Data management includes constructing and maintaining a framework to ingest, store, mine, and archive business data. That means it involves different processes and various aspects of management. This article focuses on the various types of data management. So, keep reading to find out even more about them.
- Data warehousing
It is evident that data remains useless unless processed and analyzed. That includes past data, especially when discussing progress and determining if the business is on the right track. Only then can the business get the insights necessary to improve its operations. Data warehousing facilitates access to historical data by the organization. The storage can be physical or cloud-based, and staff members can always retrieve the historical data and analyze it to make decisions whenever a need arises.
- Data Governance
As the name suggests, this is the data management aspect focusing on laws that govern how an enterprise handles data. The policy will guide all the involved parties on how to intake the data. It is also responsible for outlining how it should flow beside the measures of protecting it. It focuses on the network, quality management, security, and usage.
- Data Stewardship
Once the policies have been outlined, this sector’s role is to deploy and enforce them. It involves how the business collects the data and move it across the entire enterprise. The responsibility of implementing the policies and enforcing the rules lie on the shoulders of this particular type of data management and its professionals.
- Master data management
With so many sources of data, there are bound to exist various variations and versions. That’s where master data management comes in. it ensures that everyone uses the correct information besides using the same set of data. Otherwise, it will be hard to read from the same script if every person or department uses a different set of data. It controls the sources and tools that people use when handling data.
- Data quality management
During data collection, some of the common issues are inconsistency and redundancy. That’s where data quality management comes in to eliminate the issues. It involves combining all the collected data, eliminating any duplicate record, not forgetting to unify all the inconsistent versions, but to mention a few.
- Big data management
As the name implies, it involves huge amounts of data, including gathering and analyzing it to make the operation better than before. The data intake, storage, and integrity are analyzed for business intelligence, security, and operations improvement.
- Data Security
Attackers keep targeting enterprise data to destroy its reputation or learn a few tricks of how it operates. Consequently, data security should be an integral part of any organization. That’s where this sector comes in. It will ensure that data is encrypted during transfers to avoid attacks. Equally important, it will see to it that not even a single unauthorized person access the data. Last but not least, unintentional deletion and movement also become a thing of the past.
There are various aspects of data management that every company should put into consideration. Ensure that your organization considers all the above types because none is more important than the other. They should be integrated for successful data management.