Database glossary: provided by Canadian Marketing Association

Print Action, Apr 2003

Ad-Hoc Reporting: The ability to access information from a database to meet information requirements as required. One-off requests not satisfied by pre-set reporting.

Agent: An application that searches the data and sends an alert when a particular pattern is found.

Aggregations: Information stored in a data warehouse in a summarized form. Instead of recording the date and time a certain product is sold, the data warehouse could store the quantity of the product sold each hour, each day, or each week. Aggregations are used to save storage space and to improve the performance of business intelligence tools.

Alert: A message that is sent automatically by a computer system when a certain situation occurs.

Application: A piece of software designed to meet a specific purpose.

Attribute: A single data item related to a database object. The database schema associates one or more attributes with each database entity. Also known as: field, column.

Business Intelligence Tools: Software that enables business users to see and use large amounts of complex data.

Candidate Key: A combination of attributes that can be uniquely used to identify a database record. Each table may have one or more candidate keys. One of these candidate keys is selected as the table primary key.

Cardinality: In set theory, cardinality refers to the number of members in the set. When specifically applied to database theory, the cardinality of a table refers to the number of rows (or tuples) contained in a table.

Clickstream Data: Data regarding Web browsing.

Client/Server Architecture: A type of network in which computer processing is distributed among many individual PCs (clients) and a more powerful, central computer (server). Clients can share files and retrieve data stored on the server.

Data: A series of facts or statements that may have been collected, stored, processed and/or manipulated but have not been organized or placed into context. When data is organized, it becomes information. Information can be processed and used to draw generalized conclusions or knowledge.

Database: A collection of tables. It also often includes forms for entering data, rules for checking and validating data that has been entered, and the format for creating informative reports from the data in the database.

Data Cleansing: The process of manipulating stored data to make it more aligned. Implies eliminating duplication, correcting spelling and removing null fields.

Data-based Knowledge: Knowledge derived from data through the use of business intelligence tools and the process of data warehousing.

Data Mart: Also known as local data warehouse or datamart. A database that has the same characteristics as a data warehouse, but is usually smaller and is focused on the data for one division or one workgroup within an enterprise.

Data Migration: The process of physically transmitting data from one environment to another.

Data Mining: The use of automated data analysis techniques to uncover previously undetected relationships among data items. Data mining often involves the analysis of data stored in a data warehouse. Three of the major data mining techniques are regression, classification and clustering.

Data Model: The description of the contents of a database. It includes tables and the relationship between them.

Data Quality: The suitability of data for different requirements. When constructing and populating a database the data quality must be checked to ensure that it meets the needs of all the applications.

Data Scrubbing: Removing errors and inconsistencies from data being imported into a data warehouse.

Data Transformation: The modification of data as it is moved into the data warehouse.

Data Warehouse: A data warehouse is a centralized database that captures information from various parts of an organization's business processes. This information can later be analyzed to determine predictive relationships through the use of data mining techniques.

Data Warehousing Management: The on-going supervision of the data warehousing process.

Database Management System (DBMS): The software that is used to store, access and manage data.

Decision Support System (DSS): A computer system designed to assist an organization in making decisions.

Dimension: The separation of data according to different view. A logical designation of related information that applies a hierarchy for access and reporting.

Domain: The set of all allowable values that an attribute may assume.

Drill Down and Drill Up: The ability to move between levels of the hierarchy when viewing data with an OLAP browser.

i) Drill Down - Changing the view of the data to a greater level of detail.

ii) Drill Up - Changing the view of the data to a higher level of aggregation.

Enterprise Resource Planning: An integrated system of operation applications combining logistics, production, distribution, contract and order management, sales forecasting, and financial and HR management.

Entity: A single object about which data can be stored. It is the subject of a table. Entities and their interrelationships are modeled through the use of entity-relationship diagrams.