Question

The data warehouse is one of the most important business intelligence tools a business needs to have. It turns the massive amount of data generated from multiple sources into a format that is easy to understand.

Discuss the data warehouse concept?

Answer 1

Data warehousing is defined as a technique for collecting and managing data from various sources to provide meaningful business related inferences.  Data warehouse generalizes and consolidates data in multidimensional space.
Data warehouse system is also known as Decision Support System , Executive Information System ,Management Information System, Business Intelligence Solution and Analytic Application.
The construction of data warehouses involves data cleaning, data integration, and data transformation, and can be viewed as an important preprocessing step for data mining.
Data warehouse systems allow for integration of a variety of application systems. They support information processing by providing a solid platform
of consolidated historic data for analysis.
A data warehouse stores the information an enterprise needs to make strategic decisions.

Data Warehouse Models:
1. Enterprise Warehouse: An enterprise warehouse collects all of the information about
subjects spanning the entire organization or enterprise.
2. Data mart: A data mart contains a subset of enterprise data that is of importance to a
particular group of users. The scope is confined to specific selected subjects.
3. Virtual warehouse: A virtual warehouse is a set of views as per user need over operational databases.

Data warehousing process involves:
1. Data extraction: collecting and gathering raw data from varoius sources internal or external
2. Data cleaning: cleaning the raw data of errors, outliers, missing values,etc.
3. Data transformation: converting the data from one form to another as per required for business.
4. Data loading: sorting and summarizing data
5. Refreshing the data, updating it at frequent time intervals.

Metadata(data about data) are the data that define warehouse objects. A metadata repository should contain the following:
1.Description of the data warehouse structure.
2. Operational metadata, containing history of the data extraction and operations performed on it.
3. Algorithms used for summarization of the data.
4. Mapping from the operational environment to the data warehouse.
5. Business metadata relating information of data used for business purpose.

Components of Data warehousing:  
1. Load Manager : also called as the front component. Deals with extraction and loading of data into warehouse.
2. Warehouse Manager : manages the data like updation, transformation, merging, backing up data etc.
3. Query Manager : A backend component manages queries regarding the data.
4. End user access tools: Tools related to data reporting, query tools, application development, EIS and OLAP and data mining tools. are maintained here.

Data warehousing is used in banking, airline, healthcare, public sector, investment and insurance sector, telecommunication and hospitality industry, etc.