Data are the raw facts and are referred to as the stored representation of events and objects that have importance and meaning in the user’s environment. Data can be structured or unstructured.

Both the data and information are closely related to each other. Information is the data that is processed to increase the knowledge of a person who uses that data.

Metadata is the data that describe the characteristics or properties of data used by the end user and the context of those data.

Enterprise Resource Planning is a process of managing businesses. This process is used by many organizations to manage and integrate different parts of their businesses. It integrates all the important factors like product planning, manufacturing, development and sales.

Data Warehouse is a collection of large amount of data and information from different sources and management of that data to provide meaningful business insights.

Constraints are used for specifying rules for the data in a table. It is used to limit the type of data to ensure reliability and accuracy of the data.

Database is a collection, organization, storage, update and access of data. Database makes data management easy.

Entity can be a place, person, object, concept or event in the user environment about which the organization wants to maintain the data.

Database management system is a software system that is used to create, store, update, retrieve, maintain and access user databases.

Data lake is referred as a repository that stores a large amount of raw data in its native format. Data lake can store structured or unstructured data. Data lake stores data using a flat architecture.

System Development Life Cycle is a traditional method used to develop, maintain and replace information systems. It is a complete set of steps that include professionals like designers and programmers to develop and maintain information systems.

Prototyping is an iterative process involved in systems development in which there is a conversion of requirements to a working system which is revised continually through close work between users and analysts.

Enterprise Data Model creates an overall explanation and image of organizational data and not for a particular database. It may involve many databases and describes the scope of data maintained by the organization.

Conceptual data model is a detailed and technology independent specification of the overall structure of data of organization.

Logical data model is a data model that describes the data in a detailed format without considering how the data is physically implemented in the database.

Physical data model describes how data from logical data model is stored by a database management system. A physical data model consists of table’s structure that includes column name, primary key, constraints, data type and relationships between tables.