Data Mart - Data Marts are developed to support a single business function or process. Data Marts usually include a subset of the organization's data and are focused on a specific subject area or business area. The data mart is typically summarized and aggregated.

Data Warehouse (DW) - A collection of data pulled together primarily from operational systems and specifically structured and tuned for easy access and use for query, reporting and analysis purposes. The Data Warehouse may contain historical data, as well as transformed transactional data, aggregated data and derived/calculated data. The data in a DW are typically subjected, oriented and time varying with changes happening in a controlled form.

Executive Information System (EIS) - A concise set of customized, high-level, generally graphical views of the organization's information, enabling executive-level management to see the overall health of their business.

Extract, Transform and Load (ETL) -Technology components and processes that deal with the processing and movement of operational data to prepare it for storage in Data Warehouse and Data Mart type repositories, or to share it with other analytical applications and systems.

• Extract - The technology and process by which selected data from the Source systems is accessed and extracted. Extraction technology can be composed of an engine; change data capture tools, or independent programs/modules. Mappings are used to map source data to a target data structure. Data can be extracted in full or in increments based on data that has changed since the last extract.
• Transform - The technology and process by which previously-extracted data is integrated with other relevant data elements and structures, processed with defined business information rules, and used to derive, calculate, and store value-added information closely tied to the business objectives in the Information on Demand environment. Mappings are further extended to capture source-to-target data transformation rules.
• Load - The technology and process related to moving information that has been processed by the extraction, transformation and integrity/quality systems. This component may use special technology or tools to provide high-performance data loading and volume loading, which is typically a batch scheduled process. Near real-time data loading may also be accomplished through the use of asynchronous message queues.

Metadata - Metadata includes any information that is captured and maintained with the purpose of supporting the development, administration and usage/navigation of the Business Intelligence Environment.

Online Analytical Processing (OLAP) - A category of applications and technologies for collecting, managing, processing and presenting multidimensional data for analysis and management purposes.

Relational Database Management System (RDBMS) - RDBMS is a type of database management system (DBMS) that stores data in the form of related tables and relationships between such tables. In RDBMS tables are collections of records, and each record in a table contains the same attributes. Records in different tables may be linked if they have the same value in one particular attribute in each table.

Structured Query Language (SQL) -The query language standardized in 1986 by the American National Standards Institute (ANSI) and used to request information from tables in a relational database and to manipulate table structure and data.

Star Schema - A relational database schema for representing multidimensional data. A star schema is a set of tables comprised of a central fact table surrounded by de-normalized dimensions.