Every organization has a huge pile of data, both external and internal, to maintain. However, not every organization is able to manage it well enough in a way that it comes out to be accurate, clean, and easy to access whenever required. Effective data management can help businesses to grow and help them drive revenue as well as cut costs.
What is Data Management?
Data management is the process of storing, protecting, acquiring, and processing the required data so that users can access it to make informed business decisions.
Some of the best data management best practices include:
- Policies and Administration:
- Data Policy: Because data policy defines long-term goals of an organization, so it should be dynamic and flexible. Also, factors like cost, ownership, custodianship, privacy, sensitivity, and liability should be considered when establishing data policy for an organization.
- Role and Responsibilities: It is very important for individuals involved in the project to understand roles and responsibilities in order to meet the data management goals. For this, roles associated with functions should be clearly defined, data ownership should be established in all phases of the project, and data quality should be adequate and agreed upon.
- Capture and Collection:
- Data Quality: Data quality is the main reason why many organizations opt for data management services. When data is entered, stored and managed, the quality of data is affected. Data quality is accessed by verification and validation that tell whether the data is valid or not.
- Data Documentation: The key to good quality of data is documentation process which should be properly managed by companies. Its main objective is to ensure the longevity of data, facilitate discovery of data sets, and to ensure that data users completely understand the context, content, and the data set limitations.
- Data Standards: Data standards define features, collected items, objects that are affected by the function of organizations. So the data should be organized and managed well to a defined protocols and rules.
- Use and Longevity:
- Data Security: Data security covers system, procedures, and processes that save data from awful activities such as malicious attacks, misuse of data, unauthorized access etc. The companies should implement methods like consensus, risk management, risk mitigation and risk assessment to keep data secured and safe.
- Data Access and Sharing: Data should only be accessed by people who are given permission to use it. Also, it is the data owner or custodian who can decide to whom the access to use the data should be given.
Following these data management best practices organizations can maintain high quality and easily accessible data to make quick and informed decisions.