Data Ware Housing & Data Mining – Adv
- Description
- Curriculum
- Reviews
Model Question Paper
Data Ware Housing & Data Mining
Key Features
- Unit-wise Short Notes
Each unit includes a summary in both languages, making revision faster and more effective. -
Extensive MCQ Practice
1500+ MCQ Practice Questions: This comprehensive question bank includes 1500+ multiple-choice questions (MCQs). Each unit contains approximately 150 MCQs covering a wide range of cognitive levels such as remembering, understanding, application, and analysis. -
Exam Practice Paper with Mock Tests
Includes three full-length mock tests for real exam practice. One mock test is free for students to assess the quality of our question paper. -
Latest Syllabus as per NEP
The syllabus aligns with the latest National Education Policy (NEP) and follows the exam patterns of MSU, CCSU, and other universities following the NEP. -
Designed by Experts
This question bank has been meticulously prepared by subject matter experts to ensure accuracy and relevance.
Why Choose This Model Paper?
- Complete Exam Preparation: Unit-wise summaries, MCQ practice, and mock tests provide a complete study solution.
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Latest NEP-Based Pattern: Ensures compliance with the latest university exam structure.
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Program/Class: Degree/ BCA |
Year: Third |
Semester: Sixth |
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Department: BCA |
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Course Title: Data warehousing & Data mining |
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Credits: 4 |
Core Compulsory |
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Max. Marks: 25+75 |
Min. Passing Marks: 33 |
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Unit |
Topics |
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I |
Data Warehousing: Introduction to Data Warehouse, its competitive advantage, Data warehouse Vs Operational Data, Things to consider while building Data Warehouse
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II |
Implementation: Building Data warehousing team, Defining data warehousing project, data warehousing project management, Project estimation for data warehousing, Data warehousing project implementation
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III |
Techniques: Bitmapped indexes, Star queries, Read only table spaces, Parallel Processing, Partition views, Optimizing extraction process
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IV |
Data Mining: Introduction to Data Mining, benefits of Data Mining, How it helps in decision making, Data mining techniques, Introduction to Data Mart, Data Mart Tools, Data warehouse vs Data Mart, OLAP and its need, MOLAP and ROLAP
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Unit 1: English Summary - Data Ware Housing & Data Mining -
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Unit 1: MCQs - Data Ware Housing & Data Mining- Adv -
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Unit 2: English Summary - Data Ware Housing & Data Mining
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Unit 2: MCQs - Data Ware Housing & Data Mining- Adv
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Unit 3: English Summary - Data Ware Housing & Data Mining
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Unit 3: MCQs - Data Ware Housing & Data Mining- Adv
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Unit 4: English Summary - Data Ware Housing & Data Mining
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Unit 4: MCQs - Data Ware Housing & Data Mining- Adv
