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Data warehousing Concepts J.Srinivasa Reddy Page # 1 Data Warehousing Concepts Introduction In today’s competitive global business environment, understanding and managing enterprise wide information is crucial for making timely decisions and responding to changing business conditions. There is a tremendous amount of data generated by day- to-day business operati onal applicatio ns. In addition there is valuable data available from external sources such as market research organizations, independent surveys and quality testing labs. Operation al Data Operational data is the data you use to run your business. This data is what is typically stored, retrieved, and updated by your Online Transactional Processing (OLTP) system. An OLTP system may be, for example, a reservations system, an accounting application, or an order entry application. Informat ional Data Informational data is created from the wealth of operational data that exists in your business and some external data useful to analyze your business. Informational data is what makes up a data warehouse. Informational data is typically: Summarize d operational data Infrequently updated from the operational systems Optimized for decision support applications Possibly "read only" (no updates allowed) Based on the way the data is used, database can be classified in to two ways: the one that is used for transactions Online Transaction Processing (OLTP) and the one that is used for analysis Online Analytical Process (OLAP). As the business these days contain huge amounts of data and the users are connected to these databases across the globe and round the clock the necessity for maintaining a separate database for the sake of analysis is very much clear. OLTP Database s OLTP Databases are what we generally refer as “Databases”. These are the databases that contain information of day-to-day transactions. Typically OLTP database has hundreds of users connected to it and performing transactions round the clock. Most of the time these transactions insert data in to the database. Example : ATM Machine , Online Shopping, Online Application Filing, Online Railway Reservation.. The ratio of number of records being inserted is more than the number of records being updated or deleted. Hence these databases or optimized for insertions. These databases are normalized to reduce the redundancy of the data and increase performance while inserting the data.

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