Satyam - iDecisionsPresentation

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Business Intelligence &Data Warehousing

Copyright 2005 Satyam Computer Services Limited.


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iintegration.ntegration.iintelligence.ntelligence.iinsight.nsight.

Agenda

Roadblocks for BI Implementations

Roadblocks for BI Implementations1

1

2

2 Introduction to Packaged Analytics - iDecisions

Introduction to Packaged Analytics - iDecisions

3

3 Examples of Industry Verticals and Subject Areas

Examples of Industry Verticals and Subject Areas

4

4 iDecisions Case Studies

iDecisions Case Studies

5

5 Satyam Business Intelligence Practice Overview

Satyam Business Intelligence Practice Overview


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SourceOLTP

Systems

ReplicatedData Sets

Infinite Versionsof the Truth

Data Extracts

SourceOLTP

Systems

DataWarehouse

One Versionof the Truth

Source

OLTPSystems

HR Reporting System

Sales Reporting System

Mgmnt Reporting System

CRM Reporting System

Replicated Data Sets

Multiple Versions of the Truth

Oracle Financials

i2 AASystem

i2 Seibel CRM 3rd PartyData

OracleDW

Siebel AASystem

3rd Party AASystem

Whose Truth is it Anyway

60-80% of DW projects have failed to deliver on the promise

Business Intelligence - Reality Check


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Better Info

Better Data Qual

End-User Prod

Sprt Org Chg

Imprv Cost Mgmt

Reduce DSS Bac

Better Perf

Facilitate BPR

IT Productivity

Other

0 0.1 0.2 0.3 0.4 0.5 0.6

Better Info

Better Data Qual

End-User Prod

Sprt Org Chg

Imprv Cost Mgmt

Reduce DSS Bac

Better Perf

Facilitate BPR

IT Productivity

Other

Common Reasons for Failure

The Great Divide Between Business Users and IT

Ambitious Planning Data Warehouse is a Journey, not a Destination

Architecture and Technology Compromises

Quality of Data impacts the Quality of Decisions

Gap in Technology and Process Skills

Usage Problems Reports Vs Analytical Capability

Business Intelligence - Reality Check

Though the Business Drivers for Business Intelligence are clear, success hasbeen elusive due to clearly defined requirements

Source:Meta Group

0

2

4

6

8

10

12

14

16

18

1970's 1980's 1990's 2000's

Business Information Needs IT's Ability to Supply


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Multiple Data

Sources

Applications anddata organizedaround products

Heterogeneous

Hardware and

Databases

No consistentterminology /

business meta

data

#2#2

Proprietary

Technology

Standards

Multiple tools inmarket withown technology

stds

No openarchitecture

#4#4

Roadblocks

Time to Market

Modeling forDataWarehouse

Difficulty inwriting ETLprograms

Difficulty in

managingmetadata

#3#3#1#1

Unclear

Business

Requirements

Challenge indefininganalysis needs

(Reports VsAnalyticalNeeds)

Bridgingbusiness to

technology

Availability ofBusiness Users

Business Intelligence - Roadblocks


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Agenda

Roadblocks for BI ImplementationsRoadblocks for BI Implementations11

22 Introduction to Packaged Analytics - iDecisionsIntroduction to Packaged Analytics - iDecisions

33 Examples of Industry Verticals and Subject AreasExamples of Industry Verticals and Subject Areas

44 iDecisions Case StudiesiDecisions Case Studies

55 Satyam Business Intelligence Practice OverviewSatyam Business Intelligence Practice Overview


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Implementing Business Intelligence: Build Vs Buy

Source Build or Buy. Data Warehouse Institute 2003

Current Trends Business need - reduced time-to-market, i.e. faster implementation. Industry trend is move towards pre-packaged analytical applications

(pre-built & customizable Data Warehouse).

Trend similar to adoption of ERP applications and packagedapplications

Build Buy Build Buy

Average Project Cost(US$)

Return on Investment (in%)

2.1 mil. 1.8 mil. 104% 140%

15% 26%

Source: IDC's "The Financial Impact of Business Analytics" study made across 43European and U.S. organizations

A recent study by IDC also asserts that preA recent study by IDC also asserts that pre--built applications are cheaperbuilt applications are cheaper

to build and produce better returns on investmentto build and produce better returns on investment


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Definition of Packaged Analytics

Solution based on industry best practices

Highly Customizable and Flexible

Open Architecture

Analytical Application Templates : Packaged

AnalyticsPackaged Analytics are value-added solutions embedding knowledge ofthe process and expressing specific metrics for a given (set of) businessfunction(s) based on industry best practices.

Source: Gartner Group, 2002


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iDecisions Solution

Pre-Packaged, customization-friendly and Open AnalyticalApplication from Knowledge Dynamics

Developed based on Best-of-Breeds practice across

industries. Salient Features

Industry-standard multi-layer BI Data Model

Pre-built report and analysis templates Reporting and Analysis Layer delivered on Oracle BIEE

Technologies

Includes pre-built Metrics, Perspectives and Reportstemplates for data retrieval, measurement and analysis.

Highly customizable solution (One-Click Customization).

Cost-efficient and user-friendly interface.


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iDecisions - Accelerators for BI Solutions

Solution Accelerators for BI Analytical Solutions Industry Focused Domain Solutions

Pre-Built Data Models incorporating Industry Best Practices

Reduced Time-To-Market

Technology Neutral and Agnostic

Pre-Built Analytical Templates on Oracle BI EEE, Hyperion, Cognos, Business Objectsand MS Reporting Services


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iDecisions Packaged Analytics

iDecisions is a Packaged Analytic Application forBusiness Intelligence from Knowledge Dynamics.

It can be used by organizations to jumpstart their

Business Intelligence (Data Warehouse) initiatives.

iDecisions

Approach

Business

Requirements

Data

ModelETL Design

User AccessDesign

Development Test

BRD GapAnalysis

ImplementChange

Test

Traditional

Appro

ach

Month 1 Month 2 Month 3 Month 4 Month 6

Implementation time

reduced by 50%

Implementation time

reduced by 50%30%

Cost Savings

Illustrative

iDecisions

Approach

Business

Requirements

Data

ModelETL Design

User AccessDesign

Development TestBusiness

Requirements

Data

ModelETL Design

User AccessDesign

Development Test

BRD GapAnalysis

ImplementChange

Test

Traditional

Appro

ach

Month 1 Month 2 Month 3 Month 4 Month 6

Implementation time

reduced by 50%

Implementation time

reduced by 50%30%

Cost Savings

Illustrative


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iDecisions Deliverables and Value Proposition

Deliverable Value Proposition

Definition of staging files entry point for sourcedata (IFS format)

Pre-identified key data elements accelerates data acquisition from sourcesystems

Detailed Data Model Industry specific, flexible data models, decreases the time to build normalizedEDW and dimensional Data Models and map them to the acquisition andpresentation layers

Analytical Templates (standard predefined reportsand analytical scenarios)

Customizable templates, provides for domain specific, best practice analyticsand reporting that is flexible enough to incorporate metrics unique to eachbusiness

Internal Data

External Data

SOURCE DATA STAGING AREA DATABASE USER LAYER

AnalyticalTemplates

Data Entry ASCII, Excel etc.

Staging Area

Files, Either

RDBMS xml

or flat files

Custom

built

routines

Any

databaseData

Aggregation


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iDecisions on Oracle Platform


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Why iDecisions?

RAPID ROI with pre-built reports, templatesand best-practice analytics.

REDUCED TIME to implement.

REDUCED RISK at implementation.

QUICK time-to-market capability.

SCALABILITY included.

FLEXIBLE and customizable analyticapplications that cater to individual

requirements.


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Agenda







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Banking - Credit Risk

CustomerCountry

Account

Perspectives Metrics

- Risk Adjusted Return on Capital (RAROC)

- Expected Loss

- Unexpected Loss

- Change in Risk Profile

- Account Outstanding Amount

- Account Credit Repayment Status

- Account Write-off, Recovery & Write-BackDetails

- Relationship Officer Details

- Customer Credit Rating

Type, BU,Currency, Start-

End Dates, Credit

Limit, Rating,Charges,Repayment Grade

Customer Type

Customer Segment

Customer Demographics

Product

Prod.Desc & GrpStart-End DatesInterest, Charges

RiskGrade,L

imits,

Currency

Analytical Templates

Exposure Analysis

Current Relative Exposure byProduct

Current Exposure by DPDClassification

Exposure Trend by CollateralType

Delinquency Analysis

Accounts with current

DPD>180 days & DPDTrend

Old & Current AccountDelinquency

Write-off Amount by Loan

Classification Trend

Collateral Analysis

Collateral Mix by Country

Obligor Type by Outstanding

AmountCollateral Mix by Risk Grade

Collateral Type by FSV

Amount

Credit P rocess

Application Score Report

Credit Aging Report

Yield W ise Credit ReportRisk Grade vs RORC Report

IndustryInternal ClassificationRegulatory ClassificationLimits


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Banking - Customer Intelligence


-Customer Net Worth

-Customer Type (Salaried/Self Employed)

-Customer Residence Type (Rented/Own)

-Account Details

- Cost Details per Channel/Transaction

Type

- Cost of Capital, Operating Expenses,Other Cost Details

-Customer Contact Details

- Customer Acquisition Cost

- Customer Retention Cost

CustomerPro

duct

Account

Account Details

Type,Currency,Status, Balance,Brance

Customer Type

Customer Segment


ChannelChannel Start/End Date

Transaction Type

ProductStartD

ate

ProductEndDate

EffectiveInterestRa

te


Segmentation & P rofile Analysis

Segment Migration Trend Top Gainers by Segment

Segment by Similar Product AffinityNo. of Customer by P roducts Product by Length of Relationship

Behavioral Analysis

Same Time Joiners Trend

Segment Target vs. Actual

By Revenue

Customer Segments w ith

Different Product Affinity

Customer Profitability

High Profit Customer

Top Customers by Revenue

Credit Score AnalysisLowest Product Profits

Product Contribution


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Enterprise - Sales

CustomerT

ime

LegalEntity


- Billed Volume

- Billed Quantity

- Book to Bill Ratio

- Backlogs

- Order Entry Quantity

- Order Entry Amount

- Order Entry Costs

- Scheduled Deliver Quantity

- Scheduled Time Frame

- Order Booked Quantity

- Order Booked Revenue

Customer Type

Customer Segment


ProductProd.Desc & GrpStart-End DatesInterest, Charges

Month,quarter,

year


Comparative Analysis

Top Nth Products,

Bottom Nth Products,

Top X Customers,

Bottom Nth Customers,

Top Nth Salespersons, Bottom Nth Salespersons

Sales Variance Analysis

Actual vs. Budget,

Forecast,

Re-Forecast

Sales Trends

Variation over Time Periods Variation over P roducts

Sales Key Performance

Indicators

Sales by Customers,

Sales by P roducts,

Sales by Time P eriods

Market Competition

By Market Segment,

By Product Groups,

By Customer Locations

Entity Type


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Enterprise - Manufacturing

Lots

Tim

e

WorkArea

Perspectives

Lot Type, Desc

Process

Process Desc

Start-End Date

Month,quarter,

year


Key Indices Report

Work In P rogress

Turn Ratio

Cycle Time Moves

Yield

Efficiency

Fab Performance

Line Yield

Fab Yield

Wafer Acceptance TestYield

Fab CVP

Efficiency Report

Equipment Availability

Scrap

Re-work

Production Capacity

Wafer Start

Wafer Out

Fab Out

Area Desc

Area Size

Metrics

- Wafer Per Hour

- Equipment

Efficiency

- Utilisation

- Fab Yield

- Fab CLIP

- Run Time

- Lost Time

- Test Time

-Wafer Moves

-STEP Moves

-Location Moves

-Work-In-Progress

(WIP)

-End On Hand

-Begin On Hand

-Turn Ratio PerDay

-

Back-up Time

Shift Desc, Time

Shift


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Agenda






Case Study 1 Financial Intelligence System for a PortCase Study 1 - Financial Intelligence System for a Port


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CLIENT OVERVIEWOur client is the technological and market leader in port management and logistics. Theclients network of ports in Asia, the Middle East and Europe handles close to one-tenth ofglobal container throughput and 30% of world-wide transshipment volume. Our client isembarking on initiatives in e-commerce, logistics, cruise center development and eventmanagement with a view to extend their core competency across related business.

OBJECTIVEEnabling faster reporting and updatesProviding better transparency of informationEnabling sharing of resources and competencies to allentities

SOURCE

Non-Oracle

system

s

Oracle 11i Apps

Old COA

Oracle 11I Apps

New COA

External

Source

AR, AP, GL, PS

AR, AP, GL,

PS

Hyperion Essbase

App Manager / EIS Admin

Oracle 9i Database Server

STAGING WAREHOUSE / DATAMART END USER ACCESS

iLoad

Environmen

t

Essbase Integration Services

OWB

Repositor

y

Essbase Server

Essbase Cubes

FSDW

EIS

Repository

Analyzer

Repository

OWB Client

Financial System Data Warehouse Environment

Hyperion

Analyzer

Essbase Excel

Add-in Client

The solution implemented was a Financial System DataWarehouse dealing with Management Reporting, Revenue

Analysis, Spend Analysis, Debt Analysis and Staff Cost AnalysisBusiness Subject Areas

BENEFITSEase in development and consolidation of management

reportsEmpower users to perform on-line analysisMaintain historical data for meaningful correlation and trendanalysisProvide an integrated and consistent data repository tofacilitate information distribution for operational and planningsupportProvide users with pre-defined monthly, weekly, etc. reports

on timeReduce effort in preparing both regular and ad-hoc reportsand statistical analysis by empowering users to find theirown information through the use of powerful data accesstools.

SOLUTIONPopulation of Singapore financial/ historical data for bothold and new Chart of Accounts to the Financial System DataWarehouseFinancial Figures comes from the Oracle Financials,namely Oracle General Ledger (OGL), Oracle AccountsReceivables (OAR), Oracle Accounts Payables (OAP),Oracle Purchasing (OPS) and the different non-Oracle

Financials platform systems.Reporting and Analysis functionality for companies locatedin Singapore

Case Study 1 - Financial Intelligence System for a Portand Logistics Services Provider

Case Study 1 - Financial Intelligence System for a Portand Logistics Services Provider

C S d 2 A P fi bili M S


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TRADITIONAL

iDE

CISIONS

BusinessRequirements

Discovery

DataModel

ETL Design

User AccessDesign

Development Test

BRD GapAnalysis

ImplementChange

TestTIME & COST SAVINGS

Reduced Implementation

Time & Reduced Risk

The CustomerThe Customer

A UK based Pharma major with a presence in 116 countries with FY05 revenue of USD 39 Billion

Typical Implementation Duration 5 Months

Implementation Duration 3 Months

To meet the project objectivesthe following businessmodels were delivered.

The key business drivers for the implementation of the BI solution whereIdentify and effectively manage cost drivers to maximize group profitability.Interrogate the Sales and Cost of Goods Sold information, to derive Gross Profit at market and productlevel

Gather business insights to achieve multi-million dollars savings to replace the existing manual reportingand expense allocation processes.

Profit General

Ledger

Sales Expenses

Reduction of time 2 MonthsExpected ROI of 5 Million USD

Case Study 2- A Profitability Management SystemCase Study 2- A Profitability Management System

Th S l i


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The SolutionThe Solution

Customer Challenge

Timely management of tax liability arising out of profits accrued through intra-company sales was difficultdue to the manual processes involved in generating the relevant business insights

An IT enabled solution needed to be implemented within 3 calendar months to ensure appropriate profitmanagement for the current and future fiscal. Multi-million dollars of savings were at risk if the profitabilityrelated business insights could not be had within the required timeframe.

Business Benefits Operational Efficiency: Elimination of manual processes reducedthe time required for conducting profit and tax analysis Reduced Implementation Timeline: Shorter time to market for thesolution by leveraging iDecisions framework Best Practice Inculcation: Cross pollination of industry bestpractices due to utilization of iDecisions framework whose data

model is a collective essence of best practices across industries Leverage existing IT investments: iDecisions based Satyamsolution leveraged existing IT investments in JD Edwards andCognos thereby reducing additional investments in new products Futureproof Solution: Loose coupling of iDecisions with sourcesystems and reporting tools ensured that the business analyticsframework did not lock the customer into a particular product

Satyam Solution

A business insightssolution that provided therelevant profitability reportsfor intra-company sales after

collating the data frommultiple systems

Solution leveragesiDecisions a businessanalytics framework ofSatyam

Case Study 3 : APAC Financial Data Warehouse &Case Study 3 : APAC Financial Data Warehouse &


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The client is organized in the region with offices and manufacturing locations in variouscountries in the region. Singapore is the regional headquarters. There are five separateinstances of JDE in Asia. Each instance is customized to meet the local requirements andhas 7 years of data. Main Subject areas covered are P&L, Balance Sheet, Cash Flow,Product Code Analysis, Expense, Inventory, Liability, Capitol Expense, Accountreceivables, Sales & Gross Profit.

Case Study 3 : APAC Financial Data Warehouse &Budget Planning System

Case Study 3 : APAC Financial Data Warehouse &Budget Planning System

Excel based planning andbudgeting system that takes along time and lot of effort tocomplete.

Lack of centralRepository of financial &operational data cost

and profit analysis.

Business Pain Points

Lack of common views of financialinformation for analysis andbudgeting across variousdepartment and regions.

Integrated Financial Intelligence

System for FinancialPerformance Management

Focusing on Cost Allocation,Consolidation, Budget Planning

and Analytics

Solut

ion Effective management reporting and control. Manage multiple versions of budget acrros variousregions.

Able to perform manual adjustment to the costallocation With the consolidated financial data, finance usersare now able to perform budget planning and forecastexercise more efficiently and accurately Able to perform consolidation that allows users to

consolidate data from subsidiaries to generate thegroup balance sheet and profit & loss statements

Benefits

C St d 4 R l ti hi M k ti C St dCase Study 4 Relationship Marketing Case Study


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Case Study 4 - Relationship Marketing Case StudyCase Study 4 - Relationship Marketing Case Study

Objectives of the Campaign Automation Project Reduce customer acquisition costs by 50%

Boost customer retention by 5%

Support growing communication volume with same

resources Leverage customer knowledge to enhance targeting of right-

time communications

OverviewThe client is one of Indias leading private sector banks.

Provides a complete range of accounts and services.

Needed an effective way to Market its growing product and service lines

Leverage its customer base to optimize returns and

bottom-line revenue

Increase customer profitability

Build deeper, stronger customer relationships

Perform customer lifecycle marketing to send targeted

communications Build relationships and increase profit

Objectives of the Customer Activity Record(CAR) Project

Create a one-stop-shop for all Analytical Marketing needs

Enhance Customer Analysis capabilities with built ininformation such as scores and segments

Identify and implement a solution that is scalable bothfunctionally and technically

Benefits The key benefits derived by the client are:

Significant reduction in data preparation time for the campaignmanagement and marketing activities

Provided for increased latency of data for analytical marketingneeds to support real-time and event triggered marketingcampaigns.

Provided unrestrained slice and dice capabilities to end users tosupport data driven decision making by the users to design moreeffective campaigns.

Provides external data like competitor information to be

leveraged upon for analytical marketing purposes to increase theeffectiveness of the campaigns.

The Customer Activity Record is:

Used to store all analytical marketing data elements

inclusive of rollup dataAs a virtual sandbox of marketing data elements

(CAR)

A collection of all data elements that are owned by

other user groups but required for analytical

marketing (e.g. Credit Score)

Bank Enhances Bottom-Line Revenue Through Customer Lifecycle Marketing

A hit tArchitecture


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ArchitectureArchitecture

Analysis

Unica

StagingArea

Finware

FinOne

Vision Plus

Flex@

TPP

Base24

Debos

Others

Sources Acquisition Management User Access

OLAP Tool

ETL Tool

Reports

EDW

OCRM

Contact

MIS

Marketing

Reports

Weekly Load

Data Mining

De-D

uping

Cleansing

Ho

useholding

Mktg

ODS

Analysis

Unica

StagingArea

Finware

FinOne

Vision Plus

Flex@

TPP

Base24

Debos

Others

Finware

FinOne

Vision Plus

Flex@

TPP

Base24

Debos

Others

Sources Acquisition Management User Access

OLAP Tool

ETL Tool

Reports

EDW

OCRM

Contact

MIS

Marketing

Reports

Weekly Load

Data Mining

De-D

uping

Cleansing

Ho

useholding

Mktg

ODS

Unica Affinium

Agenda


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Agenda


22 Introduction to Analytical Application TemplatesIntroduction to Analytical Application Templates




B siness Intelligence & Data Wareho sing Snapshot


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Business Intelligence & Data Warehousing - Snapshot

Part of 7500+ strong EBS group

3500+ member strong BIDW practice

Total Number of Engagements Completed - 300+

Active customers - 70+

Major successes in BIDW Solution Center model - Six BIDW Solution Centers

30+ Technology Competencies

15+ Alliances with leading technology vendors in BIDW

Certified at CMMI Level 5 Global

Global Delivery locations in Hungary, Canada, Malaysia, China and Australia apart from India and US

Niche Singapore based BI Consulting firm

Vertical BI expertise in Banking and Basel II Experience in implementing over 100 Business Intelligence projects in Asia-Pacific

On Target TM methodology for BI Consulting

iDecisions TM for Analytical Applications

Gartner Magic Quadrant for Business Intelligence Implementation Services, North America, 2006 Satyamin theVisionariesquadrant

Testimonials by Thought Leader Bil l Inmon and Industry Analysts

Won the TDWI Best Practices Award in 2002 and 2006

First organization from India to join the XBR L Consortium

Experiences in Large Warehouses and Off shoring

PR

ACTICE

KD

HIGHS

Competency Spectrum


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Competency Spectrum

Capability

Engagement

Proof-Points

Low

High

CognosIBM Data stage

Microsoft

Low High

InformaticaBusiness Objects

SAPBWTeradataOracle

MicrostrategyActuate

SAS

EPM Tools

Hyperion

TechnologyCapabilities

Kalido

Siebel AnalyticsEpiphany

3,500+ Strong practice Global Delivery locations

Certified at CMMI Level 5

Global

30+ Technology Competencies

15+ Strategic Alliances with

Tech vendors

Focused Competency Centers

for leading Technologies

400

260

200

60

140

220240

100

20 60 50 50

100 100

200

50

150

250

350

450

Oracle SAP NCR SAS COGNOS

BUSINESS OBJECTS INFORMATICA DATASTAGE ACTUATE HYPERION

EPIPHANY SEIBEL EAI/EII MICROSOFT OTHERS

Panorama

Information Builders

Proclarity

BAMCelequest

The Challenges faced by our Clients can be broadly


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SomeCommonRoad-blocks

SomePossibleInitiatives

1. Lack of analysisready data withintegration issues

1. Lack of analysisready data withintegration issues

Build a Datawarehouse / mart

Implement a data

integration platform

Build a Datawarehouse / mart

Implement a data

integration platform

Data WarehouseImplementationServices

Design, Implementand OperateIntegrationCompetency Center

Data WarehouseImplementationServices

Design, Implementand OperateIntegrationCompetency Center

2. Lack of easy-to-useanalysis tools andapplications

2. Lack of easy-to-useanalysis tools andapplications

Deploy user friendlyanalysis tools

Implement subject

oriented analyticalapplications

Deploy user friendlyanalysis tools

Implement subject

oriented analyticalapplications

Design andImplementation of BIApplications

Implementation ofiDecisions basedSolutions

Design andImplementation of BIApplications

Implementation ofiDecisions basedSolutions

SampleOfferings

3. Lack of analysis cultureand processes

3. Lack of analysis cultureand processes

Implement data drivenprograms

Implement aReporting/BusinessIntelligence Unit

Implement data drivenprograms

Implement aReporting/Business

Intelligence Unit

Technical andAnalytical Consultingto accelerate adoption

Design, Implement andOperate BusinessIntelligenceCompetency Center

Technical and

Analytical Consultingto accelerate adoption

Design, Implement andOperate BusinessIntelligenceCompetency Center

classified into Integration, Intelligence, Insight

BIDW Practice Overview


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Satyam BI/DW SolutionOffering Framework

BIDW Practice Overview

Customers BI ValueFramework

StrategyMittal Steel, EGL, Walgreen, BN,

DHL

Organization &Process

Telstra, Cisco, GECF, GEE

Applications andFunctionalityHLI, J&J, Starhub, CAT, DuPont

BI InfrastructureGECF, Telstra, Cisco, Barclays

ERP CRM SCM Legacy

Intelligence

Integration

Insight

EBS

Depicts Gartners BI Value Framework, SourceGartner Research (April 2004)

BI Solution Centers,PROBIS Program Mgmt.,Six Sigma

Dedicated Business Solutions Group

for Strategy Consulting based in US

Acquisition of Knowledge Dynamics -Consulting Services and Citisoft Investment Banking

Solution Centers large one stopshop for BI & DW. PROBIS uniqueProgram management methodology forBI and Six Sigma

Intelligence includes BI solutions like

Churn, Campaign Mgmt, BAM

Satyams Enterprise Business

Solutions practice (EBS) has strongexpertise in ERP, CRM, SCM a, EAIand BPM solutions.

Dedicated Process Consulting group

for SOX Solutions, Enterprise RiskManagement and BPR

Business Solutions Group,Knowledge Dynamics,

Citisoft &Process Consulting

Insight include Business Analyticsservices like Customer Intelligence,Procurement intelligence.

Integration services are focused ondata modeling, ETL, DB design andother such core DW processes andarchitectures.

Satyam Oracle BI Experience Profile


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Satyam Oracle BI Experience Profile

Influencer Partner of Oracle 125 Skilled Personnel in Oracle BI tools

70 Advanced Experts

35 Experts 20 Intermediate

Expertise in Various tools under the Oracle BI portfolio Oracle Warehouse Builder Oracle Discoverer Desktop Oracle Discoverer Plus

Oracle Portal Oracle EDW Oracle BI Beans Oracle OLAP Server Oracle Financial Analyzer Large Project base worldwide

Worked with various technologies, and businessdomains

Detailed reporting to digital dashboards Implemented defined benchmarks and created the

best practices

OracleBIDiscoverer Plus OracleBI Discoverer

Viewer

OracleBI DiscovererPortlets

OracleBISpreadsheetAdd-in

OracleBI Discoverer Administrator

OracleBI Warehouse Builder

AS10gR2 PortalAS10gR2 BI

OOracleracle BBII PProductroduct AArchitecturerchitecture

Satyam Oracle BI Competency


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Our Alliance with OracleOur Alliance with OracleStrategic Alliance with Oracle and Preferred System Integrator PartnerAccess to Oracle technical support portal to support our Centre of ExcellenceRights to use all Oracle software for competency development and prototypedevelopment

Regular training on all upgrades and fresh releasesLatest software of all the Oracle BI products

Oracle Center Of ExcellenceOracle Center Of Excellence

Our Investments

Infrastructure ( Exclusive servers for multipleinstances)

Dedicated resources at architect level

Rigorous quality checks on project deliverables

Knowledge mgt portal & discussion forums

Conducting Best practice sessions

Tool Benchmarking & feature comparisons

Training and certifications

Benefits to Customers

Improved Productivity and hence lower costs

Reduced cycle times for deployment of solutions

Ensured quality

Proven technical capabilities to demonstrateinnovative solutions and proof of concepts

Reduced risks in technology deployment

Benchmarking of tool capabilities

Satyam Oracle BI Competency

Sample Oracle BI & DW Projects


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Sample Oracle BI & DW Projects

Customer Project description Tools usedA finance major in the US Data Warehouse for consolidating the global

financial dataOFA and Hyperion Essbase on a Sun Solaris

and Unix platform

Insurance major in the UK Planning, projection and modeling system OFA on a Windows NT and Unix platform

Retail major in India Data marts development for all the divisions along

with the deployment of a Managementdashboard

OFA, Oracle Express Objects and Oracle

Express Analyser on Unix platform

3 projects in the Retail sector major in theMiddle East

Data Warehouse implementation OFA and OSA

Telecom major in the Middle East Web-enabled DSS which involves building a DataWarehouse

OFA and OSA

Insurance Major in Japan Finance Data Mart development Discoverer

ISP major in India Data Warehouse implementation Discoverer

Banking Major in India Data Marts for tracking branch performance and foranalysing loan repayments

Oracle Express Server, Oracle Express Objects,Discoverer

Multinational Banking Major in Singapore Data Marts for Sales, Market risk and AssetLiability Management

Discoverer

Healthcare Major in India Enterprise Data Warehouse implementation Oracle Express Server, Express Objects,Express Analyser

Multination Beverages Major in Dubai Sales Data Mart implementation Oracle Express Server, OSA

Telecom Major in India Data Warehouse implementation Oracle Designer, Oracle Enterprise Manager,Discoverer

Logistics Major in Australia Data Marts development for Sales & Marketing,

Finance, Yield Management, Operations andthe final development of a Data Warehouse

OSA, Discoverer, Oracle Warehouse Builder

To know more.


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To know more.

Visit Satyams at Booth No 3548 OracleOpenWorld 2007 in San Francisco.

November 11-15, 2007 @ MosconeConvention Center

www.iDecisions.com

or

[email protected]
http://www.idecisions.com/http://www.idecisions.com/


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