Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 2

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Advanced OLAP ConceptsAdvanced OLAP ConceptsPart 2Part 2

<OLAP Concepts 201 Series>Renu Singh

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OLAP Overview• On-Line Analytical Processing is a decision support

software that allows the user to quickly analyze information that has been summarized into multidimensional views and hierarchies.

• There are three main features of OLAP system : Multidimensional Viewing – OLAP supports

multidimensional model which consists of facts and dimensions also called as Star Schema.

Calculation Intensive Capabilities – Due to data is stored in facts and dimensions tables, it enables users to analyze data without much calculations.

Time Series analysis – Enables users to analyze data across time.

• This Module will cover the details in four parts:– Part 1 – OLAP Modeling – Building Blocks– Part 2 – OLAP Types & Architectures – Part 3 – OLAP Reporting Styles – Part 4 – OLAP Issues & Optimization


OLAP Objectives

Upon completion of this module you will be able to:• Various OLAP Types and their Architectures


OLAP Outline

Lesson 1 OLAP Types and Architectures

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OLAP Types & Architectures

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Data is stored in multidimensional cubes MDDB technology is proprietary. Compilation intensive architecture. Load involves series of aggregations across orthogonal

dimensions Good to access pre-aggregated data

MOLAP – Multidimensional OLAP


Advantages• Intuitive• Performance

advantages• Ease of navigation• Little Performance

Tuning required

MDDB - A perspective

Disadvantages• Proprietary• No standard storage

techniques• Aggregate explosion

problem• Limited to 50-100 GB of

calculated data


Store atomic data in a proprietary data structure (MDDB), pre-calculate as many outcomes as possible, obtain OLAP functionality via proprietary algorithms running against this data.

Obtain multi-dimensional reports from the DSS Client

MOLAP - Architecture

MDDB Engine MDDB Engine Decision Support Client

Database Layer Application Logic Layer Presentation Layer


Support for large databases with good performance Excellent platform portability Good exploitation of hardware advances such as parallel

processing Codd rules however are not concerned about storage, but

about functionality only

ROLAP


Advantages • Robust security • Multi-user concurrent access

(e.g. read-write with locking) • Widely recognized standards • Openness to multiple tools • Based on familiar, proven

and scalable technology Extraction & Replication Parallelization Query Optimization Advanced Indexing

techniques

ROLAP - A Perspective

Disadvantages• Computation Intensive

queries are slow.• Additional layer of OLAP

engine• Non intuitive


Three tiered Architecture : • OLAP interface • ROLAP engine• RDBMS

ROLAP - Architecture

Data Warehouse ROLAP Engine Decision Support Client

Database Layer Application Logic Layer Presentation Layer


Hybrid approach seeks to provide best of both worlds - MOLAP and ROLAP

Create MDB structures for fast analytical needs Create mappings to RDBMS for larger data volumes The engine hides these mappings/ structures from the end

user

HOLAP - Hybrid OLAP


Advantages• Performance due to MDB

structures• Integration with data

maintained in RDBMS• Leverages RDBMS engine

and administration skills• Support for large volumes of

data by Relational Mappings

Hybrid OLAP - A perspective

Disadvantages• Managing large number of

data structures• Complex Architecture• Expensive


HOLAP - Architecture


Desktop OLAP tools work by extracting RDBMS data into local (or server) MD cubes

User queries are limited to the predefined dimensions in the hypercube

Do not provide shared environment Do not provide read/write capabilities Low cost tools

DOLAP


DOLAP - Architecture


Most OLAP products can now be deployed to Web browsers Approaches used

• Static Web publishing - The reports are generated in the form of HTML documents

• Using a Web OLAP Server - Simple scripts allow users to perform basic manipulations like dimension rotations, drill downs and dimension member selections

Web OLAP


Web OLAP - Architecture


Congratulations! You have now completed the module OLAP Types

You should now be able – Understand different OLAP Types– Architecture– Advantages Disadvantages

Module Summary

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The cube structure in OLAP achieves the __________functionalitya) Sharedb) Informationc) Collectiond) Multidimensional

Question 1

Answer: D


Aggregation provides OLAP with __________

a) Multidimensional Datab) Pre Calculated Datac) Slow Retrievald) Nested Data

Question 2

Answer: B


MDDB Engine is used in __________architecturea) HOLAPb) WOLAPc) MOLAPd) None of the above

Question 3

Answer: C


Deploying OLAP products on Web Browsers is

a) Web Deploymentb) WOLAPc) Web Reportsd) None of the above

Question 4

Answer: B


ROLAP Architecture includes

a) DBMS, Engine, DSSb) DBMS, ROLAP Engine, OLAP Interfacec) ROLAP Engined) None of the above

Question 5

Answer: B

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References

Library:Tek-tips reporting solutions

forumhttp://www.dmreview.com/http://www.dwinfocenter.org

Data warehouse and OLAP – Concepts, Architecture and Solutions by Robert Wrember & Christian Koncilia

The OLAP Report by Nigel Pendse and Richard Creeth

The OLAP Solutions – Building Multidimensional Information Systems Second Edition by Erik Thomsen, Wiley dreamtech India Pvt. Ltd. 2002 ISBN 81-265-0275-4

Publications Publications

Training ProgramsURL’s

Bts(Fs-tmt) Dwh - Ucf 2.x Advanced Olap Concepts v1.0 - Part 2

Documents

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