consumer protection for residents of California, USA.
PIPEDA (Personal Information Protection and Electronic Documents Act): Canada's federal privacy law for private-sector organizations.
LGPD (Lei Geral de Proteção de Dados): The Brazilian General Data Protection Law, similar to GDPR, regulates the processing of personal data.
PDPA (Personal Data Protection Act): Singapore’s privacy law that governs the collection, use, and disclosure of personal data by organizations.
HIPAA (Health Insurance Portability and Accountability Act): A US federal law that created standards to protect sensitive patient health information.
COPPA (Children’s Online Privacy Protection Act): A US law that imposes specific requirements on operators of websites or online services directed to children under 13 years of age.
Data Protection Act 2018: The UK's implementation of the GDPR, which controls how organizations, businesses, or the government use personal information.
The Australian Privacy Act 1988 (Privacy Act): Regulates how personal information is handled by Australian government agencies and organizations.
Key Aspects of GDPR:
Consent: Requires clear consent for processing personal data. Consent must be freely given, specific, informed, and unambiguous.
Right to Access: Individuals have the right to access their data and to know how it is processed.
Right to Be Forgotten: Data Erasure entitles individuals to have the data controller erase their personal data under certain circumstances.
Data Portability: Individuals can request a copy of their data in a machine-readable format and have the right to transfer that data to another controller.
Privacy by Design: Calls for the inclusion of data protection from the onset of designing systems rather than an addition.
Data Protection Officers (DPOs): Certain organizations must appoint a DPO to oversee compliance with GDPR.
Breach Notification: Data breaches that may pose a risk to individuals must be notified to the data protection authorities within 72 hours and to affected individuals without undue delay.
Data Minimization: Organizations should only process the personal data needed to fulfill their processing purposes.
Cross-Border Data Transfers: There are restrictions on the transfer of personal data outside the EU, ensuring that the level of protection guaranteed by the GDPR is not undermined.
Penalties: Non-compliance can result in heavy fines, up to €20 million or 4% of the company's global annual turnover, whichever is higher.
GDPR is not only for organizations located within the EU but also for those outside the EU if they offer goods or services to monitor the behavior of EU data subjects. It represents one of the world's most stringent privacy and security laws and has set a benchmark for data protection globally.
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