Overview of Data Warehousing

Monday, January 25, 2010

A data warehousing is a process to transform one data source to structure conductive to business analysis. Mathematical calculations are also performed on the newly created organized data to make usefulness for making business decisions. Finally, the data is available for user for analysis.
A well architecture data warehouse can return query results very quickly.
There are two types of Data Analysis.
1. OLAP
2. Data Mining
Data Warehouse is a collection of decision support technologies aimed at enabling the knowledge worker (executive, manager, and analyst) to make better and faster decisions.
OLTP Database
• An OLTP database is a transaction-based and normalized to reduce the amount of redundant data storage generated.
• Results in fast update.
• For speed of information retrieval, especially for the purpose of business analytics, an OLAP database is called for.

OLAP Database
• An OLAP database is highly de-normalized and therefore has rows of data that may be redundant.
•This makes for very fast query responses because relatively few joins are involved.
• Fast responses are what we want while doing business intelligence work.
• Data Marts – Mini data warehouses and quite often act as part of a larger warehouse.
Data Marts are subject-oriented data stores for cleaned data
•E.g. Sales data mart, an inventory data mart, or any subject rooted at the departmental level.
• A Data Warehouse functions at the enterprise level and typically handles data across the entire organization.