Bi And Big Dat The Transformation Of Raw Data Into Meaningful And Useful Information For Business Analysis

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BI and Big Data


As Wikipedia’s explanation, Business intelligence (BI) is the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes. It is a solution package, to integrate all the existing data of organizations efficiently, provide accurate report to support high level managers to make business strategic decision. BI is not a new concept, it was introduced in 1996 for the first time. As the development of BI is the ETL technologies, ETL stands for Extraction Transformation Loading. Data integration platforms focus on extracting and transforming various business data, to support the requirement of Business intelligence, Data Warehouse against the data
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Trace back to 1865. Cyclopaedia of Commercial and Business Anecdotes, a Richard Millar Devens’ work, contains the first known usage of the term “Business Intelligence”. He uses this word to describe Sir Henry Furnese, a banker, succeeded: he had an understanding of political issues, instabilities, and the market before his competitors.

Hans Peter Luhn, an IBM computer scientist published a landmark article, A Business Intelligence System. In that book Mr Luhn defined Business Analytics, “The ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal”. Essentially, he point to the core of what BI is: “a way to quickly and easily understand huge amounts of information data so that the best possible decisions can be made. Luhn did more than introduce and expand the possibilities of a new concept.
Based on his work IBM established its first analytical systems.

1970,Edgar Codd, an IBM researcher invented the Relational Database. Based on it, the software developer got more freedom to develop new complex system. Also in 1970s, MIT researchers first pretended that strategic decision support system and transactional system should be separated. Which means the decision support system should be designed by separate data storage method.

1983, Teradata built the first decision support system for Wells Fargo Bank by parallel processing technology. Then in

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