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Semester 1MCA135

Data Warehousing and Mining (MCA135) crash course, Online MCA, Semester 1:

This subject covers how data warehouses are designed, built and tuned for multidimensional analysis, and how data mining techniques such as clustering,…

  • 19 video lessons
  • 3h 58m
  • Study notes
  • 95 quiz questions
  • Assignment
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Data Warehousing and Mining crash course

19 lessons in Data Warehousing and Mining

Each lesson pairs one topic with a hand-picked video, trimmed to the part that teaches it.

About this subject

This subject covers how data warehouses are designed, built and tuned for multidimensional analysis, and how data mining techniques such as clustering, decision trees and neural networks extract descriptive and predictive models from large datasets. After it, you will be able to plan a data warehousing project, apply performance techniques like bitmapped indexes and partitioning, and choose suitable mining methods for business and government problems.

  1. 1

    Introduction to Data Warehouse and Its Competitive Advantage

    Module I, Data Warehousing: Introduction to Data Warehouse, its competitive advantage

    L1: Data warehouse Features | Introduction | Data warehouse and Data Mining(DWDM) Lectures in Hindi· Easy Engineering Classes· 17 min

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  2. 2

    Data Warehouse vs Operational Data

    Module I, Data Warehousing: Data warehouse vs Operational Data

    L5: ETL Process, Comparison between OLTP and Data Warehouse | Data warehouse Data Mining Lectures· Easy Engineering Classes· 9 min

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  3. 3

    Things to Consider While Building a Data Warehouse

    Module I, Data Warehousing: Things to consider while building Data Warehouse

    How to Build a Data Warehouse (Full Lifecycle Explained)· 365 Data Science· 5 min

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  4. 4

    Building a Data Warehousing Team and Defining the Project

    Module II, Implementation: Building Data warehousing team, Defining data warehousing project

    Design Data Architecture for Your Data Warehouse | Data Engineer Portfolio Project | #SQL Project 5· Data with Baraa· 10 min

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  5. 5

    Data Warehousing Project Management and Estimation

    Module II, Implementation: data warehousing project management, Project estimation for data warehousing

    Chapter 2 - Data Warehousing Planning and Project Management_PART1· skema lecturer· 19 min

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  6. 6

    Data Warehousing Project Implementation

    Module II, Implementation: Data warehousing project implementation

    8 Data warehouse implementation· Technology with Kiran· 9 min

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  7. 7

    Bitmapped Indexes and Star Queries

    Module III, Techniques: Bitmapped indexes, Star queries

    Bitmap index and Join index· Dr. Azizkhan F Pathan· 22 min

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  8. 8

    Read Only Tablespaces and Parallel Processing

    Module III, Techniques: Read only tablespaces, Parallel Processing

    TABLESPACE MANAGEMENT READ ONLY READ WRITE LOGGING NOLOGGING OFFLINE ONLINE MODES· The Supreme Family· 5 min

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  9. 9

    Partition Views and Optimizing ETL Extraction

    Module III, Techniques: Partition views, Optimizing extraction process

    SQL Table Partitioning (Visually Explained) | Optimize Big Table Performance | #SQL Course 42· Data with Baraa· 33 min

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  10. 10

    From Data Warehousing to Data Mining: Objectives

    Module IV, Data Mining: From Data ware housing to Data Mining, Objectives of Data Mining

    L21: Difference between Data Warehouse and Data Mining | Data warehouse and Data Mining Lectures· Easy Engineering Classes· 5 min

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  11. 11

    Business Context of Data Mining: Process Improvement, Marketing and CRM

    Module IV, Data Mining: the Business context for Data mining, Process improvement, marketing and Customer Relationship Management (CRM)

    What is Data Mining? ⛏️ | Data Mining Explained in Hindi for Beginners | Data Mining in Hindi· Code-yug· 6 min

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  12. 12

    Technical Context of Data Mining: Machine Learning and Decision Support

    Module IV, Data Mining: the Technical context for Data Mining, machine learning, decision support and computer technology

    What is Data Mining?· IBM Technology· 7 min

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  13. 13

    Data Mining Process and Algorithms Overview

    Module V, Data Mining Techniques and Algorithms: Process of data mining, Algorithms, Data Mining Techniques

    L20: Data Mining Process Architecture | Steps in Data Mining/Phases of KDD in Databases | DWDM· Easy Engineering Classes· 9 min

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  14. 14

    Database Segmentation and Automatic Cluster Detection

    Module V, Data Mining Techniques and Algorithms: Data base segmentation or clustering, Automatic Cluster Detection

    Lec - 23 : Clustering in Data Mining Explained | Top Clustering Methods You MUST Know!· Gate Smashers· 6 min

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  15. 15

    Predictive Modeling and Link Analysis

    Module V, Data Mining Techniques and Algorithms: predictive Modeling, Link Analysis

    Chapter 7 - Data Mining Basics_PART2· skema lecturer· 32 min

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  16. 16

    Decision Trees and Neural Networks in Data Mining

    Module V, Data Mining Techniques and Algorithms: Decision trees and Neural Networks

    L37: Decision Tree Technique for Classification and Prediction | Data Mining Lectures in Hindi· Easy Engineering Classes· 8 min

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  17. 17

    Case Studies in Building a Business Data Mining Environment

    Module VI, Data Mining Environment: Case studies in building business environment

    Module 1.2: Administrivia & Intro (Part 2) | Data Mining (2025/26 CSC 4792))· Lighton Phiri· 10 min

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  18. 18

    Data Warehousing and Data Mining in Government

    Module VI, Data Mining Environment: Application of data ware housing and Data mining in Government

    E-Commerce and E-Governance(Application of Data Warehousing and Data Mining)· SICS Chitrakoot· 23 min

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  19. 19

    National Data Warehouses: Case Studies

    Module VI, Data Mining Environment: National Data ware houses and case studies

    National Data Warehouse For Egyptian Foreign Trade; a Success Story· ERF Official· 3 min

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Assignment

Design and Mine a Retail Sales Data Warehouse: From Requirements to Patterns

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    Hand-picked video lessons

    19 short lessons, each with the best YouTube explanation we could find, trimmed to the part that matters.

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    95 questions across the course, with the right answer and why, the moment you pick.

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Data Warehousing and Mining: common questions

This subject covers how data warehouses are designed, built and tuned for multidimensional analysis, and how data mining techniques such as clustering, decision trees and neural networks extract descriptive and predictive models from large datasets. After it, you will be able to plan a data warehousing project, apply performance techniques like bitmapped indexes and partitioning, and choose suitable mining methods for business and government problems. It's the Data Warehousing and Mining subject of Online MCA, Semester 1, in 19 lessons: Introduction to Data Warehouse and Its Competitive Advantage; Data Warehouse vs Operational Data; Things to Consider While Building a Data Warehouse; Building a Data Warehousing Team and Defining the Project; Data Warehousing Project Management and Estimation; Data Warehousing Project Implementation; Bitmapped Indexes and Star Queries; Read Only Tablespaces and Parallel Processing; Partition Views and Optimizing ETL Extraction; From Data Warehousing to Data Mining: Objectives; Business Context of Data Mining: Process Improvement, Marketing and CRM; Technical Context of Data Mining: Machine Learning and Decision Support; Data Mining Process and Algorithms Overview; Database Segmentation and Automatic Cluster Detection; Predictive Modeling and Link Analysis; Decision Trees and Neural Networks in Data Mining; Case Studies in Building a Business Data Mining Environment; Data Warehousing and Data Mining in Government; National Data Warehouses: Case Studies.

Yes. Every video lesson is free to watch without an account. A free login unlocks study notes, quizzes, the assignment, a notebook and progress that syncs across devices.

About 3h 58m of video across 19 lessons, plus time for notes and quizzes. Go at your own pace; your place is saved.

Yes: “Design and Mine a Retail Sales Data Warehouse: From Requirements to Patterns”. It comes after the last lesson, with a brief, clear tasks and how the work is judged.

A members-only live chat beside the video, shared by everyone studying Online MCA, where learners ask doubts, share tips and react with stickers and GIFs. One ₹19 pass, paid once from your InsideEdge wallet, opens the live chat for every degree.

No. It's a crash course to help you understand and revise the subject quickly. Use it alongside your official study material and assignments.

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