What is Data Governance?
Table of Contents
- By Bryan Lee
- Aug 07, 2023
Decision-makers have always relied on information to make the best choice. However, never in history have they had so much data to draw from. This explosive growth in data forced organizations to realize the need for improved organization so it could be used and protected effectively.
However, these tiresome precautions are necessary. After all, if this information is helpful to you, wouldn't others want it too? The past decade has seen significant upticks in cyber threats coming from around the globe, and defending against them is the key to protecting your organization. Data governance provides the organizational structure that makes this all possible.
What is Data Governance?
The definition of data governance encompasses the processes and rules that ensure the proper management, quality, accessibility, and security of your digital assets. It defines the data's ownership, relevancy, and classifications.
The primary goal of governance is to create a consistent and reliable flow to support data-driven decision-making within an organization. It also ensures that data regulations are followed to avoid legal repercussions or internal disputes. In general, the process can be broken down into a few steps.
The first step to data governance is figuring out what you have to deal with and where it is. As we said before, organizations amass enormous amounts of data daily. Modern solutions build meta-description archives that help programs quickly learn where specific information is stored.
For example, a dataset including clients' email addresses and phone numbers could be assigned a meta description of "client information." Searching this keyword would promptly pull up the information without requiring the user to search for a specific file name.
While the discovery phase makes it easier to find information, data classification helps users understand what types of information are available. Data is separated based on what roles need access and how long it's relevant. Classification is essential to cybersecurity, access control, and keeping clutter out of the databases.
Policy & Rules
This step refers to drafting the organization's "data bible." It is a centralized document that explains the standards that every member must follow to ensure they're optimally and safely using data. These policies cover subjects such as:
- How data integrity is measured
- Assigning stakeholders to datasets
- Procedures and processes surrounding data security
- Outlining how specific data can be used
Why Data Governance Matters
Organizations are virtually required to fragment their data for the sake of security. Access and permissions are split across numerous employees, making retrieving specific data sets a lengthy process. The issue becomes much worse when, after all that, the user receives either wrong or outdated data.
Improved Data Quality
Data governance aids the readability and accuracy of information. Whether the cleansing is performed by artificial intelligence or data stewards, the data sets are checked for errors, inconsistencies, and duplicate inputs before reaching end users.
The data is also reformatted and standardized to ease cross-examination. For example, if one document recorded "Date of Birth" and another used "Birthday," then one would be changed to match the other. The same is done for inconsistent measurement systems such as pounds versus kilograms.
Compliance and Regulation Management
Federal laws such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA) are meant to protect individual’s digital privacy. They make releasing information a significant risk for organizations. Data governance policies put red warning tape around certain information. Users can only access this risky information with certain permissions, and can only be used in certain situations.
Data governance always includes provisions regarding cybersecurity measures. These provisions go hand-in-hand with the regulatory benefits as they revolve around robust data access controls, encryption, and security applications.
The most significant cause of data breaches is human error. It's hard for hackers to break into a well-protected security system, but it's relatively easy to prey on an inattentive employee. Data governance teams often require anti-virus and anti-phishing software that can intercept threats the user misses.
Data governance enhances decision-making by providing high-quality, reliable, and well-managed data to key stakeholders and gaining a competitive advantage.
Meet the Data Governance Team
Drafting these policies and rules is a massive undertaking. Input is taken from all parts of the organization, including upper management, IT professionals, and endpoint users. However, most data governance teams follow a similar structure.
Chief Data Officer (CDO)
The chief data officer sits at the top of the decision tree. A senior executive typically takes the role as it's responsible for creating the team and tracking its progress. The chief data officer is a supervisory position that periodically checks in while performing other duties.
Data Governance Manager (CGM)
The data governance manager position may overlap with the chief data officer. However, the manager takes care of the team full-time. Since data governance is an organization-wide task, the data governance manager works as the bridge between departments.
This person, or persons, coordinates meetings, tracks progress, and decides the next steps in a much more hands-on way than the CDO.
Data Governance Committee
This group decides on the actual policies of the organization. It dictates what's privileged information, how to implement data, and what security protections must be added. It may be easiest to think of the data governance committee as the "lawmakers" of the company. The membership is made almost entirely of high-level management along with key stakeholders.
Data stewards are the governance team's "boots on the ground." They focus on maintaining the data sets and end users to ensure the policies are followed. Data stewards are often assigned specific digital assets they frequently work with. This can range from full to part-time work but doesn't always require deep knowledge of IT.
Data Governance Challenges
You've certainly realized by now that data governance isn't easy. Small businesses with limited staff and resources will find it especially difficult to set up. You must remember that proper data governance is essential to maximizing the data you're painstakingly collecting. Not to mention it keeps you out of trouble with the law.
Here are a few problems you'll likely encounter when creating and introducing data governance policies.
Choosing the Right People
Determining which stakeholders should take part in the initiative is a challenge. These people need to know the flow of data in the organization intimately. This means understanding where data is most helpful and where it carries the biggest risk.
Accessibility vs. Productivity
Keeping data in the right hands is a huge part of data governance. If an employee is barred from crucial information, they may waste days or weeks fishing for access. There's a thin margin between optimization and danger, but allowing space to change the access controls can help mitigate this problem. Doing so is as easy as classifying job titles using metadata and adding additional permissions when a problem arises.
There isn't a business with no room for growth. However, governance teams must be ready to scale their policies simultaneously. Depending on the expansion, they must onboard new users, reformat client data, and redo the entire metadata system.
Data governance involves the people at the top of the pyramid down to its base. After all, the policies apply to everyone equally. Managing collaboration between multiple departments and seniority levels is a social challenge. Leaders will face clashing personalities, schedules, and opinions based on personal experience.
Always Know How Your Data is Governed
Data governance is the cornerstone of effective data management and decision-making. It ensures data quality, security, compliance, and integrity. By implementing a well-defined data governance framework, organizations can optimally use their data while mitigating risks to themselves. Our team can assist you in implementing data governance into your business or bolster your personal safety through comprehensive identity monitoring.