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Introduction to Data Warehouse

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Introduction to Data Warehouse
Introduction to Data Warehouse

Introduction to Data Warehouse

A data warehouse is a relational database that is designed for query and analysis rather than for transaction processing. It usually contains historical data derived from transaction data, but it can include data from other sources.

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. These technologies help executives to use the warehouse quickly and effectively. They can gather data, analyze it, and take decisions based on the information present in the warehouse. The information gathered in a warehouse can be used in any of the following domains

1. Tuning Production Strategies: The product strategies can be well tuned by repositioning the products and managing the product portfolios by comparing the sales quarterly or yearly.

2. Customer Analysis: Customer analysis is done by analysing the customer’s buying preferences, buying time, budget cycle etc.

3. Operations Analysis: Data Warehousing also helps in customer relationship management, and making environment corrections. The Information also allows us to analyse business operations.

Application of Data Warehouse

1. Information Processing: Quiring, basic statistical analysis and reporting using crosstabs, table, charts or graphs. A current trend in data warehouse information processing is to construct low cost web based accessing tools that are then integrated with web browsers.

2. Analytical Processing: A data warehouse is often used as the basis for a decision support system. Data can be analysed by means of basic OLAP operations, including slice and dice, drill-down. It generally operates on historical data in both summarized and detailed forms.

3. Data Mining: It is also called knowledge discovery. There are two main kinds of models is data mining. One is predictive models and another one is descriptive models.

 

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