The Key Differences Between Data Governance and Data Management

There are two crucial components of managing data: data governance and data management. Each has its distinct advantages; the key is to know which one to use in any given situation. Keep reading to learn more about the key differences between data governance and data management.

Defining Data Governance and Data Management

When debating the use of data governance vs data management practices, it’s important to understand the differences between the two. Data governance is the process of overseeing how an organization collects, stores, and uses data, whereas data management is the process of organizing and managing data so that it can be used efficiently.

The primary difference between data governance and data management is that data governance focuses on the organization’s overall strategy for data, while data management focuses on specific tasks such as creating and maintaining databases.

Data Governance Processes

The main benefit of data governance is that it helps to ensure that data is consistently accurate, reliable, and timely. This is accomplished by setting standards for how data is collected, managed, and used. Data governance also helps to ensure that everyone who needs access to the data has permission to access it and that the appropriate security measures are in place to protect it.

Data governance includes activities such as defining standards for collecting and storing data, creating processes for approving new datasets, and developing policies for using data. Data management includes tasks such as designing databases, creating queries, and importing and exporting data.

The goal of both data governance and data management is to ensure that the organization’s data is reliable and accurate. However, the two processes differ in their focus: data governance focuses on establishing rules for how the organization will use its data, while data management focuses on making sure that the organization’s data is properly organized and accessible.

Data Management Processes

Data management, on the other hand, focuses on managing the technical aspects of storing and using data. It includes tasks such as creating databases, developing applications that use the data, and configuring networks to support the flow of data. While data management is important for ensuring that data is accessible and usable, it does not typically address issues such as accuracy or reliability.

Other data management processes include developing a master database schema, loading data into a database, and creating reports.

The Challenges of Implementing a Good Data Governance Program

The key challenge in implementing an effective data governance program is getting everyone in the organization on board. This requires commitment from senior management down to the individual employees who will be responsible for collecting and using the data. It also requires cooperation between departments that may have conflicting goals or use cases for the data.

Another challenge is ensuring that all relevant data is captured and included in the governance process. This can be a daunting task when you consider how much unstructured data organizations contend with in the modern business landscape. And finally, it’s important to develop a strategy for enforcing data governance policies that outlines the consequences of violating those policies.

Effective Data Management Depends on Data Governance

While data governance and data management are two distinct concepts, each must be effectively implemented to ensure the success of the other. Think of data governance as a strategic, high-level activity that sets the overall direction for an organization’s data, and data management as the tactical implementation of that strategy. Data governance defines how an organization will use its data to achieve its business goals, while data management ensures that those goals are met by creating and enforcing policies for governing the collection, storage, use, and disposal of data.

Put another way: Data governance is the process of overseeing data throughout its entire lifecycle, while data management is the implementation of those policies.

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