D

Dashboard

A method that is used to display management information in a simple way. The analogy is that of a dashboard in the car, on which one can see at a glance all the relevant information that one needs to drive the car. A dashboard in BI terms is usually one screen on which the most relevant information that is required …

Data conditioning

Method to compress data and to reduce storage capacity data definition language (DDL). Standard to describe and define elements (data) in a database. The term ‘data description language’ is also used.

Data

All internal and external data that is relevant to business operations. Also data generated during business operations. In BI terms, it often concerns data that is recorded or to be recorded electronically. (Un) structured, apparently random data form the basis for BI solutions that are able to convert it into usable (control) information.

Data analysis

Analyzing data and data flows in preparation for further structuring and modeling.

Data architect

Specialist in the preparation of data models and also in the preparation of Data Warehouse architectures.

Data cardinality

Number of times a relationship or association can / may occur. For example: A project has one or more employees. The cardinality is then one or more.

Data cleansing

Removing errors and inconsistencies from data before it is loaded into the Data Warehouse

Data collection

Used to describe the process of collecting data, for example, and the ultimate collection itself. For example, the collection process can be performed by a SQL query. The result of such a query is the collection itself.

Data dictionary

A database in which specifying data about data and database structures is stored.

Data directory

A database in which all information about data and database structures is stored. A catalog of all data elements, including names, structures and usage information. A central location for metadata.

Data extraction

The process of extracting data from source systems

Data hierarchy

The hierarchical relationships that arise between different data elements

Data integration

Bringing together and consolidating data from various sources into one universal source

Data Literacy

The ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied — and the ability to describe the use case, application and resulting value. (Source Gartner Feb 6, 2019)

Data management

Managing data, data collections and data flows

Data mart

Part of a data warehouse with a limited set of data from that data warehouse, tailored to the purpose of use. Intended to make data easier and faster accessible for a specific purpose or a specific user group.

Data mining

Data mining is the targeted search for (statistical) connections in large collections of data for scientific or commercial purposes. Such a collection of data can be formed by registering events in a practical situation (purchasing behavior of consumers, symptoms in patients, etc.) or by comparing and reinterpreting the results of previously conducted scientific studies. The name stems from the similarities …

Data pivot

Data pivot is the tilting of data in an OLAP environment. Often the data is moved from the horizontal axis to the vertical axis or vice versa.

Data Quality

This is to which data complies with the set requirements with regard to, for example, reliability, validity, completeness, timeliness and the extent to which the data is in accordance with the business rules.

Data repository

The place where the metadata is stored. The data repository contains all information about the data relevant to the data warehousing environment.

Data staging area

The front portal of the Data Warehouse where data is temporarily stored for processing.

Data steward

The data steward is responsible for data security specifications, data definitions, data quality requirements and the management of the business rules of a specific area of interest.

Data steward (DS)

The data steward is responsible for data security specifications, data definitions, data quality requirements and the management of the business rules of a specific area of interest.

Data Warehouse

A ‘data warehouse’ in which all kinds of data is stored in a structured way to be used for analysis and / or reporting purposes.

Data Warehouse (DWH)

A ‘data warehouse’ in which all kinds of data is stored in a structured way to be used for analysis and / or reporting purposes.

Data Warehousing

Data Warehousing is the accommodation of all kinds of data in one system, so that it is easier to analyze and report on all kinds of knowledge available within the organization. Data Warehousing is like puttin gall the cards on table like the card catalog with customers, the cash book and stock management in a warehouse so that a company …

Database

A logically structured system in which data is stored in such a way for flexible consultation and use.

Database administrator

The administrator of one or more databases. The DBA takes care of, among other things, backups, periodic clean-ups, etc. and manages the databases in the general sense of the word.

Database administrator (DBA)

The administrator of one or more databases. The DBA takes care of, among other things, backups, periodic clean-ups, etc. and manages the databases in the general sense of the word.

Database management system

A software system that provides access (save, read, change and delete) to a database.

Database management system (DBMS)

A software system that provides access (save, read, change and delete) to a database.

Datamodel

A data model (or data model or data model) describes how the data is structured in an information system.

Datamodel – Conceptual

The conceptual data model describes the structure of and the relationships between the conceptual data objects, called entities. The graphical recording of the conceptual data model is usually done in an Entity Relationship Diagram (ERD).

Datamodel – Logical

The logical data model describes the structure of and the references between the logical data objects, called tables. The conceptual model is linked to the logical model in that entities are converted into tables (or more precisely: table definitions), and relationships are converted into foreign key constraints. The logical data model can be graphically recorded in a Data Structure Diagram …

Datamodel – Physical

The physical data model describes the way data is stored in an individual database. The connection between the logical and the physical data model is established by converting the logical data objects into database definition instructions in accordance with a particular Data Definition Language (DDL). After execution of the DDL on a physical database, the definitions of the database objects …

De-normalization

In a relational scheme, the data must be stored as uniquely as possible. In a Data Warehouse the opposite is the case. It is important for the performance of the Data Warehouse that the fact tables are not normalized.

Degenerated dimension

A degenerate dimension is a dimension that is included in the fact table. It is a virtual dimension, without its own physical dimensional table. It does not refer to a dimension and is not a measure. Example: order number. All sales are linked to order number. There are several order lines on 1 order. Via order you can find all …

Deming Cycle

The Deming circle shows that four types of activities are needed in a company: Plan: Consider in advance which products or services will be delivered, and how they should be made. This activity is therefore an important part of that described above in organizing. Do: Execute what has been devised in Plan (cooperate carefully). Check: Check regularly whether what was …

Dense

Term used to describe ‘information density’. This means the extent to which a collection of data contains relevant data. Dense means a high ‘information density’ Opposite of ‘sparse’.

Dimension

A dimension is a structural attribute that consists of a list of members that, in the perception of users, are of the same type. For example months, days, years, hours, etc. are part of the dimension ‘time’. Countries, cities, streets, etc. are part of the ‘geography’ dimension. A dimension serves as an index to identify values within a multi-dimensional array. …

Dimension outrigger

A ‘second level’ dimension table that further defines and gives meaning to the multi-dimensional model. Sometimes you have a date in a dimension, where you would like the functionality of a full date dimension, such as a customer acquisition date. It is then allowed to establish a relationship between the date attribute and the date dimension. This is a form …

Drill anywhere

The ability to drill (click through) anywhere within reporting and analysis environments, without being bound to predefined drill paths.

Drill down

The ability to drill (click through) to the data in underlying levels within reporting and analysis environments.

Drill through

The possibility to drill (click through) from one reporting or analysis environment to another reporting or analysis environment. The starting point is that the starting point in the other environment is determined on the basis of the starting point.

Drill up

The possibility to drill (click through) to the data in higher levels within reporting and analysis environments.

Due Diligence

The English term due diligence literally means due care. In mergers and acquisitions and in accountancy, however, there is a specific meaning, namely due diligence, for example in the case of a company takeover. A due diligence investigation provides a good picture of the company. The due diligence report describes the strengths and weaknesses of the company and formulates points …

Dynamic query

Dynamically constructed SQL that is not predefined and is compiled and executed in runtime. Often created by and / or with the help of query tools on the desktop.