A data warehouse is a record of an enterprise's past transactional and operational activities, stored in a database. The database design favours data analysis and reporting in order to gain strategic insight and to facilitate decision making. Data warehouses are not used for current, "live" data.
Data warehouses often hold large amounts of information which are sometimes subdivided into smaller logical units called dependent data marts.
Periodically, one imports data from enterprise resource planning (ERP) systems and other related business software systems into the data warehouse for further processing. It is common practice to "stage" data prior to merging it into a data warehouse. In this sense, to "stage data" means to queue it for preprocessing, usually with an ETL tool. The preprocessing program reads the staged data (often a business's primary OLTP databases), performs qualitative preprocessing or filtering (including denormalization, if deemed necessary), and writes it into the warehouse.
Online analytical processing (OLAP) is a mode of computational analysis often used in data warehouses; conversely, online transaction processing (OLTP) is more suitable for current, normal business operations.
DataWarehousing is a field that has grown out of the integration of a number of different technologies and experiences over the last two decades.
Data Staging is also called copy management or replication management, but in fact, it includes all of the processes necessary to select, edit, summarize, combine and load data warehouse and information access data from operational and/or external databases.
The scope of a data warehouse may be as broad as all the informationaldata for the entire enterprise from the beginning of time, or it may be as narrow as a personal data warehouse for a single manager for a single year.
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