Syllabus
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Course Code: IT-401 Course Name: Specialisation – E: INFORMATION TECHNOLOGY - Data Mining for Business Decisions |
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| MODULE NO / UNIT | COURSE SYLLABUS CONTENTS OF MODULE | NOTES |
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| 1 | Introduction to data mining (DM): Kind of data, DM Functionalities, Classification of DM Systems, Issues in DM. Business Analytics at Data Warehouse Level, designing physical database, Deploying and supporting DW/BI system Multidimensional data model: Data cubes, Stars, snowflakes and fact constellations, Defining schemas, concept hierarchies, OLAP, Types of OLAP servers: ROLAP versus MOLAP versus HOLAP, Steps for design and construction, Three-tier Data Data Preprocessing, Why to preprocess data? Data cleaning: Missing values, Noisy data, Data Integration and transformation, Data Reduction: Data cube aggregation, Dimensionality reduction, Data Compression, Numerosirty, Reduction Discretization and concept hierarchy Generation. Data Mining Primitives, Languages and System Architectures: Task relevant data, Kind of Knowledge to be mined, DM Query languages: Syntax, Designing GUI, Architectures of DM Systems, Concept of Cluster Analysis. , Application and trends in Data mining, Data Mining for Financial data analysis, Data Mining for retail industry, Data mining for telecommunication industry |
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