You may have heard the phrase, “data is the new oil, ” which is entirely accurate. Data is a precious asset for any company, and it is integral to its growth and success.
Businesses use data to gather valuable insights and make decisions that take the company forward. Simply collecting data isn’t something that guarantees success – it has to be appropriately leveraged as well.
When it comes to the processing and management of data, two main processes take place in any company – data governance and data management. These processes are interconnected, and both of them are crucial to a company’s operations.
In this guide, we’ll talk about:
This chapter is part of our comprehensive Data Governance guide.
Data Governance Definition
Data governance is a process used by enterprise systems, and it manages the accessibility, reliability, integrity, and security of the data. Moreover, this process is based on internal data standards and policies used to gauge data usage.
The sole purpose of data governance is to determine and ascertain that the data is consistent and authentic and that it isn’t used for the wrong intentions.
As new and evolving data privacy regulations have been introduced and companies have to rely on them, they turn to data governance to offer them analytics that can optimize their operations and enhance the decision-making process.
Businesses come up with data governance programs to design the policies and standards that will be used to govern data and the procedures enforced to implement said policies.
Data Management Definition
Similar to data governance, data management is also an enterprise-level process. It involves the transportation, storage, organization, and management of data that a company has collected.
Proper and efficient data management is an essential component of the IT system deployment process, which executes business applications and facilitates decision-making by providing valuable analytics. The data is also used for strategic planning and road mapping by business executives and managers.
The data management process encompasses several functions that ensure data accuracy, availability, and accessibility. Most of the process is undertaken by IT and data management teams. Still, business managers also join in to determine whether the data suits their requirements, and they are also briefed about the policies concerning the use of this data.
Data management has become increasingly important in the past few years, and here are some of the reasons why:
- Data management helps executives and managers make more informed decisions.
- It can be used to optimize marketing campaigns and improve business operations.
- It helps businesses reduce costs and boost their revenue and profits
- It helps companies comply with data regulation and privacy laws.
- It helps organizations organize large volumes of data and make it useable for the business.
Data Governance Vs. Data Management
Now that you have a clearer idea of what data governance and data management are, it is time to compare the two and see how they differ from each other.
In essence, data governance is considered a business strategy, whereas data management is more of an IT-based practice. Most executives think that both are the same, which isn’t the case at all.
The only similarity you will find between data governance and data management is that both of them are integral to organizing data for use in your business. Moreover, both of them are handled by managers and executives.
Let’s have a broader look at the differences between the two.
1. Difference in Purpose and Enforcement
It can be said that data governance is a component of the data management process. Data governance helps develop the policies and procedures that a company will use, and data management implements them to gather data and use it for decision-making and business operations.
2. Difference in Managers and Members
Another difference is that data governance is conducted by business managers and executive-level employees, who have more say in the company’s operations. On the other hand, data management is undertaken by the company’s IT department. If you place both of them in order, it suffices to say that data governance precedes data management because the former devise policies that the latter enforces and adheres to.
3. Data Governance Paves the Way for Data Management
You can also consider the difference between data governance and data management with an example. Suppose you want to build a new home on the land you just purchased. Naturally, you would need a house design before you can hire a contractor to build it. For this purpose, you will get in touch with an architect who will design the home and develop blueprints that the construction team can use.
In the above example, the architect refers to the data governance team responsible for building the data management policy blueprint to make the structure. Without the blueprint or a design, your structure wouldn’t be as practical or useful, and it might be prone to breaking down over time.
4. Difference in Tools and Techniques
Both processes also differ in the tools and methods used for each. Data governance revolves around people because they are the ones who generate and handle data and also contribute to properly governed data. It also includes policies and rules that define what is to be done and how it will be done. Last but not least, this process involves metrics, which help you measure the success of your policies and procedures.
On the other hand, data management revolves around the validation and cleansing of data, which makes it comply with the policies set by the data governance team. Later on, the data management team uses data protection and privacy policies to prevent unauthorized access or use of the data. Lastly, the data archiving and retention tools enforce retention policies. Together, these tools help businesses comply with global data protection regulations.
Agile Data Governance with Satori
Satori helps you with DataSecOps for your modern data stack. This includes continuous sensitive data discovery, integration with existing data governance tools to make data governance more efficient and immediate, and means to streamline access to sensitive data and create security policies that are independent of the specific data infrastructure you’re using.
Conclusion
Although data governance and data management are separate processes, they help companies achieve a single goal: to ensure that the business has accurate, reliable, and usable data to build their operations upon and leverage the data to drive more revenue and profits. Therefore, both data governance and data management have a deeply rooted relationship.
