Metadata provides information about a piece of data, such as its size, format, or author. Attributes, on the other hand, are characteristics or properties of an entity, object, or file that define its features or behavior. In essence, metadata describes the data itself, while attributes describe specific qualities or traits of an entity.
A can be defined as the subject or entity for which data are being collected and stored. It can represent any element, person, product, or event that is being recorded and analyzed within a dataset. In data collection, A serves as the focal point for gathering information and insights.
In information technology, "state" refers to the condition or status of a system, program, or data at a particular point in time. It is used to describe the current configuration, settings, or content of a computing entity. The state can change dynamically as a result of user interactions, input data, or system events.
A data dictionary is a repository that contains definitions of data processes, data flows, data stores, and data elements used in an organization. It helps to provide a common understanding of data terminologies and structures within a dataset or system. Data dictionaries are often used to maintain consistency and clarity in data management and analysis processes.
data dictionary
record
A group of related data elements treated as a unit is called a record. It typically represents a single entity or item and contains fields that store specific attributes or information about that entity. Records are often organized within a database to facilitate efficient data management and retrieval.
An entity refers to a distinct object, person, concept, or event about which data is stored. An attribute is a characteristic or property of an entity that describes it or provides more information about it. Attributes help to define the specific details or features of an entity.
Entity can be an account, activity, or contact about which data can be stored.
Metadata provides information about a piece of data, such as its size, format, or author. Attributes, on the other hand, are characteristics or properties of an entity, object, or file that define its features or behavior. In essence, metadata describes the data itself, while attributes describe specific qualities or traits of an entity.
Entity-Relationship diagrams are useful for modelling data and the relationships between the data. They can be used when the constraints between data are relatively simple. They do not allow specification of interactions between the data or model how the data changes (there are no processes in Entity-Relationship). Entity-Relationship diagrams are most often used to model databases.
None. The data set has no elements and so there cannot be any central tendency.
Signal Element Versus Data Element: Let us distinguish between a data element and a signal element. In data communications, our goal is to send data elements. A data element is the smallest entity that can represent a piece of information: This is the bit. In digital data communications, a signal element carries data elements. A signal element is the shortest unit (time wise) of a digital signal. In other words, data elements are what we need to send; signal elements are what we can send. Data elements are being carried; signal elements are the carriers.
Entity means a specific thing in both database work and data modeling. An entity is data that can be classified, and has a relationship with other classified data, as in entities.
The E-R model is a data model used to describe the relationships between entities in a database. An Entity set is a collection of similar entities (objects) with shared attributes that are grouped together in the database.
entity
An entity is a fundamental thing of an organisation about which data may be maintained. It has its own identity which distinguish it from other entity.