Effective data governance requires more than compliance. Companies are moving forward in a world that has the General Data Protection Regulation in place. This means that it is imperative to ensure data governance in everyday operations. The regulatory mandate was crucial in informing enterprises about this important but often neglected practice.
Compliance is and will continue to be, an important aspect of data governance. We recognize the importance of GDPR in making data governance more mainstream. We need to think bigger. Many organizations are already doing this.
A comprehensive approach to data governance will ensure that both data keepers and users (business analysts) are satisfied. It is a strategic, collaborative, and ongoing practice that allows data to be discovered and tracked, understood in the appropriate context, and maximizes its security, value, quality, and safety. These other factors are critical if you are considering a data governance program.
Data governance can lead to better decision-making. This applies to both the decision-making process as well as the decisions. It is easier for those involved to find valuable insights when data is well-governed. This means that decisions can be made based on the right data. This will ensure greater accuracy, trust, and transparency.
Better data understanding and lineage
Data governance involves understanding the data assets and their storage locations. Governance, when done correctly, provides a comprehensive view of all data assets. Governance provides more accountability. It’s easier to know who is responsible for which data when permissions have been granted.
Good data is extremely valuable in today’s data-driven world. You should treat it like the valuable asset that it truly is. As an example, consider the physical assets of a manufacturing company. A well-run manufacturing company ensures their production-line machinery is subject to regular inspections, maintenance, and upgrades. This allows the line to operate smoothly with little downtime. Data should follow the same procedure.
Greater data quality
Businesses that have effective governance programs will also see an increase in data quality and discoverability as a result of good data governance. Although technically two different initiatives, some of their goals overlap. These include standardization and consistency in data. To clearly distinguish the two programs, you can look at the questions each field poses. Data quality seeks to understand how useful and complete data are, while data governance seeks to identify where and who has responsibility for the data. Data governance consultant improves data quality as it allows you to answer the latter, which makes it easier to deal with the former.
Effectively implementing Data Governance practices
As you might expect, the first step in creating strong data governance is to collaborate with relevant stakeholders to establish standards and policies regarding data governance, Next comes the creation of plans to implement and enforce these procedures. These procedures play an equally important role as your underlying policy.
This process can seem overwhelming and can lead to conflict in an organization. Because data owners have often different ideas about what data governance should look like, this can make it difficult for them to manage their data assets. This article will assist you in making this process as painless as possible.
Involve all stakeholders and data owners from the start.
Regularly provide data governance training and education to all relevant teams, individuals, and stakeholders.
Continuous communication is essential for the successful implementation and development of your data governance processes and procedures. This communication can take many forms, including emails, newsletters, and formal reports. All stakeholders must be involved.
It is important to set clear, specific goals that are measurable.
Start small and increase your efforts as you get more experience. It can be tempting to attempt to achieve all goals at once. However, it is better to keep your focus small and work on building up your systems.
Remember that data governance doesn’t need to be a project. Instead, it should be a practice. This means that it will always evolve and grow.