Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence by Shrawan Kumar Trivedi Shubhamoy Dey Anil Kumar Tapan Kumar Panda

Author:Shrawan Kumar Trivedi,Shubhamoy Dey,Anil Kumar,Tapan Kumar Panda
Language: eng
Format: epub
Publisher: IGI Global

BI Needs Joint Working of Business and IT

A successful BI approach for an organization which is aiming to adopt BI analytics in a big way, must involve joint working of people having the three skill sets described earlier, which are, business insight, data science and Information Technology Skills. Based on a vision of end objectives outlined by the organization, the first step is performed by IT and Data scientists who together design and build the right data warehouse architecture, select the right technology and provision requisite IT infrastructure. The decision on what data sources to use and what target information pattern for decision making to be used will have to be advised by the business users. Such business users must have a deep functional understanding and have foresight to visualize the type of insights business would need in the future. Once the initial structure of data warehouse is ready, the task is handed over to IT professionals who set up and maintain the IT environments, tools, populate the data warehouse, take regular back up of data, run batch jobs to update data warehouse on day to day basis. Summarization and population of data warehouse also needs joint working between all the three-skilled people. One the data warehouse (or data mart) is up and running, all business users who are trained in the access of data using BI tools are allowed use the BI environment and seek necessary reports.

But it is not fair to assume that from day one all business users would be proficient in using BI tools and would be able to get all reports required by them easily. There will be a learning process involved here. Let us take an example of building a behavior model of a customer with an objective of offering him a suitable product. The process starts with Business analyst making a hypothesis. Hypothesis will involve linking a behavior to a profile (Age, economic status, location…etc). This needs to be tested using analytics tools. If the test shows positive correlation, then the analysis will be implemented across larger set of data and sales team will reach out to such identified customers to drive sale based on these inputs on a regular basis.

In many cases, such as credit card fraud or suggesting product in online buying etc. BI tools must react very fast. Such analysis and pattern recognition has to happen on a real-time basis for quick action to prevent a financial fraud as in the case of bank. Similarly, a suggested product based on the customer profile must pop up on the customer screen before he/she leave the e commerce site. In both cases the BI system must have a sub second response and automated action must take place without any manual intervention. The technology platform required for such analysis needs to be very different.

BI and Organization

It is important at this stage to understand the impact of BI tools and technology on any organization. In the fiercely competitive globalized business environment of current times,

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