What are the data modeling techniques for DW?How ?

Information processing, analytical processing, and data mining are the three types of data warehouse applications that are discussed below:

• Information Processing - A data warehouse allows to process the data stored in it. The data can be processed by means of querying, basic statistical analysis, reporting using crosstabs, tables, charts, or graphs.

• Analytical Processing - A data warehouse supports analytical processing of the information stored in it. The data can be analyzed by means of basic OLAP operations, including slice-and-dice, drill down, drill up, and pivoting.

• Data Mining - Data mining supports knowledge discovery by finding hidden patterns and associations, constructing analytical models, performing classification and prediction. These mining results can be presented using the visualization tools.

• http://www.tutorialspoint.com/dwh/dwh_quick_guide.htm

Evolution in organization use

These terms refer to the level of sophistication of a data warehouse:

Offline operational data warehouse

Data warehouses in this stage of evolution are updated on a regular time cycle (usually daily, weekly or monthly) from the operational systems and the data is stored in an integrated reporting-oriented data

Offline data warehouse

Data warehouses at this stage are updated from data in the operational systems on a regular basis and the data warehouse data are stored in a data structure designed to facilitate reporting.

On time data warehouse

Online Integrated Data Warehousing represent the real time Data warehouses stage data in the warehouse is updated for every transaction performed on the source data

Integrated data warehouse

These data warehouses assemble data from different areas of business, so users can look up the information they need across other systems.

https://en.wikipedia.org/wiki/Data_warehouse

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