IT6702 Data Warehousing and Data Mining Syllabus Notes Question Papers Question Bank with answers

IT6702 Data Warehousing and Data Mining Syllabus Notes Question Papers 2 Marks with Answers Question Bank with answers Anna University IT6702 DWDM Notes Syllabus 2 Marks with answers Part A Part B Problems Anna University IT 7th Semester - Regulation 2013 7th Semester Syllabus Notes

Anna University IT6702 Data Ware Housing and Data Mining Notes Syllabus 2 marks with answers Part A Question Bank with answers

Anna University IT6702 Data Ware Housing and Data Mining Syllabus Notes 2 marks with answer is provided below. IT6702 Notes Syllabus all 5 units notes are uploaded here. here IT6701 DWDM Syllabus notes download link is provided and students can download the IT6702 Syllabus and Lecture Notes and can make use of it.

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Click below link to download IT6702 Data Ware Housing and Data Mining Study Materials .

IT6702 DATA WARE HOUSING AND DATA MINING THEORY SYLLABUS REGULATION 2013
UNIT I DATA WAREHOUSING
Data warehousing Components –Building a Data warehouse –- Mapping the Data Warehouse to a Multiprocessor Architecture – DBMS Schemas for Decision Support – Data Extraction, Cleanup, and Transformation Tools –Metadata. 

UNIT II BUSINESS ANALYSIS
Reporting and Query tools and Applications – Tool Categories – The Need for Applications – Cognos Impromptu – Online Analytical Processing (OLAP) – Need – Multidimensional Data Model – OLAP Guidelines – Multidimensional versus Multirelational OLAP – Categories of Tools – OLAP Tools and the Internet. 

UNIT III DATA MINING
Introduction – Data – Types of Data – Data Mining Functionalities – Interestingness of Patterns – Classification of Data Mining Systems – Data Mining Task Primitives – Integration of a Data Mining System with a Data Warehouse – Issues –Data Preprocessing.

UNIT IV ASSOCIATION RULE MINING AND CLASSIFICATION
Mining Frequent Patterns, Associations and Correlations – Mining Methods – Mining various Kinds of Association Rules – Correlation Analysis – Constraint Based Association Mining – Classification and Prediction - Basic Concepts - Decision Tree Induction - Bayesian Classification – Rule Based Classification – Classification by Back propagation – Support Vector Machines – Associative Classification – Lazy Learners – Other Classification Methods – Prediction.

UNIT V CLUSTERING AND TRENDS IN DATA MINING
Cluster Analysis - Types of Data – Categorization of Major Clustering Methods – K-means– Partitioning Methods – Hierarchical Methods - Density-Based Methods –Grid Based Methods – Model-Based Clustering Methods – Clustering High Dimensional Data - Constraint – Based Cluster Analysis – Outlier Analysis – Data Mining Applications.
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IT6702 Data Warehousing and Data Mining Syllabus Notes Question Papers Question Bank with answers Reviewed by Anirudhan R on 8:08 PM Rating: 5

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