Common terms in Datawarehousing.

I have been interested in datawarehousing concepts for a long time, but unfortunately never got a chance to work on them. Here are some common concepts U need to know to understand any datawarehousing glibber.

Data Warehousing: An enterprise-wide implementation that replicates data from the same publication table on different servers/platforms to a single subscription table. This implementation effectively consolidates data from multiple sources.

Data Warehouse: A data warehouse is a subject oriented, integrated, non volatile, time variant collection of data. The data warehouse contains atomic level data and summarized data specifically structured for querying and reporting.

Data Mining: The process of finding hidden patterns and relationships in data. For instance, a consumer goods company may track 200 variables about each consumer. There are scores of possible relationships among the 200 variables. Data mining tools will identify the significant relationships.

OLAP (On-Line Analytical Processing)
Describes the systems used not for application delivery, but for analyzing the business, e.g., sales forecasting, market trends analysis, etc. These systems are also more conducive to heuristic reporting and often involves multidimensional data analysis capabilities.

OLTP (OnLine Transaction Processing)
Describes the activities and systems associated with a company's day-to-day operational processing and data (order entry, invoicing, general ledger, etc.).

Data Dictionary:
a software tool for recording the definition of data, the relationship of one category of data to another, the attributes and keys of groups of data, and so forth.