Data governance is a data management concept used on both a macro and a micro-level. The former meaning is a political concept and forms part of international relations and Internet governance.
The macro-level data governance refers to the governing of cross-border data flows by countries, and hence is more precisely called international data governance. While the micro-level data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality exists throughout the complete lifecycle of the data. The key focus areas of data governance include availability, usability, consistency, data integrity, and data security and includes establishing processes to ensure effective data management throughout the enterprise such as accountability for the adverse effects of poor data quality and ensuring that the data which an enterprise has can be used by the entire organization.
What is the purpose of data management?
Data management includes the following functions: practicing the disciplines in the development, execution, and supervision of plans, programs, policies and practices that protect, control, deliver and enhance the quality and value of data and information in the organization.
What is the purpose of data governance?
Data governance is the initiative a company takes to create and enforce a set of rules and policies regarding its data. These policies cover issues such as: Assigning accountability to employees responsible for data assets. Granting or restricting access to data, as needed.
What is the difference between data governance and data management?
Data governance defines how data is accessed and treated within a broader data management strategy. While data management is the implementation of architectures, tools, and processes to achieve stated data governance objectives. In other words, data governance pertains to the vision of an organization, and translation of the vision into policy, management is all about making decisions for implementing the policies.
What is MDM or Master Data Management?
Master Data Management is a method used to define and manage the critical data of a business, company, corporation, or organization to provide, with data integration, a single point of reference. Nowadays, there is a lot of company software that provides a reliable MDM that can help you with your planning and execution which will produce a better strategy and solution. Great MDM treats the data as an asset as value like an investment in forex exchange or anything that has a monetary value.
Is the MDM part of data governance?
Proper governance sits on top of MDM, data movement or data warehouses for that matter, and ensures that the data is understood by the business from a definitional, sourcing, quality and accountability perspective. MDM and data governance work with each other, hand-to-hand, or side-by-side to provide you the highest quality of data and avoid further loss or failure in data management.
Customer MDM - Use Case
Why data governance is important and why you need it?
Data Governance is very much important to any business, company, or organization because it ensures the data and/or information assets are accurate, formally, properly, proactively and efficiently managed throughout and to secure its trust and/or accountability. Especially when the quality and/or accuracy of data are needed most, this will gives you a lot of benefits and more returns from your investment. Imagine if the data is not accurate, such as transaction data, will never provide the result you are looking for. Then you will find yourself spending more time, more effort, and more resources to your management.