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Database design. Database design is the organization of data according to a database model. The designer determines what data must be stored and how the data elements interrelate. With this information, they can begin to fit the data to the database model. [1] A database management system manages the data accordingly.
The process of designing a database involves producing the previously described three types of schemas – conceptual, logical, and physical. The database design documented in these schemas is converted through a Data Definition Language, which can then be used to generate a database. A fully attributed data model contains detailed attributes ...
It involves the database environment as well as security. Extract, transform, load (ETL) design and development is the design of some of the heavy procedures in the data warehouse and business intelligence system. Kimball et al. suggests four parts to this process, which are further divided into 34 subsystems [3]: Extracting data
t. e. In computing, extract, transform, load (ETL) is a three-phase process where data is extracted from an input source, transformed (including cleaning), and loaded into an output data container. The data can be collated from one or more sources and it can also be output to one or more destinations. ETL processing is typically executed using ...
Database normalization is the process of structuring a relational database accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model. Normalization entails organizing the columns (attributes ...
Evolutionary database design. Evolutionary database design involves incremental improvements to the database schema so that it can be continuously updated with changes, reflecting the customer's requirements. People across the globe work on the same piece of software at the same time hence, there is a need for techniques that allow a smooth ...
A data architecture, in part, describes the data structures used by a business and its computer applications software. Data architectures address data in storage, data in use, and data in motion; descriptions of data stores, data groups, and data items; and mappings of those data artifacts to data qualities, applications, locations, etc.
Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.