Course in Business Intelligence Tools and Techniques I
Course
In Kolkata
Price on request
Description
-
Type
Course
-
Location
Kolkata
Facilities
Location
Start date
Kolkata
(West Bengal)
See map
INDIAN INSTITUTE OF MANAGEMENT CALCUTTA Diamond Harbour Road Joka, 700104
Start date
On request
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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.
Course Objectives
Course Content
1. MIS: Basic Ideas
2. Database preliminaries
3. Data Warehouse: Data Warehousing Process: Data Extraction, Cleaning and Transforming, Data-warehousing and OLAP, Data Cube, Multi-Dimensional Data, Data Mart, Meta Data, Design of Data-warehouse and Business Analysis Framework
4. Data warehouse to Data mining
5. Association Rule Mining: Frequent Pattern Mining, Frequent pattern analysis, Apriori Algorithm, FP Tree, FP Growth Algorithm
6. Classification vs. Prediction: Classification methods - Decision Tree, Bayesian, Rule Based, kNN, Soft-computing techniques (ANN - Perceptron and Backprop, Fuzzy, GA), Regression
7. Cluster Analysis: Similarity metrices, Clustering Algorithms: k-means, k-medoid and PAM, Hierarchical, Density based.
8. Stream Data Mining
9. Text Mining
Cases:
1. Diamonds in the Data Mine
2. Continental Airlines Flies High with Real Time Business Intelligence
3. Distractions and Motor Vehicle Accidents: Data Mining Application on Fatality Analysis Reporting System (FARS) Data Files
Evaluation:
Quizzes, Assignements and Presentations: 30%
End-Term: 40%
Group Project: 30%
Course Objectives
Course Content
1. MIS: Basic Ideas
2. Database preliminaries
3. Data Warehouse: Data Warehousing Process: Data Extraction, Cleaning and Transforming, Data-warehousing and OLAP, Data Cube, Multi-Dimensional Data, Data Mart, Meta Data, Design of Data-warehouse and Business Analysis Framework
4. Data warehouse to Data mining
5. Association Rule Mining: Frequent Pattern Mining, Frequent pattern analysis, Apriori Algorithm, FP Tree, FP Growth Algorithm
6. Classification vs. Prediction: Classification methods - Decision Tree, Bayesian, Rule Based, kNN, Soft-computing techniques (ANN - Perceptron and Backprop, Fuzzy, GA), Regression
7. Cluster Analysis: Similarity metrices, Clustering Algorithms: k-means, k-medoid and PAM, Hierarchical, Density based.
8. Stream Data Mining
9. Text Mining
Cases:
1. Diamonds in the Data Mine
2. Continental Airlines Flies High with Real Time Business Intelligence
3. Distractions and Motor Vehicle Accidents: Data Mining Application on Fatality Analysis Reporting System (FARS) Data Files
Evaluation:
Quizzes, Assignements and Presentations: 30%
End-Term: 40%
Group Project: 30%
Course in Business Intelligence Tools and Techniques I
Price on request