In the modern world, the value of a company is highly competitive and rapidly changing. To survive in this environment, "data governance" has become an essential value.Collecting data has always been an industry-wide consensus, but why has it become even more important now, and why has it become the standard by which companies judge their future growth? Why have companies become so focused on managing data governance? Today, we'll take a look at what data governance is and why it exists.
What is data governance?
To understand the topic of this article, data governance, let's start with a definition of"governance." The dictionary describes it as "the arrangements that enable decision-making to be carried out responsibly and transparently by all stakeholders, within given resource constraints, in order to achieve a common goal". Originally, the word was used to describe a system of governance. It refers to a management system that exercises political, economic, and administrative authority to manage the work of various sectors necessary to run a country. It's easy to understand when we think of the institutions that run the country. It's a group of people who make decisions to achieve a common goal of national revitalization.
The key is to achieve the goals of the organization.
Now that we have a good idea of what governance is, what does it mean when it's prefixed with the word "data"? To manage or profit from any activity, we collect data.Data governance refers to the process of creating and acting upon the rules that are essential to this data collection process. In other words, the processes, roles, policies, and standard practices that help organizations use information efficiently to achieve their goals are called data governance.
Often, data governance is lumped together with the term "data management. Strictly speaking, however, data management and data governance are not the same thing.Data management is the mission of managing the life cycle of an organization's data. It's the process of tracking data throughout its lifecycle, from creation to destruction, and taking care of it so that nothing goes wrong. Data governance, on the other hand, is about establishing guidelines for building good data.
Broadly speaking, data governance is also a subset of data management, which combines with other disciplines such as data quality, reference and master data management, data security, database operations, and metadata management and data warehousing to address data holistically. If data governance is about strategy and roles, organization and policy, then data management is about execution and operations. Without data governance, clear and efficient data management is impossible.
Master data management (MDM), on the other hand, is a concept that encompasses data governance. The goal of MDM is to improve data quality so that the data collected by various departments provides the most necessary and accurate information for the organization. But even MDM can't succeed without proper data governance - you can't get the information you need without roles and responsibilities for defining, creating, curating, and accessing the data you need.
The importance of data governance
It's no secret that data is critical to a company's ability to compete for survival. How you use it leads to better insights and creates better services. But what are the benefits of having clear data governance in your decision-making process today? Experts have cited six benefits of data governance.
ⓐ A common understanding of data.
- Clearly established data governance ensures a consistent view of data across the organization.
- Business units and organizations can maintain appropriate flexibility over the data they collect.
ⓑ Improve data quality
- Data collected through data governance can ensure the accuracy, completeness, and consistency of data.
ⓒ Design a data map
- With a high level of data governance in place, you can understand where all your data resides.
- You can easily utilize your data assets and connect them to your business at any time.
ⓓ Establish an organizational framework
- Agree on common goals for your organization and have broad insights, but with the right level of consistency.
ⓔ Meet industry requirements and norms
- Utilize guidelines for using data assets while adhering to norms.
- Be able to respond consistently to areas beyond the data field, such as legal and security.
ⓕ Improve data management
- By fusing human assets with sophisticated data assets, you can be more active with data.
Gone are the days of quantity over quality, and good data requires clear data governance in order to be utilized. But managing the intangible asset of data isn't easy: it's interconnected across organizations, and when something goes wrong, it's not always easy to see. To do data governance well, you need to apply social norms and corporate rules to establish a single set of guidelines for managing data, and enforce them responsibly.
Conditions for data governance
In order to establish good data governance, you need a few conditions about your data.
- What level of consistency, integrity, and timeliness does the data need to maintain?
- Whose responsibility is it to control the consistency, integrity, timeliness, and collection of data?
- How will we measure our data management performance?
- Who will define the above rules as new data arises?
Add to this the legal interpretation of data collection, or rules about security, and you've got a whole bunch of rules that need to be put together, and then you need to devise a performance system for the people responsible for data collection. This is because, as mentioned earlier, it is an intangible value and an atmosphere of recognition for the hard work of the people who will be managing the data across departments creates sustainable data governance.
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