Data governance is a definition of the organizational structures, policies, development, rules, and business terms for continuous data lifecycle. The data management is a technical implementation of the data governance. And without proper implementation it is just the documentation. Organizational data management allows the enforcement and implementation of processes and policies.
On the other hand, data management is set of the technologies, which perform on different business rules and policies whereas contributing to information- and compliance requirements of the customers or shareholders. For getting the full grasp on a concept of the data management, we are going to explore major management strategy that is data security. It is one main priority for all the B2B & B2C organizations, which deal with the confidential information. Although lots of businesses consider data protection to the major priority, most do not focus over how they store the data within an enterprise. Without the sophisticated secure data storage practice, businesses may lose and duplicate data, causing higher downtime and reduced accuracy. Right data management means regulating information that enters the database at any time. Results of an effective reporting or managing of the data security will include high accuracy and compliance levels.
Businesses must not treat any information equally. They require right tools and individuals to make sure right management and monitoring of data. As it is very important to know how businesses will use different data pieces, it’s essential they know how the data was included at a first place and meet the compliance standards.
More About Data governance
Principal analyst defines the data governance as “strategic business process that prioritizes and determines financial benefit that data brings to the organizations and mitigates business risk of the poor data practices or quality. Just like other business processes, data governance has got their share of the standard core competencies. But, unlike many other operations in the organization, this particular function orients toward the data processes, performance and planning.
Some businesses view the data governance as a primary way of organizing the data management systems and priorities. For the data governance policy to work rightly, the business leaders must view such component as the framework, the major structure, which breaks off in various parts and functions. Each business may have various primary initiatives for accomplishing within the organization. For this reason, creating the customized data governance system will help the organizations’ leaders to develop the action plans based over their business’s goals & pain points. Some functions, which make up the data governance framework will include:
- Risk management
- Data quality measurement
- Cost minimization
- Data warehousing
- Data security
Master Data Management and Data Governance
MDM includes different processes from creation of the master data from its disposal. And Data Governance creates adjudication and rules of operational processes, which are executed within the processes. Thus, Data Governance doesn’t sit as the separate process. Governance rules will be executed by something as easy as the dropdown box on user interface. For instance, user is given a few things to select from. “It is executing & enforcing the rule.”
MDM needs Data Governance. “You actually are not managing the master data unless you have included Governance. Rules made within the Data Governance make sure privacy and quality of master data “as concepts of Data Governance and MDM are been labeled differently, often they are thought as mutually exclusive, however, they’re not. They are intertwined.” Remember that data governance rules are been attached to data, doesn’t matter where this goes. The rules don’t just start or stop with a MDM application:
How data management and data governance work together?
The data governance is one important component for any corporate management strategy; however, it will not work in the isolation. The data management procedures and policies are needed to make sure data is structured, collected, stored and organized in the right ways. Only when appropriate data classification, collection, metadata management, architecture, integration mechanisms and quality control methods are in proper place will the data governance framework get implemented. You can’t govern data if you are not able to define what this is or how it got collected, where this is stored or how it is accessed.