ravindranath shenoy bi solution i mplementation roadmap_2014 jul_ieg

Information Excellence informationexcellence.wordpress.com

Harvesting Information Excellence

Information Excellence2014 Jul Knowledge Share Session

Ravindranath Shenoy, GENPACT

BI solution implementation roadmap

Hosted by

Ravindranath Shenoy: IEG Session 2014 Jul

BI solution implementation roadmap

The Business Case, Data Prep, Exploratory Analysis, Modeling, Deployment and Measurement cycle.

Ravindranath Shenoy

3

Ravindranath Shenoy is a seasoned business intelligence architect with strong experience in analytics and building analytics based solutions.

He has contributed in different capacities ranging from BI Solution architect, Analyst and consultant.

Ravi is currently the Senior Manager with GENPACT, leading solution conceptualization and delivery on its customer engagements. He has previously been with Hansa Cequity, Sapient, Nucleus Software building Analytical and BI Solutions and Roadmap.

Ravi is also an avid historian with keen passion about Mughal History and Historical places. He is also a regular in the Marathons in the country.

Ravindranath Shenoy

Senior ManagerGENPACT

Presentation Title Goes Here

Date: April 2013

Implementing an end-to-end BI Solution

Approach to an end-to-end Business Intelligence Implementation

2

Business Analysis

IT Analysis

Solution Roadmap

Solution Design Implement Testing &

Deployment

Source System Analysis

Source System Analysis

Requirement Analysis

Requirement Analysis

KPI & Metrics

Definition

KPI & Metrics

Definition

Technical EvaluationTechnical Evaluation

UnderstandExisting

Architecture

UnderstandExisting

Architecture

Study Existing BI Solution & Process

Study Existing BI Solution & Process

Study Existing DW& Solutions

Study Existing DW& Solutions

Prepare Gap Document

Prepare Gap Document

Draft Solution

Roadmap

Draft Solution

Roadmap

Logical & Physical

Data Model

Logical & Physical

Data Model

ETL DesignETL Design

Report Visualization

Design

Report Visualization

Design

ETL BuildETL Build

Build MetricsBuild

Metrics

Build Reports &

Dashboards

Build Reports &

Dashboards

Layout Process

Maps

Layout Process

Maps

User Training

User Training

Conduct UAT

Conduct UAT

3

Business AnalysisBusiness Analysis IT AnalysisIT Analysis Solution RoadmapSolution Roadmap Solution DesignSolution Design ImplementImplement Test & DeployTest & Deploy

• Met IT team, understood current architecture and as-is landscape

• Understood various data sources and ETL to refresh them• Understood data quality process currently being done and

gaps therein

Infrastructure

• Circulated pre-work survey to gather preliminary information on reports for Reporting teams

• Interviewed each reporting analyst in these teams to complete to collect information on the following for all standard reports

• Key metrics reported• User of Report• Key Data sources used• Tools Used• No. of hours spent on creating the report• Frequency• Reconciliation / Manual Effort • Output format

• Collected a copy of each report• Identified key metrics used in reports• Designed and circulated a user survey for user feedback on

reports

Reporting/Analytics• Metrics-Variables analysis and coming up

with• Common variables• Ordering reports in the sequence of

common variables used• Overlap of common variables and core

variables initially shared during assessment

• Overlap of common variables and score card variables

• Solution roadmap• Detailed plan for the solution

Outputs

4


Select Criteria and required filters

Manually Change Date in SAS / SQL

Integrate numbers

manual copy & paste

Integrate numbers through SAS import or manual copy & paste

Pre-Extraction Sample Validation

Pre-Extraction Sample Validation

Correction for

end data

Correction for discrepancy in back

end data

Calculation of Metrics

Export to Excel and Refresh of

Pivot

Current Reporting Process a generalized view *Data Extraction Time (520 hours, 47%)

SAS / SQL

Queries

BO Reports

Manual Reports

Generate BO Report

Export Export to Text

Database

Excel Cube Access

Database

Copy to Copy to Access

Validation

Reports

Validation against other

Reports

Reconciliation

Groups

Reconciliation with other

Groups

Post Reporting

Resolution

Post Reporting Query

Resolution

Publish Report

Manual Effort Time (581 hours, 53%)

Manual effort spent on Sample Validation and Back end data correction

11

11

11

Effort is spent on Manually changing selection criteria or copy & pasting data for standard reports

22

22

22

22

22

Reconciliation, Validation Time (19%) spent on Reconciliation, Validation and Post Report Query Resolution can be freed up

33

33

33

32 hours of report generation time can be saved by automating report uploads

44

44

22

33

Eliminate through clean data

Eliminate through automation

Reduce through Clean data

Eliminate through automation

5


Ad-hoc analysis

time Savings

Ad Hoc Analysis

Data Extraction Time

Reconciliation & Validation

15%269 Hours

18%312 Hours

Other Manual Effort Time

30%520 Hours

659 Hours

Capacity spent on Standard Reporting1101 Hours

Man

-Hou

rs,%

of C

urre

nt C

apac

ity

This capacity creation can be achieved by Solving the data problem: Establishing a Cleaned up Single Reliable Source of Data and standard data definitions across departments Process Improvement: Improving the overall Reporting Process

15%264 Hours

100%

37% 37%

Ad Hoc Analysis Savings

Data Extraction

Savings

Recon & Val. Savings

Current Capacity (Effort utilized in Std. Reporting & Ad Hoc Analysis)

1760 Hours

100%816 Hours

22%390 Hours

8%135 Hours

9%156Hours

Data Extraction

Savings

Recon. & Val. Savings

Other Manual

Effort Savings

Effort utilized in Std. Reporting & Ad Hoc Analysis

in FUTURE STATE

Total of 945 man-hours or close to six analysts be freed

up per month!

Other Manual Effort Savings

46%

6

Fin 1 src2 src5 src6 src7

Operational Data Store (Oracle)

DOZSRV

Historical Data(SQL Server)

Data Warehouse (SQL Server)

Risk BIU Finance

GLReports

CAD

SASDatasets

AccessCubes

BOReports

Primary Data – “Source Systems”

Intermediate Data Storage

“Data Warehouse”

Reporting Layer

User built Custom Data Sets

Users have built multiple “Custom” Data Sets over time

Current Data Environment is not optimally designed to meet user requirements

Users face ” multiple versions of truth’ in reporting

Day 4

Day 3

src4

Day 8

To

Day 14

Data Availability

This is leading to significant delay in data processing

Other ODS

PRODSRV

Excel ReportsSAS Report

Other Sources


7

Clean Data

Enhance Reporting

• Create a “Single source” Data Mart with:

• Clean and Reconcile Variables

• Faster Data refresh process

• Data dictionary

• Consolidate Reports and improve Reporting Process

• Migrate Reports to the new Data Mart

Clean Data

Enhance Reporting

• Expand the “Single source” Data Mart as required

• Migrate additional Reports as required

• Create new reports to complete KPI coverage /Customer level

Enable Data Analysis

Enable Analytics Projects

• Infuse Analytics Skill

• Train and augment to create Analytics skilled capacity

• Create Analytics Org

Bank wide Analytics led Strategic Projects to drive Revenue Growth & Cost savings

Executives have access to quick and accurate analysis to support Data Driven decision making

Accurate & timely KPIs and the ability to create new & modify reports with changing business needs

Step 1

Step 2

Step 1

Step 4

Step 3

Step 2 contd.

Step 1 contd.

• Clean Data and freed up capacity from Phase 1 will automatically enhance Data Analysis capability

Well designed Data environment is in place supporting all MIS and Analytics requirements


8

src1 src2 src3 src4 src5


DOZSRV

Historical Data(SQL Server)

Data Warehouse (SQL Server)

Risk Sales/Acquisition Finance

Daily Refresh

Monthly Refresh

GLReports

CAD

SASDatasets

AccessCubes

BOReports

Reporting Data Mart

CURRENT STATE END STATE

src1 src2 src3 src4 src5


Daily Refresh

Reporting Interface

Daily/Monthly Refresh

Risk BIU Finance CAD

PRD SRV

BIU Sales/Acquisition

Excel ReportsSAS Reports


9Security for role based access

Operations and Monitoring (data reconciliation) ETL Flow

Query Flow

Peoplesoft

Operational Environment

Persistent Data Store EnvironmentBusiness Intelligence & Analytics Environment

Business Data Store (BDS) for Operational Reporting – 3 months

Integration By CS subject areas

Data Marts Layer- 2 years

(Phase1)

Staging layer

Land

ing

Zone

(for

fla

t file

s)

Raw DataFrom Source

Data WarehouseDimensional- 5 years

eWFM

IBS

IVR

ACD

SlowlyChangingDimensions,Reference/LookupAnd Fact Tables With Base Metrics

This image cannot currently be displayed.

• KPI’s• Scorecards • Dashboards

SS

IS E

TL fo

r lo

adin

g &

inte

grat

ion

ODSSystemsIntegrationAdapters

SiyanDiza

Qfinity

DGVM

Dialer

eGain

SS

IS B

asic

Val

idat

ion

chec

ks a

nd E

rror

Han

dlin

g

Error Reporting

Validated Source Data

360 CSRView

CustomerInteractions S

SIS

ETL

(Tra

nsfo

rmat

ion

)

ACD

MasterData

• Schema and Application Objects to connectto BDS/DW/DM

BI Semantic Layer and Delivery Platform (Reports, Dashboards And Analytic Applications)

• Standard/AdhocReporting

• Self Service Reporting

• Boardpack• Dashboards

Reports& Analysis

Integration

Adhoc/Self Service Power Users

Standard Report Consumers

Analytical Users

SS

IS E

TL (B

usin

ess

Map

ping

Rul

es fo

r der

ived

m

easu

res,

agg

rega

tes

and

sna

psho

ts)

Aggregate tablesand MSTR Cubes

DataWarehouse

DataMarts

9

Qmatic

CDI

(Phase 2)

IBS

Excel


10


Identify & Define Business MetricsIdentify & Define Business Metrics

Identify & Study Data sources thatfeeds into these metrics

Identify & Study Data sources thatfeeds into these metrics

Profile the dataProfile the data

Model Staging & DWModel Staging & DW

Model DMModel DM

Reports DesignReports Design

11


Project PlanProject Plan

Project TrackerProject Tracker

Deployment DocumentDeployment Document

Thank you..

12

Community Focused

Volunteer Driven

Knowledge Share

Accelerated Learning

Collective Excellence

Distilled Knowledge

Shared, Non Conflicting Goals

Validation / Brainstorm platform

Mentor, Guide, Coach

Satisfied, Empowered Professional

Richer Industry and Academia

About Information Excellence Group

Progress Information Excellence

Towards an Enriched Profession, Business and Society

About Information Excellence GroupReach us at:

blog: http://informationexcellence.wordpress.com/

presentations: http://www.slideshare.net/informationexcellence

linked in:http://www.linkedin.com/groups/Information-Excellence-3893869

Facebook:http://www.facebook.com/pages/Information-excellence-group/171892096247159

Google+: https://plus.google.com/u/0/communities/102316155996060621595

twitter: #infoexcelemail: [email protected]

[email protected]

Have you enriched yourself by contributing to the community Knowledge Share..

ravindranath shenoy bi solution i mplementation roadmap_2014 jul_ieg

Data & Analytics