Data governance is becoming increasingly important as organizations collect and analyze more data. Proper data governance ensures quality, security, and compliance with regulations. For those interested in learning more about data governance, here are some key steps.
Understand the Basics of Data Governance
Data governance establishes who within an organization has authority and control over data assets. This includes what actions people can take with data, such as accessing, modifying, storing, and deleting. Data governance helps define data policies, standards, processes, and metrics. It provides a framework for managing enterprise data throughout its lifecycle.
The goals of data governance include:
- Ensuring data quality and consistency
- Improving data accessibility and availability
- Reducing costs and redundancy
- Managing risk and compliance
- Supporting data-driven decision making
Data governance involves people, processes, and technology. Key roles include data owners, stewards, and custodians. Data stewards in particular work to ensure policies and best practices are followed. Data governance frameworks provide structure, while data governance tools enable control and automation.
Learn the Principles
There are several guiding principles for effective data governance that are important to understand:
- Accountability – Data stewards are responsible for implementing governance.
- Transparency – Processes and decisions are open and understandable.
- Integrity – Data remains accurate and consistent.
- Protection – Data is safeguarded from unauthorized use.
- Compliance – Data meets legal, regulatory, and policy requirements.
- Availability – Data is accessible when and where it is needed.
A successful data governance program will ensure these principles are baked into all data policies and procedures.
Understand the Data Lifecycle
Data passes through different phases, known as the data lifecycle. The typical stages include:
- Plan – Assess data needs and plan governance strategy.
- Capture / Create – Collect or generate new data.
- Organize – Structure, integrate, and store data.
- Analyze – Process and examine data for insights.
- Archive – Move inactive data to long-term storage.
- Destroy – Permanently delete data when no longer needed.
Data governance comes into play at each phase of the lifecycle. Policies should outline requirements for managing data at rest, in motion, and in use.
Learn the Key Processes
Data governance involves an interconnected set of processes. Key processes to become familiar with include:
- Data Quality Management – Ensure data is accurate, consistent, and usable through monitoring, issue resolution, and quality rules.
- Metadata Management – Control metadata like definitions, tags, and lineages to make data understandable and discoverable.
- Reference and Master Data Management – Manage shared data like customer names and product codes.
- Data Security Management – Control access, encryption, masking, and monitoring to protect data.
- Data Risk Management – Identify risks associated with data and determine mitigation steps.
- Compliance Management – Follow laws, regulations, and policies that apply to data.
- Data Operations Management – Ensure efficient and cost-effective storage, integration, and movement of data.
Study Relevant Laws and Regulations
Various laws and regulations relate to data governance. It is important to be familiar with ones applicable to your industry and jurisdiction. Examples include:
- GDPR – European data privacy law
- CCPA/CPRA – California consumer privacy laws
- HIPAA – Healthcare data in the US
- SOX – Financial data for public companies
- PCI DSS – Credit card payment data
Knowing key requirements can inform data governance priorities and help avoid non-compliance risks.
Obtain Relevant Certifications
Consider earning certifications to validate and demonstrate your data governance knowledge. Top certifications include:
| Certification | Offered By | Focus |
|---|---|---|
| Certified Data Governance Professional | Data Governance Institute | Data governance frameworks, best practices, and implementation. |
| CCDP – Certified Chief Data Officer | DOTS Institute | Leading enterprise data strategy and governance. |
| CDMP – Certified Data Management Professional | DAMA International | Data management concepts including data governance. |
| CDPP – Certified Data Privacy Professional | Privacy Institute | Data privacy regulations and controls. |
Join Data Governance Communities
Connect with other data governance professionals through communities like:
- Data Governance Professionals organization
- Data Management Association chapters
- LinkedIn data governance groups
- Conferences like Enterprise Data World
These groups provide networking, idea exchange, mentoring opportunities, and more.
Get Hands-On Experience
Practical experience is essential for building data governance skills. Look for opportunities like:
- Implementing data governance at your current job
- Joining data governance projects as an intern or volunteer
- Taking courses with data governance case studies
- Reading through public data governance plans
- Trying data governance software tools
Hands-on learning will cement your understanding and allow you to apply knowledge.
Conclusion
Following these steps will provide a solid foundation in data governance. Focus on understanding the fundamentals, principles, processes, and regulations. Obtain relevant certifications, join data governance communities, and get practical experience. With dedication and effort, you can become an expert in this essential discipline.
