The collective processes of storage configuration, optimization and administration including backup and recovery and business continuance.

The “shared nothing” approach of parallel computing.

1. A particular technique or technology for delivering a function. Examples might be a telephone, a computer, or an electronic mail service.

2. Resources that enable or facilitate the step/sequence in a test scenario.

The process of compiling multiple data records, retaining the desired data, and removing unwanted data. This process may be invoked during the data acquisition process.

Also known as data about data is the information about the contents and uses of the data warehouse. Meta data is created by several components of the data warehouse and provides a business and technical view of the data warehouse solution.

The process of consolidating, relating, and synchronizing data elements with the same or similar meaning from different systems. Metadata synchronization joins these differing elements together in the data warehouse to allow for easier access.

A database that contains the common metadata and client-friendly search routines to help people fully understand and utilize the data resource. It contains common metadata about the data resource in a single organization or an integrated data resource that crosses multiple disciplines and multiple jurisdictions. It contains a history of the data resource, what the data initially represented, and what they represent now.

A structured organization of tasks, estimates, and guidelines that provide a systematic approach or discipline.

A system of principles, practices, and procedures applied to a specific branch of knowledge.

A measured value. For example, total sales is a metric.

A communications layer that allows applications to interact across hardware and network environments.

A small subset of a data warehouse used by a small number of users. A mini mart is a very focused slice of a larger data warehouse.

Millions of Instructions Per Second – a measure of computer processing capacity.

A logical program unit. Examples include: forms, reports, user exits, C programs, PL/SQL procedures, and database triggers.

Multidimensional OLAP. MOLAP systems store data in the multidimensional cubes.

Informational Analysis on data which takes into account many different relationships, each of which represents a dimension. For example, a retail analyst may want to understand the relationships among sales by region, by quarter, by demographic distribution (income, education level, gender), by product. Multi-dimensional analysis will yield results for these complex relationships.

A database management system in which data can be viewed and manipulated in multiple dimensions. Data is stored using multidimensional structures and is organized to support analytical operations such as drill-down, consolidation, slicing, and dicing.

See multiple dimension processing.

On-line analytical processing for decision support that uses a combination of single dimension and multiple dimension data subjects. It is also referred to as static data analysis because the data values do not change. It is also known as multiple dimensional analysis.