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Updated by Mad Rever on Jul 06, 2015
Headline for A glossary of data related terms
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A glossary of data related terms

Here is a list of recurring terms used in data related functions, complete with a definition of our own.


data governance

it must define the rules for exercising the activities of data management, to ensure compliance with these rules and their implementation and to ensure their development and evaluate their effectiveness


data quality

The Business Intelligence tools, the data warehouses... provide the information the user needs to act and decide. This information is the result of an aggregation of data made in accordance with predefined rules. To provide "good quality data" to the user implies good quality data taken individually and coherent data aggregation.


big data

the black gold of the 21st century offers to organizations the possibility to better target their customers and to differentiate them by suggesting customized offers of services. It consists in all the information collected both off- and online which allows the analysis and the predictability of behaviours, representing essential data as used in marketing. Problem met by big data : the protection of sensitive or confidential data is understandably wished for individuals. A solution would eventually come with the anonymization of data inside the organizations.


database (or DB)

refers to the information stored in an organized manner in a computer system such as the data it comprises can be manipulated easily by software applications and stored effectively regardless of
size. Depending on the context we also refer to:
 - the envelope (the "structures")
 - the contents of the envelope ("data")
 - or both


Database Management System (or DBMS)

software package that allows you to organize, control, view and modify the structures and/or data in a database. DBMSs are classified by type according to the ways of
organizing data that they provide:
 - Flat (eg VSAM, ISAM, UFAS)
 - Hierarchical (eg IMS)
 - Networks (eg IDMS, IDS2)
 - Relational (eg DB2, My SQL, Oracle, Postgres, SQL Server and so on)
 - XML


Information system (or IS)

data set within a defined scope


Model Driven Data Engineering (or MDDE)

MDE process applied to computer data


Model Driven Engineering (or MDE)

The process of building a technical object from a formal and abstract description of the object to achieve



this is the process used to design, describe and realize and put into production a technical system. In the field of databases, it is to create the system used to store data.



The process that allows the transformation of an existing technical system to conform to new specifications. For databases, it is the transformation of a database (that is to say structures, data and their
interactions with the program) so that it can be used to meet new business needs or functions in new technological environments.


Reverse engineering

is the process of examining existing technical processes in order to obtain a complete and detailed description of how a system works. In the field of data management, it is a description of the
structures, business rules, dependencies and access. The goal is to "reconstruct" the different models from an existing technical system.


technical model:

This term refers to the grouping into a single model of logical and physical models. Indeed, in the relational universe, the logical and physical models are sufficiently close to each other that they
can be confused. This model is called "technical" in that it is used for the technical implementation of the database.


data model:

is a generic term that covers:

  • conceptual model
  • logical model
  • physical model


Metadata are data describing other data (semantically data about data). It's the information which allows to recognize the collected data.