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A data warehouse is a repository of data structured into relationships between data domains that provide an enterprise view of data.Usage:Data warehouses are used to provide business intelligence in either the form of reports, dashboards, or visualizations. Data Warehouses can also be used as a data hub in which applications either sit on top of the warehouse or use extracts of data from the warehouse.Components (This will answer the data stage portion of the question):Data model - logical and physical design of the warehouse (key to the success and usage of the warehouse)Database - software & hardware storing the dataIntegration - Usually referred to as ETL or ELT (or some combination of those three letters). ETL is short for Extract, Transform, and Load. This is the extraction of data from a source system, transforming the data to meet the target data model and usage, and loading the data into the datawarehouse. Data Stage is an integration tool, used in this space to perform the ETL for a data warehouse. It is essentially the data API into the warehouse.User Interface - usually a business intelligence reporting tool, such as Cognos or Microstrategy. It could, however, be simply a SQL assistant tool or command line allowing SQL to be executed on the database.
Data warehouse is the historical data collected/extracted from various sources and transformed the data into required format and loaded into the warehouse database for the purpose of analysis and reporting.
Cognos, informatica are the tools of BI.
To answer your question i would say,Data Warehouse is the method to store,analyze , and mine the data that may come from different sources like data from some business organization.Let say, your company produces some products and you want to know ,which product is going to be more demandable for the next month.So first you need to collect the data from the market review and store them in proper manner and you may need to analyze whether if there have any outlier ,noise hidden pattern,redundancy among the data sets and possibility of dimensionality reduction for the data set you have collected .And then you can use mining technique like regression model,classification model etc.to predict the future of your products.Data Warehouse subject deal with all of those purposes.
As a data storage tool you can use Oracle or My SQL, or MS-EXCEL etc .
A data warehouse is a federated repository for all the data that an enterprise's various business systems collect. The repository may be physical or logical.
Data warehousing emphasizes the capture of data from diverse sources for useful analysis and access, but does not generally start from the point-of-view of the end user who may need access to specialized, sometimes local databases. The latter idea is known as the data mart.
There are two approaches to data warehousing, top down and bottom up. The top down approach spins off data marts for specific groups of users after the complete data warehouse has been created. The bottom up approach builds the data marts first and then combines them into a single, all-encompassing data warehouse.
Typically, a data warehouse is housed on an enterprise mainframe server or increasingly, in the cloud. Data from various online transaction processing (OLTP) applications and other sources is selectively extracted for use by analytical applications and user queries
enterprise's various business systems collect. for its future analysis
Sorry brother i am not the right person to answer.
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