What is Data Governance?
The average person generates around 147 GB of data each day, consciously or unconsciously, equating to nearly 330 million TB globally. Organizations and businesses produce and collect the most amount of data, collecting it from their operations, customer interactions, market research, web analytics, and internal processes.
Given these, there's no doubt that handling and managing so much data can be a challenge for you and your company. That's where the concept of data governance comes in.
What is Data Governance?
Imagine you have a library. This library has thousands of books but no system in place to organize them. Over time, finding a specific book becomes a nightmare.
Data governance is like employing a librarian for that library. It's the process of managing, improving, monitoring, maintaining, and protecting information in your company. The system makes sure that each piece of data is in its proper place, is accurate, and can be easily accessed when needed.
With proper governance, you can make sure that your data remains trustworthy, consistent, and properly used.
Misconceptions Surrounding Data Governance
When we talk about data governance, it's easy to get lost in what it actually does. However, it's equally important to understand what data governance isn't. By clarifying these misconceptions, we can better appreciate its value and understand how to properly implement it in our daily operations.
It's NOT just about technology
Data governance is about the way a company thinks about and values its digital assets. While tools and software play a role in data governance, it's not solely about using the latest tech. It's more about the processes, people, and policies. The emphasis should always be on creating a culture where everyone understands the importance of high-quality, well-organized systems and information.
It's NOT a one-time project
Data governance is ongoing—not something you set up once and forget. As things change in a business, the way we handle digital assets needs to change, too. So, your system should keep evolving.
It's NOT only for big companies
Every business, big or small, deals with information. Whether you're just starting out or a big company, having rules for your data is always good practice.
For example, a small shop might have details about its buyers, what they've sold, and what's left in stock. If they don't manage this info well, they could mix things up, miss out on selling stuff, or even get into legal trouble.
On the other hand, a big company with many teams genuinely needs good rules for their data. Think about what could happen if one team uses old buyer info while another uses new info. This mix-up can cause internal problems and upset customers.
It's NOT restrictive
Some might think that data governance limits what they can do with digital assets. In reality, however, it actually confirms that information is used correctly and efficiently. Data governance gives you a clear path on how to use your assets wisely.
Data Governance vs. Data Management
The distinction between the two is simple: data management is the action, and governance is the game plan.
Data management is the practical side of things; it focuses on how organizations deal with information on a regular basis. It's about the day-to-day handling of digital assets, which involves collecting, storing, and using information.
On the other hand, data governance sets the rules and policies for managing digital assets. It provides guidelines and policies to make sure data is used and stored correctly. It's the backbone that supports and guides your organization's data management strategies.
Why is Data Governance Important?
Keeping things organized in business paves the way for smoother operations. When it comes to data, this means you can quickly locate the specific information needed to make informed decisions, solve problems, or plan strategies.
That said, here are seven key reasons data governance is crucial:
Enhanced data quality
Businesses base their strategies, decisions, and initiatives on their data. It could lead to costly mistakes if it's incorrect, misleading, or outdated. Conversely, making decisions based on reliable information can lead to increased profits and enhanced customer satisfaction.
Having a proper data governance process in place means your company's data is always accurate and reliable. For example, a retail business can monitor its inventory accurately and prevent supply chain disruptions.
Some laws dictate how certain types of data should be handled, especially personal information. Data governance allows companies to follow these laws and avoid hefty fines, which sometimes reach millions or even billions of dollars.
For instance, the General Data Protection Regulation in Europe is one such law that requires businesses to handle personal data in a specific way. The fine for non-compliance can be up to 4% of a company's global annual turnover or €20 million, whichever is higher.
Implementing a robust data governance strategy can help you avoid these penalties. It can also improve your reputation among customers and partners.
When you uphold data accuracy and consistency, you streamline your processes, reduce errors, and make quicker, more effective decisions that align with your goals and customer needs. In other words, with well-governed data, your business can operate more efficiently, saving you time and money.
Reduced security risks
Data governance includes measures to protect digital assets from breaches, theft, and other threats—such as firewalls or encryption. This system helps prevent data loss and protects your business's private information.
Implementing governance means assigning clear roles and responsibilities for managing your data. This way, there's always someone responsible for any data-related task or issue, leading to quicker resolutions.
Higher level of customer trust
Trust is a cornerstone of customer loyalty; it's what leads to increased business and positive word-of-mouth. When customers know their data is being handled responsibly, they're more likely to trust your company.
Key Components of Data Governance
Data governance is a multi-layered approach to managing and safeguarding digital assets. It includes stewardship, quality, policies and procedures, and security. When implementing a successful data governance plan, there are several key components to consider:
Data stewards are responsible for ensuring that your data is used and maintained properly. They play a crucial role in overseeing business databases. Without their oversight, digital assets can become disorganized, leading to inefficiencies and potential errors.
It's easy to make wrong decisions if you use bad or outdated information. Data quality verifies that the data is accurate, consistent, and up-to-date.
Data policies and procedures
These are the rules about how data should be used and handled. Without clear guidelines, people might use information in ways they shouldn't, which can cause problems.
Data must be protected from theft, breaches, and other threats. If someone gets their hands on digital assets they shouldn't have, they can misuse them by selling personal information, committing fraud, manipulating records, or even launching targeted cyberattacks.
Your First Steps Toward Proper Data Governance
Now that we've gone through data governance's importance and components, it's time to take action. Here's a roadmap to kickstart your journey:
Step 1: Assess
The first step in governance is to take a close look at your current data situation. Examine the sources of your digital assets, how they're stored, and who has access to them. Identify outdated information, inconsistencies in recording, or any other gaps in your current system. Checking these areas allows you to determine the improvements you must implement.
Step 2: Plan
Once you've evaluated your data, the next step is to make a plan. This involves setting clear guidelines on data usage and storage. When deciding on these guidelines, consider things like data sensitivity, regulatory requirements, business objectives, and potential risks. These factors will help make sure that your guidelines are both comprehensive and aligned with your organization's needs.
You'll also need to determine who will be responsible for different parts of the governance process. This could be assigning a team or specific individuals to oversee quality or security.
Step 3: Implement
After planning, it's time to put your data governance plan into action. Train your staff on new policies or introduce governance tools, such as data catalogs and data management software, to help organize information better. In some cases, you might need to bring in experts or consultants to help set up your governance system.
The key is to make sure the changes you make align with your plan and that everyone involved understands the new processes.
Step 4: Monitor
Are the new policies being followed? Is the data quality improving? If something isn't working as expected, you must identify the issue and make necessary adjustments.
As mentioned, data governance isn't a one-time task. It's an ongoing process that requires regular attention. This means checking every three or six months to make sure that the system is working as it should.
Types of Data Governance Tools and Technologies
There are many tools out there that help companies manage their data. When picking a data governance tool, here are five things you should look for:
- User-Friendly: It should be easy to use, even if you're not a tech expert.
- Flexible: Check that it works well with your other tools or systems.
- Secure: Look for features that protect your data.
- Scalable: It should be able to handle more data as your company grows.
- Collaborative: Find one that allows multiple team members to work together seamlessly.
Using a mix of tools can also greatly help your business. For instance, while tools like data catalogs organize your data, others like data quality tools ensure its accuracy. Pairing certain tools, like metadata management, with data security systems makes sure your information is both clear and protected.
This approach allows you to choose the best tools for your specific needs and gives a complete view of your business. With this broader perspective, you can better understand your data and make informed decisions.
In fact, let's now take a look at four data governance tools commonly used by organizations:
Data catalogs are big directories for all your data. They help you find and organize information easily. They can also track where digital assets come from and how it's used, allowing you to trust and rely on the information you have.
Data quality tools
Data quality tools, such as Atacama and IBM InfoSphere, check your data to make sure it's correct and up-to-date. They highlight inconsistencies and errors in your data, helping teams fix issues before they become bigger problems.
Metadata management tools
Metadata management tools, like Informatica and Dataedo, provide a clear context and meaning for each piece of information. With these, you can understand your data better through labels and descriptions. These tools also make it simpler for different teams to use digital assets.
Data security tools
Data security tools keep your data safe from threats or unwanted access. They also offer monitoring features, alerting you if there's any suspicious activity or potential breaches.
Common Challenges in Data Governance
As with any business undertaking, data governance can present its fair share of challenges. Here are some potential roadblocks you may face:
Keeping up with rapid data growth
Always review and update your governance strategies to keep them relevant and effective. After all, you may find it harder to manage and oversee things as all your data piles up.
Moreover, the variety and complexity of data sources can increase as your business expands. This might include new customer channels, partnerships, or even acquisitions. Invest in tools, such as data quality platforms and advanced analytics, that can efficiently manage and monitor large volumes of digital assets.
Balancing access and security
Giving everyone free access to your data can pose many security risks. Data breaches can happen in many ways, such as unauthorized access, phishing, ransomware attacks, and even Insider threats, which is when employees misuse data.
Set up comprehensive user roles and permissions so that each team member has access only to the data they need. After all, too much restriction can hinder work, but too little can lead to data breaches.
Moreover, train your team on security best practices to guarantee that everyone understands the importance of these measures.
You also have to stay updated on the latest security threats and countermeasures. Invest in cybersecurity solutions to stay ahead of advanced threats.
Handling different data types
Data comes in many forms. There's structured data like spreadsheets and databases, as well as unstructured data like emails and documents. Managing and governing these different types can be tricky, as each one requires different tools and strategies.
Invest in versatile management tools that can handle a wide variety of data types. Also, you must set clear guidelines on how to manage each data type. If you're starting out with data governance, consider bringing in specialists or consultants who can provide expert guidance on the process.
Managing high data volume
As you adopt more tools and platforms, the amount of information generated multiplies. So, on top of the variety, the sheer volume of your data can be overwhelming.
As such, invest in more storage solutions, backup processes, and checks. This way, you can make sure that digital assets meet the set standards, regardless of their origin.
Ensuring compliance with regulations
There are many laws and regulations about how digital assets, especially personal data, should be handled. These rules can change and vary from one region to another, and non-compliance can lead to legal issues.
To avoid all this, you must stay up-to-date with the latest laws and regulations related to data governance and implement them accordingly. A legal expert can help your business understand and comply with current laws. Also, inform your team members about these regulations and train them on how to comply with them.
Gaining organization-wide buy-in
Every team member should understand their role in safeguarding and effectively using the organization's data. However, getting everyone, from top-level management to entry-level employees, to understand the importance of data governance and commit to it can be challenging.
Fortunately, it's not impossible if you regularly communicate the progress and outcomes of your efforts.
For example, when discussing data governance with upper management, emphasize the positive impact on the company's strategic direction and profitability. Use facts and figures to showcase the benefits, like improved decision-making and cost savings. Also, highlight how it can reduce potential risks, such as data breaches and regulatory penalties.
Meanwhile, for regular employees, explain data governance in simple terms and how it relates to their daily tasks. Engage them in the process through training sessions or workshops and provide easy-to-follow guidelines on data handling. Recognize those who adhere to these standards to encourage continued compliance and participation.
As data governance policies are set or updated, you must train employees to follow these guidelines. This training needs to be ongoing, allowing everyone to be up-to-speed as new members join or as policies change.
How Is Data Governance Used in Different Industries?
The process of data governance remains a crucial aspect regardless of the sector. Here are a few examples of how data governance is applied in some of them:
Patient records are one of the most sensitive types of data. Mistakes or breaches can have serious consequences. These can affect patient care and violate privacy laws, such as The Health Insurance Portability and Accountability Act (HIPAA).
Hospitals and clinics must manage these digital assets carefully to keep them accurate, up-to-date, and only accessible to authorized personnel.
Another major challenge in healthcare is managing electronic health records (EHRs) from different sources, like labs, doctors, and hospitals. Data needs to be integrated and synchronized for doctors to get comprehensive patient information. This requires advanced data governance techniques and systems.
In the healthcare industry, strict access controls and audit trails are established to monitor who accesses and modifies patient data. Additionally, interoperability standards, such as HL7, are utilized to ensure seamless data exchange between various healthcare providers.
Financial data is often targeted by cybercriminals. In fact, it's the second most-impacted industry regarding reported data breaches last year.
Given the large sums of money and personal details the industry manages daily, data governance ensures the accuracy of financial records. There's also the challenge of ensuring accurate financial reporting and complying with various financial regulations, such as the Sarbanes-Oxley Act (SOX).
The finance industry regularly backs up data, employs robust encryption, and adopts multi-factor authentication to enhance data security. Regular staff training on security and awareness of phishing threats also further bolsters these security measures.
Just like the healthcare and finance industries, retail businesses also deal with sensitive data, primarily customer information and transaction details. In retail, good governance means orders are right, stock counts are correct, and customer details are safe.
To safeguard sensitive transaction data in retail, businesses invest in secure payment gateways. They also employ inventory management software integrated with sales platforms for real-time inventory tracking.
In manufacturing, governance is needed to manage and analyze production, quality control, and supply chain data. This information helps manufacturers improve their operations, identify inefficiencies, and make informed decisions.
However, manufacturing companies often deal with massive volumes of data, such as machine performance metrics and production rates.
For handling big data, manufacturing companies turn to advanced analytics tools. These tools also merge information from varied sources, like machine sensors or supplier databases, which offer a comprehensive view of operations. Additionally, a data classification system is in place to facilitate easy data retrieval and analysis.
Data Governance Frameworks
Different organizations have made guidelines on how to manage data effectively. Here are some widely used data governance frameworks:
DAMA is a non-profit group that has a set of rules that talk about different parts of data handling. It divides data management into several knowledge areas, such as data architecture, data quality, and data security.
DGI is another group with its own framework. It provides a detailed structure, focusing on data stewardship, quality, and policy management. Moreover, the framework is adaptable, allowing businesses to customize it to their specific needs.
IBM, a big tech company, also has its own framework for data governance. It's designed to help organizations understand where they currently stand in terms of data. The model breaks down governance into five maturity stages, from initial to optimized.
CMMI is a process-level improvement training and appraisal program. It focuses on improving processes in any organization, making them more efficient and effective by streamlining processes related to data management and quality checks.
ISO 8000 model
ISO 8000 is a standard that focuses on data quality, particularly emphasizing the importance of data accuracy, consistency, and reliability. By using ISO 8000, companies can make better decisions and build trust with other organizations and consumers.
Data Governance Will Keep Your Business Structured & Trustworthy
Data governance helps make sure that your company's information is correct, safe, and useful. With the right governance system in place, businesses can sidestep issues and make informed decisions.
Plus, be aware that this is not just a one-time thing but something your organizations must keep working on. The more you and your team understand and value its importance, the better your chances of mitigating risks and, ultimately, driving business value.