Conceptual Modeling of Data Warehouses

Duration: Under a minute

This video lesson is available to enrolled students.

Return to /learn/DSSSB-TGT-COMPUTER-SCIENCE-PAPER-2/data-base-management-system/data-warehousing-mining/data-warehousing/asset-conceptual-modeling-of-data-warehouses after enrolling

Inside: a video lesson and guided study material.

Module outline

  1. About Course: About the Course
  2. Programming, Data Structures, OOP & Java: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling, Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing, Java, OOPS with C++, Java Fundamentals, Array, String, IO & References, Language Design, Intro to Compilers, Visual Basics, Syntax Analysis: Bottom-Up, Object Oriented Technology
  3. Computer Networks, TCP/IP & Network Security: Introduction to CN, Data Communication, DLL: Flow Control, DLL: Access Control, DLL: Error Control, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics, Network Access Technologies, Network Security, Society, Law & Ethics, Cloud Computing, Mobile Computing, Net Layer:Routing Protocol, Cyber Safety and Security
  4. Teaching Methodology: Child Development, Concept of Pedagogy, Theories, Inclusive Education, Experiential Pedagogy, Assessment & Evaluation, Curriculum Framework & Reforms, National Education Policy (NEP) 2020, Psychology, Teaching-Learning Process, Personality Development, Teaching Methods & Strategies, Learning and Motivation, Learners & Learning Process, Factors Affecting Teaching, Methods of Teaching, Nature, Objectives & Characteristics of Teaching, Teaching-Learning Aids & ICT Integration, Classroom Management & Communication, Evaluation, Assessment & Measurement, Curriculum & School Environment, Inclusive Education & Special Needs, Professional Development & Ethics
  5. Digital Electronics / Boolean Logic: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation, Analog-Digital Conversion
  6. Operating Systems & Linux: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, File Management, Disc Scheduling, Unix OS, Linux OS, Distributed Systems, Windows OS
  7. Data Base Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, Relational Algebra, SQL, File Organization & Indexing, Transaction Management, Concurrency Control, Database Security & Authorization, Database Recovery, Data Warehousing & Mining
  8. Internet & Web Technologies: Website, Browser & Services, Internet Fundamentals, Web Design & Development, Protocols & Services, Web Publishing & Hosting, Server Side & Security, HTML Basics, CSS, Emerging Technologies, JavaScript-Basics, .Net Programming, Electronic Data Interchange and E-Commerce, XML
  9. Computer Fundamentals, IT Basics & Architecture: Basics of COA, Cache Memory Organization, Input Output Organisation, Register Transfer and Microoperations, Control Unit Design, Programming the Basic Computer, Terms & Abbreviations, MS Office Applications, Instr Formats & Modes, Floating Point Rep
  10. Python Language: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis
  11. Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management, extras, Fundamentals of Systems and Information Systems
  12. Design & Analysis of Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Advanced Algorithms
  13. Mathematics - I, II, III, IV: Permutation and Combination, Logarithm, Linear Algebra, Algebra, Calculus, Trigonometry, Vectors, Set Theory, Functions, Relations, Propositional and Predicate Logic, Research Process Steps, Graph Theory
  14. Computer Graphics, Multimedia & Mobile Computing: Basics of Computer Graphics, 2-D Geometrical Transforms and Viewing, 3-D Object Representation, Geometric Transformations and Viewing, Multimedia
  15. Emerging Trends: Emerging Tech Trends, Knowledge Representation, Natural Language Processing
  16. Statistical Techniques: Probability, Statistics
  17. Interpolation - DI: Data Interpretation
  18. Basis of Physics: Physics
  19. Previous Year Paper:
  20. Business Studies and Management: Business Communication, Business Organization and Management, Financial Accounting, Business Economics, Management Information System (MIS), Knowledge Management & New Economy
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video presents a lecture on conceptual modeling for data warehouses, focusing on the star schema and fact constellation. It begins by defining the star schema as a model with a central fact table connected to multiple dimension tables. A diagram illustrates this structure, showing a 'Sales Fact Table' linked to 'time', 'item', 'branch', and 'location' dimension tables, with measures like 'units sold' and 'dollars sold'. The lecture then transitions to the fact constellation, which is shown as a more complex model with multiple fact tables (e.g., 'Sales Fact Table' and 'Shipping Fact Table') sharing common dimension tables, demonstrating a more flexible but complex design. The visual content is a slide presentation with clear text and diagrams, and the instructor's voice provides the explanation.

Chapters

  1. 0:00 – 0:30 00:00-00:30

    The video starts with a slide titled 'Conceptual Modeling of Data Warehouses'. The instructor explains the concept of modeling data warehouses using dimensions and measures. The slide defines the 'Star schema' as a fact table in the middle connected to a set of dimension tables. The presentation then transitions to a diagram titled 'Example of Star Schema', which visually depicts a central 'Sales Fact Table' with attributes like 'units sold' and 'dollars sold', connected via foreign keys to dimension tables for 'time', 'item', 'branch', and 'location'. The diagram clearly shows the relationships between the fact and dimension tables, with the 'time' table containing attributes like 'day', 'month', and 'year'.

The lecture progresses from a foundational definition of the star schema to a more complex model, the fact constellation. It demonstrates that while the star schema is a simple, hub-and-spoke model ideal for single fact analysis, the fact constellation allows for multiple fact tables to share dimensions, enabling more complex analytical queries across different business processes. The visual examples effectively contrast the two modeling approaches, highlighting the trade-off between simplicity and analytical power.

Loading lesson…