OLAP Vs OLTP

Duration: 5 min

This video lesson is available to enrolled students.

Return to /learn/COGNIZANT-PREPARATION/dbms/basics-of-dbms/types-dba-functions/asset-olap-vs-oltp after enrolling

Inside: a video lesson and guided study material.

Module outline

  1. Communication Round: Vocabulary, Subject Verb Agreement (Verb Noun Agreement), Tenses, Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Cloze Test (Cloze Passage), Sentence Correction (Error Correction), Sentence Completion (Fill in the blanks), Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Direct and Indirect Speech, Active Passive Voice (Voice), Verbal Analogy (Word Based Analogy), Articles, Preposition, Conjunction, Sentence Construction, English Writing Ability, Communication Assessment
  2. Quantitative Aptitude: Ratio and Proportion (Ratios), Divisibility Rules, Data Interpretation, Mixture and Alligation, Permutation and Combination, Logarithm, Number System, HCF LCM, Speed Time and Distance, Percentage, Average, Powers and Exponents (Surds and Indices), Time and Work, Mensuration and Geometry, Age Problems, Pipe and Cistern, Probability, Profit and Loss, Simple Interest and Compound Interest, Algebra
  3. Analytical and Logical Reasoning: Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Data Sufficiency, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Directions (Direction Test), Ranking, Order and Sequence, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Selection Decision Table (Decision Making), Logical Sequence Of Words, Puzzle Solving (Puzzles), Syllogisms, Seating Arrangements, Calendar, Clock, Blood Relations, Cubes & Dices, Venn Diagram, Analytical Reasoning (Counting Figures Reasoning)
  4. Cognizant Gaming Aptitude: Gamified / Game Based Aptitude
  5. Java (Cluster 1): Java
  6. ANSI SQL MySQL (Cluster 1,2,3): SQL
  7. HTML, CSS, JavaScript (Cluster 1,3): HTML, CSS, JavaScript
  8. Python (Cluster 2): Python for Placements by Yash Sir
  9. Cloud Fundamentals (Cluster 2): Emerging Tech Trends
  10. C# (Cluster 3): C#
  11. OOPs: Object Oriented Programming (OOPS)
  12. Technical Assessment (Coding): Coding Questions by Yash Sir, C Programming by Yash Sir, Programming in C++, Pseudo Codes
  13. Data Structures: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  14. DBMS: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, Relational Calculus, Transaction Management, Concurrency Control, Database Recovery, ORDBMS, Database Security & Authorization, Query Processing & Optimization, Enhanced Data Models, Data Warehousing & Mining, Big Data Systems, NoSQL
  15. Operating Systems: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Windows OS, Linux OS, Security, Distributed Systems, Virtual Machines
  16. Computer Networks: Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics, Network Security, Mobile Technology, Cloud Computing and IoT, Cyber and Info Security
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This lecture segment introduces the distinction between OLAP and OLTP database systems using a static two-column comparison slide titled "OLAP Vs OLTP." The instructor presents the material by sequentially highlighting rows in a side-by-side table, using red hand-drawn circles around the column headers and red checkmarks or underlines next to key phrases. The OLAP column is characterized as giving a multi-dimensional view of business activities, helping with planning, problem solving, and decision support, and using consolidated data as its source. The OLTP column is described as enabling a snapshot of ongoing business processes, being useful for controlling and running fundamental business tasks, and using operational data as its source. The teaching flow moves from the top rows describing purpose down to lower rows describing data sources, with annotations accumulating on the slide as the instructor progresses. Because only sampled screenshots are available and no transcript or audio is provided, the exact spoken explanations cannot be verified; the summary relies on visible slide text and annotation cues.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The slide titled "OLAP Vs OLTP" appears with two check-marked columns. The instructor begins by circling the "OLAP" and "OLTP" headers in red, then highlights the first row: OLAP "Gives a multi-dimensional view of business activities" versus OLTP "Enables a snapshot of ongoing business processes." Red checkmarks appear next to these phrases, and the second row is introduced: OLAP "Helps with planning, problem solving, and decision support" versus OLTP "Useful for controlling and running fundamental business tasks."

  2. 2:00 – 4:42 02:00-04:42

    The comparison continues down the table to the data-source rows. The instructor highlights "Data source is consolidated data" under OLAP and "Data source is the operational data" under OLTP, adding red checkmarks and underline/arrow marks to each row. The slide remains static with the circled headers, a small red "HFD" mark near the top-left, and accumulated annotations guiding attention through each characteristic. The segment ends with the fully annotated comparison table visible.

The core concept is a structured contrast between analytical (OLAP) and transactional (OLTP) database systems. OLAP is framed around multi-dimensional analysis, planning, problem solving, decision support, and consolidated data. OLTP is framed around operational snapshots, controlling and running fundamental business tasks, and operational data. The instructional method is a row-by-row walkthrough of a comparison table, using red circles on headers and checkmarks/underlines as visual anchors. For exam revision, students should memorize the paired contrasts: multi-dimensional view vs snapshot of ongoing processes; planning/decision support vs controlling/running tasks; consolidated data vs operational data. No formulas, code, or worked examples are visible in the sampled frames; the lesson is conceptual and table-based.

Loading lesson…