Course in Business Data Mining

Indian Institute of Management Calcutta
In Kolkata

Price on request
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Important information

  • Course
  • Kolkata

Important information

Where and when

Starts Location
On request
INDIAN INSTITUTE OF MANAGEMENT CALCUTTA Diamond Harbour Road Joka, 700104, West Bengal, India
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Course programme

At IIM-C we firmly believe that information is power. In the years to come the need for increased sharing of information will govern the changes in organizational structure. A basic understanding of information systems is thus mandatory. We endeavor to ensure that you drive the e-commerce revolution. These courses not only equip you with software tools but also impart an understanding of the hardware which will help you set design your own database. It's time you started your own dotcom at IIMC.


Today, for sustainable competitive advantage, organisations need to make better business decisions faster. Organisation with managers who can make correct and timely decisions wins. But how to ensure managers make the best decisions? Computerized database systems are in use in organizations for decades to ensure efficient and consistent handling of data and to answer routine queries on the underlying data. Such traditional database systems are mostly transaction-oriented. For quick and effective decision making, employees require to study and analyse not only its own transaction data available at its various units but also many other data sources elsewhere which may be related to its business interests. This data load offers new challenges and opportunities as it is no longer easy to foresee, let alone retrieve, the summary information a manager may want from an ocean of data.

Intelligent navigation through data sources may unearth unanticipated new knowledge enabling better handling of business logistics and discovery of new opportunities. For an example, a traditional transaction oriented database for a superstore would keep track of physical coordinates of items for sale and maintain detailed inventory information. An intelligent data mining analysis, in contrast, may reveal that those who buy milk at a visit to a store also buy bread with a high probability and this finding would pave ways for a more efficient way of keeping bread and milk at adjacent rather than far-apart racks. Analyzing past history of sales, customers can be classified according to their buying patterns and this may lead to an effective customer relationship management and help in direct marketing. Decisions on launching new products not only depends on market research but also on the mining the data on sales of various products. Past data driven decision making is expected to take a significant role in near future.

Extracting useful information from such huge data sources and summarizing it in a desirable form for decision support is another big challenge. For an example, a superstore may have several branches spread over various cities of a country or perhaps a number of countries. The sales pattern might depend on economic, cultural, climatic, and many other dimensions. Data warehousing addresses issues related to filtering and representation of huge volumes of data towards these ends. It remains a big challenge how a data warehouse should be modeled and maintained so that the desired analysis on various dimensions can be performed to aid decision making of managers.

In summary, innovative applications, typically studied under the banner of Data Mining and Data Warehousing, are becoming increasingly important in the management of modern organizations. Modern managers will find it useful to keep abreast of the potentials, limitations, and issues related to these emerging areas in their decision making process.

Course Objective:

The course is aimed at helping students understand and appreciate the role of Data Mining for Business decisions and also the use of Data Warehousing for decision support in the broader context of making organizations smarter and intelligent in decision making.


Classroom Lectures, Group Projects and Presentations.

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