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Successful businesses have the right understanding of the data and the ways to use them effectively in the business. Data governance and data management are the two important strategies that help a business store, organize and use their data to solve problems. In this article, we are going to discuss both these terms to help readers get clarity about them.

EWSolutions has been a leading provider of data governance services since 1997. Their approach provides a customized methodology and the right governance program to each client partner to suit their requirements.

What is Data management?

Data management is seen as the IT practice that works with the objective to organize and control your data resources to make them accessible, dependable, and timely whenever users need them. This process is essential, because if data is not treated properly, then it will become unusable, useless, and corrupt.

The IT teams use a comprehensive, and customized set of processes, theories, practices, and systems to protect, gather, validate, organize, store, process, and maintain data.

What does Data management comprise?

Data management includes the following different categories, and fields that are pertinent to the company:

  • Data governance
  • Data security management
  • Data stewardship
  • Data quality management
  • Data warehousing
  • Data architecture
  • Business intelligence
  • Business analytics
  • Metadata management

What is Data governance?

Where data management is viewed as the logistics of data, data governance is viewed as the strategy of data. Data governance comprises a broad set of practices, theories, and processes. It can overlap with several data areas, such as usability, security, privacy, compliance, and integration.

It is more expansive and holistic than data management as it is a key business program, that requires implementation of the right policies in the business. It is best reached by consensus throughout the company.

The main objective of data governance is to determine how does a company prioritizes the financial advantages of data while preventing the business risks associated with poor data. Data governance requires a company to determine the following things about data to make it more usable:

  • How to creates data?
  • Where is data accumulated and used?
  • How precise it should be?
  • What rules should the data follow?
  • Who is involved in the several phases in the data lifecycle?

Benefits of data governance

Here are some important advantages of data governance in an organization:

  • Increasing the data value of the company
  • Reduce costs within other data management subsets
  • Increase overall revenue of the enterprise
  • Standardizing data policies, systems, and procedures
  • Ensure the right rules and compliance procedures
  • Assist in solving data issues
  • Promote transparency
  • Establish education and training that surrounds data

About Data Governance Framework

A data governance framework outlines systems and processes that will be used for the creation, storage, maintenance, and disposal of data. The model determines the structure of responsibility for data management. Based on the creator and user of data, an organization can adopt several different types of data governance models. These include:

  • De-Centralized Data Governance Model with Single Business Units
  • De-Centralized Data Governance Model with Multiple Business Units
  • Centralized Data Governance Model
  • Centralized Data Governance Model with De-Centralized Execution

Conclusion

Data governance and data management are two different concepts or practices. Both of them are necessary to ensure the valuable and successful usage of data in the organization. They work with a common objective to determine a holistic way for controlling data assets to enable firms to get the maximum value from the available data.

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