Data Mining And Warehousing
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Data Mining And Warehousing Syllabus — Unit-wise Content
The official GTU curriculum for Data Mining And Warehousing (subject code 3361604) as prescribed for Biomed · Semester 6 divides the course into 6 units, covering 41 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (3361604)Unit 1 Fundamentals of data mining
- 1.1. Data mining: History, strategies, techniques, applications, challenges of data mining, Future of data mining
- 1.2. Types of Data
- 1.2.1. Database Data
- 1.2.2. Data Warehouses
- 1.2.3. Transactional Data
- 1.2.4. Other Kinds of Data
Unit 2 Objects, Attributes, & Statistical Description of Data
- 2.1. Data Attribute
- 2.1.1. Nominal Attributes
- 2.1.2. Binary Attributes
- 2.1.3. Ordinal Attributes
- 2.1.4. Numeric Attributes
- 2.1.5. Discrete versus Continuous Attributes
- 2.2. Mean, Median, and Mode
- 2.3. Measuring the Dispersion of Data: Range, Quartiles, Variance, Standard Deviation, and Interquartile Range using WEKA
Unit 3 Data Preprocessing
- 3.1. Preprocess the Data
- 3.2. Major Tasks in Data Preprocessing
- 3.2. Data Cleaning
- 3.2.1. Missing Values
- 3.2.2. Noisy Data
- 3.2.3. Data Cleaning as a Process
- 3.3. Data Integration
- 3.3.1. Entity Identification Problem
- 3.3.2. Redundancy and Correlation Analysis
- 3.3.3. Tuple Duplication
- 3.3.4. Data Value Conflict Detection and Data Mining and Warehousing Course code: 3361604 __________________________________________________________________________________________ GTU/NITTTR/Bhopal/14-15 Gujarat State 3 Unit Major Learning Outcomes (in cognitive domain) Topics and Sub-topics Resolution
- 3.3.5. Use WEKA for cleaning and integration
Unit 4 Classification
- 4. Explain decision Trees and clustering
- 4.1. Decision tree: ID3
- 4.2. Probability based solving
- 4.3. Concepts of Clustering
- 4.4. Using WEKA for classification and clustering
Unit 5 Data Warehouse & OLAP Technology
- 5.1. Data Warehouse
- 5.2. Differences between Operational Database Systems and Data Warehouses
- 5.3. Enterprise Warehouse, Data Mart, and Virtual Warehouse
Unit 6 Data Mining Tool: WEKA
- 6. Install and Configure WEKA Tool
- 6.1. Basic of WEKA
- 6.1. Installing WEKA
- 6.2. WEKA data file format
- 6.3. Data visualization in WEKA
- 6.4. Data filtering
- 6.5. Using the concepts of data mining with WEKA
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