Siksha Sarovar

Siksha Sarovar (sikshasarovar.com) is a free educational web application that helps students in India learn programming and prepare for academic and competitive exams. The platform offers structured coding courses (C, C++, Python, Java, HTML, CSS, PHP, Power BI, AI, Machine Learning, Data Science), complete university curriculum notes for BCA/MCA students with previous year question papers, Class 10 and Class 12 CBSE/HBSE school notes, and dedicated preparation material for SSC, UPSC, Banking, Railway and other government exams. Browsing the site is completely free and requires no account. Users may optionally sign in with Google solely to save their learning progress, quiz scores and personal preferences across devices.

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Siksha Sarovar is a free e-learning platform for coding courses, BCA university notes and competitive exam preparation. Optional Google sign-in saves your learning progress across devices.

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Unit 2 Overview

Lesson 11 of 32 in the free Data Warehousing and Data Mining(Elective-II) notes on Siksha Sarovar, written by Rohit Jangra.

Unit II: Multi-Dimensional Data Modelling

Data warehouse and OLAP technology, multidimensional data model and different OLAP operations, OLAP Serverx: ROLAP, MOLAP and HOLAP, Data warehouse implementation, efficient computation of data cubes, processing of OLAP queries, indexing OLAP data.

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Unit II: Multi-Dimensional Data Modelling

1. Data Warehouse and OLAP Technology

1.1 Understanding OLAP

Online Analytical Processing (OLAP) is a category of software technology that enables analysts, managers, and executives to gain insight into data through fast, consistent, interactive access to a wide variety of possible views of information.

Unlike OLTP (Online Transaction Processing), which records transactions, OLAP is about retrieving and analyzing data to find patterns, trends, and answers to business questions.

1.2 The Relationship: Data Warehouse and OLAP

The Data Warehouse and OLAP are complementary technologies.

  • The Data Warehouse is the storage container. It holds the historical, integrated data.
  • OLAP is the engine or the access method. It sits on top of the Data Warehouse (or Data Marts) and transforms the static data into multi-dimensional "cubes" for analysis.