6 Best Practices for Data Governance

In this article, we’ll take a closer look at 6 best practices for data governance. Before diving into our article, let’s think together why good data governance is so important? Consider what it could lead to without it: poor data quality, data hard to use, data lack of integrity, data vulnerable to cybersecurity threats, data inconsistency , and data is not always available to business users. In other words, from a business perspective, there is no point in having data without data governance.

The Data Governance Institute, an organization that provides best practice and guidance in the field, defines it as, “Data governance is a decision-making and accountability system for information-related processes, performed according to agreed models that describe who can take what action with what information, and when and under what circumstances.”

The digital transformation underway in many organizations will also make strong data governance even more important to the enterprise, because the success of an enterprise depends in large part on the reliability, security, and availability of data to the right people at the right time.

Not surprisingly, demand for data governance products and services is on the rise. Research firm MarketsandMarkets estimates that the global data governance market will grow from $2.1 billion in 2020 to $5.7 billion in 2025, at a compound annual growth rate (CAGR) of 22% over the forecast period.

Factors such as rapid growth in data volume, increasing regulatory and compliance requirements, and increasing business collaborations are also expected to drive the market growth, according to the report. With government agencies around the world enacting a slew of data privacy regulations, ensuring that data within organisations is properly stored, used and discarded is more important than ever, the report said.

Another factor influencing the growth of data governance needs is the increasing adoption of DevOps in software development, the company said. The report states that there is a strong correlation between DevOps adoption and the implementation of data governance programs.

By following some best practices, organizations will be able to create effective data governance programs.

Best Practices for Data Governance – 1. Identify Key Data Elements and Treat Data as a Strategic Resource

But not all data is equally important to an organization, and part of good data governance is understanding which aspects of the data infrastructure are most critical to the business.

“Across the field, you’ll find that these critical elements span dozens to hundreds of systems and applications,” said Jack McCarthy, chief information officer for the New Jersey Department of Justice. These key data elements can be found in multiple reports throughout the system. By first identifying these key elements, you will be able to trace their source and determine applicable policies and procedures.

At a more fundamental level, organizations need to grasp the importance of information to business success. This helps create a culture that supports strong data governance, including at the highest levels of the organization.

“My experience is that the effectiveness of data governance stems from an organization’s willingness and ability to embrace data as a key strategic asset,” said Bill Balint, chief information officer at Indiana University of Pennsylvania.

“Turning raw data into information that yields positive results cannot be considered an afterthought,” Balint said.

Best Practices for Data Governance – 2. Set Policies and Procedures for the Entire Data Lifecycle

Data does not exist at a single point in time. It is created from a data source and goes through the process of cleaning, updating, storing, analyzing, transferring, backing up, deleting, etc. Each step of the lifecycle has potential touchpoints, and managing data at each stage requires having policies and procedures in place for each stage.

“Determine who owns the data and which systems or people can change the data throughout its lifecycle,” McCarthy said. In this way, organizations will be able to provide audit trails and other data checkpoints to ensure a thorough understanding of data elements, he added.

A good example of the need for policy support at the same time is that the New Jersey Department of Justice is considering a risk assessment of criminal justice reforms to remove bail in the state.

“As we try to gather data and identify the key elements needed to automatically calculate assessment tool scores, we continue to drill down into the life cycle of an arrest,” McCarthy said. “We found that the necessary data did not exist at the moment the warrant was filed with the court. The data source occurred earlier when law enforcement completed fingerprint checks to identify the defendant. By tracing our data back to the source, we will be able to co-issue directives and policies with internal and external partners to ensure that key elements of the system we are building are available to us and other downstream partners.”

Best Practices for Data Governance – 3. Involve Business Users in the Governance Process

Enterprise users are often the biggest beneficiaries of good data governance because it enables them to have high-quality, highly available data to help them do their jobs better. If it makes sense, they should also be involved in the governance process.

“I like to form a user group with data owners or their lieutenants,” said Bryan Phillips, senior vice president of technology and chief information officer at packaging company Alpha Packaging. “Then I’ll give them some level of budget control over what’s going on and priorities.”

This facilitates collaboration between departments, fosters knowledge sharing, and can even create a little friendly competition, Phillips said. “You want this group to share a sense of accomplishment. And data governance can be seen as a negative if it’s not done right,” he added.

Data owners are also often the ones best suited to categorize their data, Phillips said. “No one knows the data better than they do,” he said. “You can use this group to identify the problem” and solve the problem.

Best Practices for Data Governance – 4. Don’t Ignore Master Data Management

Governance should also include managing master data, the data about the business that provides context for all business transactions. Effective master data management can improve data consistency and accuracy.

“There has to be (great) emphasis on standardization and cross-referencing of master data,” Phillips said. “This is often the most overlooked area. Without it, data becomes siloed and cross-domain data cannot be correlated. It is important to have the master data group own this data and work closely with business users.”

Ideally, the group responsible for master data management should be a business function that spans multiple departments, not part of IT, Phillips said.

Best Practices for Data Governance – 5. Understand the Value of Information

Data governance is almost a misnomer because it doesn’t necessarily reflect the true value of gathering insights from information.

“Information is the association of data that creates value for an organization,” said Marc Johnson, senior consultant and virtual chief information officer at medical consulting firm Impact Advisors. These include financial records, patient records, employee records, and more.

“Governance requires more than data classification,” Johnson said. “It also requires classification of information. Classification of information shows the value and subsequent impact to the organization if information is lost, stolen or destroyed.” He gave an example where an employee might email information from a company account to private account.

“We have data loss precautions in place to prevent the release of protected health information,” Johnson said. “If we don’t take steps to categorize information, not just data, we can block out a list of chores. If we had not performed additional due diligence, it could have resulted in thousands of false positives in our system, which could have resulted in alarm fatigue, excessive network traffic, and unnecessarily high alert status in the security operations center.”

Data governance requires detailed due diligence to understand who has access to what information and its value to the organization, customers, employees, partners, and others.

“If an organization doesn’t go deep enough into the data governance process, they risk over-engineering, or under-engineering, the protection, availability, and recovery of the business information foundation,” Johnson said.

Best Practices for Data Governance – 6. Do Not Overly Restrict Data Usage

Given the competing value of information resources and the significant security and privacy risks, IT executives may be inclined to severely restrict how data is distributed and used. This can make governance seem more like a negative practice in the organization than a positive one, and ultimately discourage innovation.

Severe restrictions “would limit value creation and inhibit business value,” said Brandon Jones, chief information officer at insurance provider Public Agency Employees Worldwide Insurance (WAEPA). “This has led to user dissatisfaction and lack of adoption of enterprise technology.”

WAEPA has built a comprehensive, comprehensive platform that aggregates data from disparate sources into one platform and leverages multiple visualization techniques based on business stakeholder needs, Jones said. Goals include improving the accessibility, accuracy, and completeness of data to support more confident decision-making.

“Organizational leaders must continually adapt to the needs of the business, and to do this, every stakeholder needs to contribute,” Jones said. They also need to be able to easily and securely access information relevant to their work.

“Governance is about making sure the right problems are being addressed and how data is used to inform decisions about how to address them,” Jones said.

Conclusion

Thank you for reading our article and hope it can help you have a better understanding of best practices for data governance. If you want to learn more about data governance, we would like to advise you to visit Gudu SQLFlow for more information.

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