Data Warehousing and Mining
Unit I: Introduction
Why Data Mining?, What Is Data Mining? , What Kinds of Data Can Be Mined? What Kinds of Patterns Can Be Mined? Which Technologies Are Used? , Which Kinds of Applications Are Targeted? , Major Issues in Data Mining.
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Unit II: Getting to Know Your Data
Data Objects and Attribute Types, Basic Statistical Descriptions of Data, Data Visualization, Measuring Data Similarity and Dissimilarity
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Unit III: Data Preprocessing:
Data Preprocessing: An Overview , Data Cleaning , Data Integration , Data Reduction , Data Transformation and Data Discretization.
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Unit IV: Data Warehousing and Online Analytical Processing
Data Warehousing and Online Analytical Processing: Data Warehouse: Basic Concepts, Data Warehouse Modeling: Data Cube and OLAP, Data Warehouse Design and Usage, Data Warehouse Implementation, Data Generalization by Attribute-Oriented Induction
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Unit V: Data Cube Technology
Data Cube Computation: Preliminary Concepts, Data Cube Computation Methods, Processing Advanced Kinds of Queries by Exploring Cube Technology, Multidimensional Data Analysis in Cube Space.
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Unit VI: Mining Frequent Patterns, Associations, and Correlations :
Basic Concepts and Methods: Basic Concepts , Frequent Itemset Mining Methods , Which Patterns Are Interesting?- Pattern Evaluation Methods
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Text Book:
Reference Books:
- Data Mining Techniques, Arun K Pujari, 3rd edition, Orient Blackswan/Universities Press, 2013.
- Data Warehousing Fundamentals, PaulrajPonnaiah, John Wiley & Sons, 2001.
- Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach and Vipin Kumar, Pearson Education, 2007
- Insight into Data mining Theory and Practice, K.P. Soman, Shyam Diwakar and V. Ajay, Easter Economy Edition, Prentice Hall of India, 2006.
- G. K. Gupta, “Introduction to Data Mining with Case Studies”, Easter Economy Edition, Prentice Hall of India, 2006
Also check: Cloud Computing Syllabus