Understanding data management basics

Data management is by itself a wide topic. Any organization will have valuable information / data that are critical to its business. Managing such data or information is what is called data management. It covers data architecture, analysis, design, policies, practices and procedures to manage data in an enterprise. In short we can say that the program or the functions used to control access to data sets and to regulate the input and output of data to and from the systems are part of the data management function.

Management of information lifecycle with the necessary tools like database management systems together forms the data management. If we further drill down to the lowest levels of task in data management we can find that there are many tasks like, data architecture, data analysis, design, protection, integrity, security, access, privacy, business intelligence, data mart, data mining, and data warehousing.

 

Data management also includes managing the physical storage of data in the hard drives and other storage devices. Controlling access to this physical storage and protecting the storage are also part of the data management tasks. Database administration is another task that is very important in protecting the data from unauthorized access, removing duplicate data, and data maintenance. Database administration is very important in data management.

 

Administrators are there to take care of the database environment and they take are of backup of data, security, and availability of data at all the time. They also support development and take care of performance of the database.

With proper maintenance of data and by the usage of business intelligence software the top management in any organization can take important decisions easily.

 

The future expansion of the organization depends on the business intelligence module that makes use of the existing customer data and product related data in your database. Now-a-days when we talk of data management, it is inferred that it is information management and knowledge management. Pros and cons of these inferences are there and disputes go on.