Deepanshi Dube Gaurav Kalra Sakshi

8/14/2019 Deepanshi Dube Gaurav Kalra Sakshi

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DEEPANSHI DUBE GAURAV KALRA

SAKSHI BAJ PREKSHA JAINYASH PAREEK JENTI TAHILIANI


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UNDERSTANDING DATA WAREHOUSING CUSTOMIZING DATA WAREHOUSES DATA MODELING

DATA WAREHOUSING USING OLAP SYSTEM TYPES OF OLAP OLAP V/S OLTP DEVELOPING BUSINESS STRATEGIES


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A Data Warehouse is a

repository database thatefficiently extracts datafrom existing systems for

the rapid analysis andreporting of information in abusiness enterprise.


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RELATIONAL DATABASES ( RDBMS ):-

This organizes data into related rows

and columns as specified by the relationalmodel.

FLAT FILE STRUCTURE :-

This comprises fields that are the samefixed length with records each separatedby a delimiter.


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Formulate Business Strategies

Used for Analysis / EffectiveReport Generation

Collate and consolidate data

Generate complex Query / Report


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DATA VALIDATION

DATA PREPARATION

DATA CLEANSING AND

TRANSFORMATION

DATA LOADING


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A Data Mart is a customized smaller

version of a data warehouse. DataMarts are smaller and focused onthe customization needs of aparticular department and the endusers. These provide inputs to thedecision support system for thedepartment.


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Efficient management of data

The decision support systems can easilyanalyze this information

The cost of data mart is less than thatof data warehouse

The performance of the systems is good.


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Data Modeling is defined as theprocess whereby integrated dataobtained from divergent sources ismodeled to map to the usersperspective.Data modeling is used to

design the data warehouse.


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A Schema is a diagrammatic representationof the relation that exist among a group oftables in a database.

It is used for dimensional modeling

It provides a multi dimensional view to the enduser

Epicenter of this schema is a fact table

Queries that rely on multiple dimension can use theschema to return accurate result


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In a survey, we asked respondentsabout the extent to which they hadachieved eight separate potential

business benefits. The possible levelsvaried from "Proven and Quantified" to"Got Worse/More Expensive." We usedthese responses to calculate weightedscores, plotted in a Figure which can beseen in the next slide


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On-Line Analytical Processing (OLAP) tools meet theneed for interactive multidimensional reporting and

analysis. They allow

operational managers to perform trend, comparative,and time-based

analysis by enabling exploration of pre-calculated andsummarized data

along multiple dimensions. Operational managers can

explore data firstat a summary level, then drill down through the data

hierarchy


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In DATA WAREHOUSE using OLAP system,information exploration and historical trend

analysis requirements of the organizationare assessed.

The data that is analyzed by OLAP tools is

obtained from the DATA WAREHOUSE todetermine the future ratio of success forthe companies.


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Steps in the OLAP Creation Process


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A Data cube stores dimensions,hierarchies and facts, which are

analyzed according to the userperspective.


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Offers real time access to data.Provides a multi-dimensional view.Provides quick access to all

aggregates statements.Management of the DataWarehouse and Business

Intelligence.


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OLAP systems have been traditionallycategorized using the followingtaxonomy

Multidimensional OLAP (MOLAP)

Relational OLAP (ROLAP)

Hybrid OLAP (HOLAP)


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MOLAP is the 'classic' form of OLAP andis sometimes referred to as just OLAP.MOLAP uses database structures that are

generally optimal for attributes.

ROLAP works directly with relational databases.The base data and the dimension tables are storedas relational tables and new tables are created tohold the aggregated information.


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A HOLAP database will use relational tablesto hold the larger quantities of detailed

data, and use specialized storage for atleast some aspects of the smaller quantitiesof more-aggregate or less-detailed data.


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OLTP OLAP

users Clerk,it professional Knowledgeworker

functions Day to dayoperations

Decision support

DB design Application oriented Subject oriented

Usage repetitive Ad-hoc

Unit of

work

Short,simple

transaction

Complex query

DB size 100 MB-GB 100 MB-TB


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The various tools used in developing businessstrategies include :-

Data MiningKnowledge Management System

Business Intelligence Systems


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Data Mining is an activity that extracts

information to discover hidden factsthat are contained in databases.

It is a technique that helps in analyzing

data in an accurate and effectivemanner.


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Knowledge Management System is a process ofadopting knowledge as a strategic asset to drive a

sustainable business advantage. The many benefitsof Knowledge Management System include :-

Improved decision making

Improved customer serviceEnhanced employee skills

Increased profits


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Business Intelligence entails the process of :-

Collecting the right information

Analyzing the collected informationConverting the collected information or data intoa useful form

Distributing the useful form of the data acrossthe enterprise

Deepanshi Dube Gaurav Kalra Sakshi

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