Database Management Basics

Database management is the method for managing data that supports the company’s business operations. It involves storing data, distributing it to users and applications making changes as needed, monitoring changes in the data and preventing it from getting corrupted due to unexpected failures. It is a part of a company’s overall informational infrastructure, which supports decision-making and growth of the company as well as compliance with laws like the GDPR and the California Consumer Privacy Act.

In the 1960s, Charles Bachman and IBM among others came up with the first database systems. They developed into information management systems (IMS) which allowed the storage and retrieve large amounts of information for a range of applications, from the calculation of inventory to supporting complicated human resources and financial accounting functions.

A database is a collection of tables that organizes data according to the specific scheme, for example one-to-many relationships. It makes use of primary keys to identify records, and also allows cross-references among tables. Each table has a variety of fields, also known as attributes, which provide information about the entities that comprise the data. Relational models, developed by E. F. “Ted” Codd in the 1970s at IBM and IBM, are among the most widely used type of database today. This design is based on normalizing the data, making it simpler to use. It also makes it easier to update data without the need to change different sections of the database.

Most DBMSs can accommodate various types of databases, by providing different levels of external and internal organization. The internal level deals with cost, scalability and other operational issues such as the design of the database’s physical storage. The external level is the way the database is represented in user interfaces and other applications. It may include a mix of different external views based on different data models. It also may include virtual table that are calculated using generic data in order to improve the performance.