RE: what is the difference between Datawarehousing and...
Data warehousing deals with all aspects of managing the development, implementation and operation of a data warehouse or data mart including meta data management, data acquisition, data cleansing, data transformation, storage management, data distribution, data archiving, operational reporting, analytical reporting, security management, backup/recovery planning, etc. Business intelligence, on the other hand, is a set of software tools that enable an organization to analyze measurable aspects of their business such as sales performance, profitability, operational efficiency, effectiveness of marketing campaigns, market penetration among certain customer groups, cost trends, anomalies and exceptions, etc. Typically, the term “business intelligence” is used to encompass OLAP, data visualization, data mining and query/reporting tools.Think of the data warehouse as the back office and business intelligence as the entire business including the back office. The business needs the back office on which to function, but the back office without a business to support, makes no sense.
RE: what is the difference between Datawarehousing and...
Hi friends
Dataware house is a relational database and it design analysis and transformation processing.Â
Datawarehousing is a subject oriented, integrated, timevarient and nonvolatile collection of the data, the support and management of the decision making process.
Business Intelligence is collection of datawarehousing, datamart and knoweledge.
RE: what is the difference between Datawarehousing and...
Business Intelligence: BI is a broad cateogry of applications and technologies for gathering, integrating, storing, analysing and providing access to data to help enterprise users make better business decisions. BI Applications includes the activities of decisions support systems, query and reporting, online analytical processing, statistical analysis, forecasting and Data Mining.
Datawareshousing:
Datawarehousing is a process of dimensional modeling by Extraction, Clean, Conform and Delivering to build Dataware houses which are subject oriented, time variant, non volatile.
Regards, Ravi Kumar Garre ravi_kumar_garre@yahoo.co.in
