54
DATA GOVERNANCE & DATA QUALITY PROGRAMS BETTER OUTCOMES, WORTHWHILE CHANGE, FOR ANY ORGANIZATION 6/18/2013 + by Deepak Bhaskar

2013 Data Governance Information Quality (DGIQ) Conference session

Embed Size (px)

DESCRIPTION

Data Governance Information / Data Quality, success stories in Enterprise Data Management

Citation preview

Page 1: 2013 Data Governance Information Quality (DGIQ) Conference session

DATA GOVERNANCE & DATA QUALITY PROGRAMS

BETTER OUTCOMES, WORTHWHILE CHANGE, FOR ANY ORGANIZATION

6/18/2013

+

by Deepak Bhaskar

Page 2: 2013 Data Governance Information Quality (DGIQ) Conference session

AGENDA

Page 3: 2013 Data Governance Information Quality (DGIQ) Conference session

3

AGENDA

Introduction

Speaker Bio

Company introduction

Data issues for our Business:

Challenge 1

Batch mode Data cleansing: Centralizing commerce data in an ERP

DQP in ERP Implementation (Data Discover Profiling & DQ Tool)

Challenge 2

Real Time Data cleansing: Cloud Commerce Billing/Shipping Address Errors

DQP in Real Time Address Validation & Cleansing (DQ Tool & Postal dir.)

Further Recommendations

Conclusion: Digital River Data Governance best practices

Page 4: 2013 Data Governance Information Quality (DGIQ) Conference session

4

SPEAKER BIO:

Introduction Business Challenge 1 Business Challenge 2 Recommendations Conclusion

At Digital River – 10 years

Other roles held: Manager, Enterprise Data Quality, (2008-12) Sr. Strategic Database Analyst, Strategic Marketing (2005-08) Sr. Software Test Engineer, Quality Assurance (2003-05)

Roles held in prior to Digital River include: Lead Test Consultant, (Gelco Info. Network, now Concur Technologies) DBA, (Eschelon Telecom, now Integra Telecom) DBA, Software Developer , Sr. Test Engineer (techies.com) Retail Marketing Associate (Barnes and Noble Booksellers)

Outside of work: Enjoy reading, gardening and DIY home projects, vacationing and foreign travels

DEEPAK BHASKARSr. Manager, Data Governance, Trillium Product. Governance and Compliance.

Page 5: 2013 Data Governance Information Quality (DGIQ) Conference session

COMPANY OVERVIEW

DIGITAL RIVER

Page 6: 2013 Data Governance Information Quality (DGIQ) Conference session

6

DIGITAL RIVER

Generating Revenue in Virtually Every Country on the Planet

38 Patents Issued in Commerce, Marketing and Payments

Technology Pioneer, Founded in 1994

2012 FINANCIAL HIGHLIGHTSRevenue $386

MILLIONR&D Investment $64 MILLIONStrong Financial Balance SheetNASDAQ: DRIV

Invest 3 Million Hours Per Year Focused on Growing Our Clients Revenue

Who We Are Our Focus Our Passion Experience

Managing Over $22 Billion in Annual Online Transactions

Innovation

Page 7: 2013 Data Governance Information Quality (DGIQ) Conference session

SIMPILFY THE COMPLEX

Shopping Cart

Export Compliance

Global CapabilitiesPayments, Multi-lingual

Advanced Business ModelsSubs, Rentals, Points, etc.

Tax & Fraud Management

Compliance (PCI, SOX, SAS, Export)

Marketing and Demand Gen

Store Front

API’s & Integrations

We manage the complexity and risk on a global scale to enable a great user experience

Who We Are Our Focus Our Passion Experience Innovation

7

Page 8: 2013 Data Governance Information Quality (DGIQ) Conference session

8

UNMATCHED GLOBAL EXPERIENCE AND REACH

40

40

30

31

15

localized payment methods

transaction currencies

site display languages

offices across the globe

languages in customer service

Minneapolis • Aliso Viejo • Pittsburgh • Portland • Provo • San Diego • Seattle • Cologne • London • Luxembourg • São Paulo • Shanghai • Shannon • Stockholm • Taipei • Tokyo • Vienna

Who We Are Our Focus Our Passion Experience Innovation

Page 9: 2013 Data Governance Information Quality (DGIQ) Conference session

9

DIGITAL RIVER PROMISE

Unmatched speed to market

19 years of experience

Why world class companies put their trust in Digital River

1,400+ e-commerce experts worldwide

3 million hours a year invested in our client success

Deep understanding of consumer psychology and online behaviors

Manage more than $22 billion in online transactions

Global Demand marketing experts

Over 100 third party relationships

Most complete fraud detection tools in the industry

Who We Are Our Focus Our Passion Experience

“Digital River has been with us step-by-step as we’ve launched online stores. Their technology supports our online commerce capabilities in North America, Europe and Asia, and their marketing solutions help us acquire and retain new customers every day.”

- Lance Binley, Logitech Vice President of Digital and E-Commerce

Innovation

Page 10: 2013 Data Governance Information Quality (DGIQ) Conference session

10

Software and Services: We support the online businesses of some of the most recognized names in the software industry, including Microsoft, Adobe and SAP

Consumer Electronics: We Partner with global consumer electronic manufacturers to help them grow revenue through the direct to consumer channel—Our customers include Samsung, Lenovo, Logitech and others

Games & Entertainment: Enabling consumers across the globe to access their favorite titles immediately through e-commerce customers include Electronic Arts, Ubisoft and Ticketmaster

Education: We help learners take advantage of the benefits associated with online education—customers include University of Phoenix, Kaplan and Barnes & Noble, and many others

Travel: We support some of the travel industry’s leading online sites including Orbitz, Hotels.com and Expedia.

E-tail: Online retailers such as eBay, American Apparel and Mary Kay rely on Digital River to take their products to the online market.

Digital River has helped some of the world’s leading brands build successful online businesses. We focus on global enterprises and SMBs in industries that include:

Who We Are Our Focus Our Passion Experience

MARKETS WE SERVE

Innovation

Page 11: 2013 Data Governance Information Quality (DGIQ) Conference session

11

SERVICES

Store Architecture

Store Content

Local Fulfillment

CustomerService

Subscriptions

Reporting & Analytics

LocaleMerchandising

EmailMarketing

SearchOptimization

AffiliateMarketing

Brand Development

CurrencyPricing

Local/VATTax Support

GlobalProcessing

TransactionRouting

Fraud Screening

SiteOptimization

WORLDWIDE PAYMENTS

WORLDWIDECOMMERCE

WORLDWIDEMARKETING

Who We Are Our Focus Our Passion Experience

Merchant Services

A flexible, expandable e-commerce ecosystem perfectly suited to the needs of your business.

YOUR CUSTOM ECOSYSTEM

Innovation

Page 12: 2013 Data Governance Information Quality (DGIQ) Conference session

PERFORMANCE MARKETING

Who We Are Our Focus Our Passion Experience

12

Marketing expertise to acquire and retain customers.

• Search Engine Marketing services to help create a strategy that maximizes your pay-per-click ad spend

• Display Advertising to drive “eyeballs” to your sites and create the brand awareness needed to compete for market share

• Affiliate Programs and Networks to drive revenue through a community of pay-for-performance publishers

• Site Optimization to make sure customers find their way to your site

• Email Programs that match messages to your customers digital body language

• Advanced Analytics to provide the data points needed to manage key performance indicators

Innovation

Page 14: 2013 Data Governance Information Quality (DGIQ) Conference session

14

OPEN. MODULAR. ECOSYSTEM

Who We Are Our Focus Our Passion Experience Innovation

Page 15: 2013 Data Governance Information Quality (DGIQ) Conference session

BATCH MODE DATA CLEANSING: CENTRALIZING COMMERCE DATA

BUSINESS CHALLENGE 1

Page 16: 2013 Data Governance Information Quality (DGIQ) Conference session

16

EARLY YEARS (MID-90’S): SINGLE E-COMMERCE PLATFORM

Introduction Business Challenge 1 Business Challenge 2 Recommendations Conclusion

At the heart of the web hosting business: The order checkout workflow, which consists of:

Store homepage Product detail Page Shopping cart page Bill to page Ship to page Payment processing page Order confirmation page Thank you page Invoice page

Page 17: 2013 Data Governance Information Quality (DGIQ) Conference session

17

TODAY: MANY CLOUD COMMERCE PLATFORMS (A RESULT OF ACQUISITIONS)

Introduction Business Challenge 1 Business Challenge 2 Recommendations Conclusion

E-Com1

E-Com2

E-Com3

E-Com4

E-Com5E-Com6

E-Com7

E-Com8

Page 18: 2013 Data Governance Information Quality (DGIQ) Conference session

BATCH MODE DATA CLEANSING: CENTRALIZING COMMERCE DATA

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

In 2008 Digital River was dealing with Multiple commerce platforms

Cons:

Inefficient use of Developers and Functional teams Confusion around definition of common terms Inaccurate data being propagated across the systems Longer times to close our books at the end of the month Many manual work efforts

Digital River Solution:

Align all of the platform transaction data, as a Business Imperative with the aid of a Data Governance Program, to support creating a single source of truth (ERP)

Challenges:

Different source data capture points and multiple workflows Different payments methods and fraud rates Similar technology processes performed by different systems Similar business concepts that used many terminologies

18

Page 19: 2013 Data Governance Information Quality (DGIQ) Conference session

DATA MANAGEMENT ASSOCIATION (DAMA)

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

- Data Architecture: as an integral part of the enterprise architecture

- Data Modeling & Design: analysis, design, build, test, deployment and maintain

- Data Storage: structured physical data assets storage management

- Data Security– support ensuring privacy, confidentiality and appropriate access

- Data Integration & Interoperability – support data acquisition, transformation and movement (ETL), federation, or virtualization

- Documents and Content – store, protect, index, and enable access to data found in unstructured sources (electronic files and physical records), and make data available for integration and interoperability with structured (database) data.

- Reference & Master Data – manage gold versions and replicas

- Data Warehousing and Business Intelligence – support managing analytical data processing and enable access to decision support data for reporting and analysis

- Meta-data: integrate, control and deliver meta-data

- Data Quality: define, monitor and improve data quality

DATA MANAGEMENT BODY OF KNOWLEDGE (DMBOK) GOVERNANCE FRAMEWORK

© DAMA-DMBOK2 (Apr 2012)

19

Page 20: 2013 Data Governance Information Quality (DGIQ) Conference session

DATA MANAGEMENT ASSOCIATION (DAMA)

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

DATA MANAGEMENT BODY OF KNOWLEDGE (DMBOK) GOVERNANCE FRAMEWORK

Data Governance:

Involves planning, oversight, and control over data management and use of data

© DAMA-DMBOK2 (Apr 2012)

20

Page 21: 2013 Data Governance Information Quality (DGIQ) Conference session

DATA MANAGEMENT ASSOCIATION (DAMA)

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

© DAMA-DMBOK2 (Apr 2012)

Data Management Functions Environmental Elements

21

Page 22: 2013 Data Governance Information Quality (DGIQ) Conference session

WHAT IS DATA GOVERNANCE?

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

Data Governance has all the characteristics of any Strategic

governance process

Process

People

Technology

Programs Management

Governing body

Procedures

Plan

Decision-making

Business needs

support

Strategy

Assets

Digital River’s definition of Data Governance:-

A set of processes that treats Data as a Strategic Area within the enterprise

(just like Sales, Finance, HR, Sourcing, etc…)

22

Page 23: 2013 Data Governance Information Quality (DGIQ) Conference session

BUSINESS IMPACT/BENEFITS AND RETURN ON OBJECTIVE

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

A mechanism to convert raw Order/Transaction, Customer, Client, Vendor, Product and Other data collected from the shopper websites that we host for our clients, to 2 categories.

Clean Data (passed on to the ERP) Dirty Data (requiring some clarification and remediation)

Digital River’s definition of Data Governance:- A set of processes that treats Data as a Strategic Area within

the enterprise23

Page 24: 2013 Data Governance Information Quality (DGIQ) Conference session

THE DATA MANAGEMENT WHEEL: BINARY VS. TERNARY

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

In 2008 embraced DM which meant fundamentally changing the organizational structure of Digital River:

ITBusITBus

DM

Binary model:No Data Mgmt

IT and Business frictions

Ternary model:Data Mgmt

No IT and Business frictions

DM deployment

The DM is a process “wheel” owned by the Data Stewards

Data Stewards interface with Business and IT Stewards to carry out Data Management activities around remediating the Dirty Data

24

Page 25: 2013 Data Governance Information Quality (DGIQ) Conference session

ENTERPRISE DATA MANAGEMENT MATRIX ORGANIZATION & ACTIVITIES

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

Data Management

Data GovernancePolicies and processes

governing the management of

the data environment

Data QualityPeople,

Processes and Tools involved in

enhancing, measuring, and monitoring data

quality

Master Data Management

People, Processes and

Tools controlling the body of master data

Meta Data Management

Centralization of all data

definitions, relationships,

ownership and identification

ERP & Data WarehousingIntegrated environment enabling the implementation of all data rules and processes

Data StewardshipOrganizational resources carrying out and supporting all Data Management activities

25

Page 26: 2013 Data Governance Information Quality (DGIQ) Conference session

SIMPLIFYING PLATFORMS DOING SIMILAR THINGS

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

E-Com1 E-Com2

- Accounting- Reporting- Billing- Client Management- Tax- Compliance

- Accounting- Reporting- Billing- Client Management- Tax- Compliance

- Accounting- Reporting- Billing- Client Management- Tax- Compliance

Challenge: How can we centralize all of our platforms, creating one true

source for all Accounting, Reporting, Billing, etc?

... E-Com8

Business functions spread across each platform

Decentralized structure

26

Page 27: 2013 Data Governance Information Quality (DGIQ) Conference session

SOLUTION: ERP

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

Commerce would continue to happen on platforms, and transmit to the ERP system in batches of data

Implement an ERP system, sourced from each of the separate e-commerce platforms

E-Com1

E-Com2

E-Com8

SAP - ERP

.

.

.

27

Page 28: 2013 Data Governance Information Quality (DGIQ) Conference session

SOLUTION: ERP SYSTEM FED BY COMMERCE PLATFORM DATA

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

ERPETL

E-Com1

E-Com2

E-Com3

DATA QUALITYERP

ERPIntegration

Structure (ETL)• Extract• Transform• Load

Content (Data Quality Tool)• Quality Rules• Governance• Certification

ERPDW

BI

REPORTING

Process (ERP)• Integration• Productivity• Controls

Reporting• Accuracy• Flexibility• Scalability

Ancillary systems

ERPMDM

ETL drop zone

TSS ®

Stage

.

.

.

> Commerce occurs on platforms, batches of data transmitted to ERP

> DQP RFP: DQP Tool became an integral Technology component of the ERP Implementation

28

Page 29: 2013 Data Governance Information Quality (DGIQ) Conference session

THE DATA QUALITY PROGRAM (DQP): PROCESS COMPONENT

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

Identification

Impact assessment

Clarification & remediation

Monitoring IT Bus.

1. Identification:> Top Data Areas of importance

> Top 5 issues/concerns in Data Areas

> Provide unfiltered dataset to EDM

2. Impact assessment:> EDM loads dataset to TSS for Profiling

> EDM writes up potential Business Rule

> EDM sets up a workshop

3. Clarification & remediation> Data Steward attends Business Rules workshop

> Data Steward clarifies and sign-off Business Rules

> EDM Implement Business Rules

4. Monitoring> EDM builds the Data Quality dashboard

> EDM conducts regular Data Quality compliance monitoring

> Objective:> Improving the Quality of your Data through a strategic framework and a tactical methodology

29

Page 30: 2013 Data Governance Information Quality (DGIQ) Conference session

DATA QUALITY PROGRAM (DQP FOR ERP): PEOPLE COMPONENT

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

>Roles & responsibilities:

> Data Management (DQP Manager, Data Stewards)

> Handle the implementation and regular review of their assigned rules (monthly data quality meetings, rules sign off, Data Quality policy enforcement, etc…)

> Business Owners:

> Own the determination of Business rules. Engage their Data Stewards when an update/new rule is required.

> IT SMEs:

> Build and maintain the interfaces between data consuming systems and the DQP application

Identification

Impact assessment

Clarification & remediation

Monitoring IT Bus.

> Objective:> Centralize the management of quality rules for all enterprise data elements

30

Page 31: 2013 Data Governance Information Quality (DGIQ) Conference session

DQP ROLES

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

31

Page 32: 2013 Data Governance Information Quality (DGIQ) Conference session

DQP: ERP IMPACT ASSESSMENT

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

Attribute Unique Values Min Max Null Dist

% Business Rules

Platform Id 1 GAT GAT 0 Permissible values are GAT, TLA, or GNT. Nulls are not allowed. When the value is TLA, it must be recoded to TA.

Customer Id 37216 742328 2789613 0 Nulls are not allowed. When a value is present, this field is a pass through.Bill To Address Id 39044 4293408 5749721 0 Nulls are not allowed. When a value is present, this field is a pass through.Ship To Address Id 39044 4293408 5749721 0 Nulls are not allowed. When a value is present, this field is a pass through.

Site Id 216 bhaute zitvee 0 No Nulls Allowed. Permissible Value set are determined within ERP (location of master list to be determined)

Site Owner Id 151 bhaute zitvee 0 No Nulls Allowed. Permissible Value set are determined within ERP (location of master list to be determined)

DQP: ERP Clarification & Remediation> DQ Tool Business Rules were recorded in a Business Rule Book

> Each rule was approved and signed off by a Business Steward

> DQ Workshop Document

32

Page 33: 2013 Data Governance Information Quality (DGIQ) Conference session

DQP: ERP CLARIFICATION & REMEDIATION

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

Where do we implement the Business rules?

E-Com1

E-Com2

E-Com3

ERP

DATA QUALITY

ETL drop zone

TSS ®

payment_typevarchar2 (32 byte)

Visa

payment_idnumber (2)

1

pay_methodchar (2 byte)

VS

payment_methodvarchar2 (32 byte)

VISA

payment_methodVisa

1VS

payment_methodVISA

Impact assessment

Identification

IT Bus.

Clarification & remediation

Monitoring

.

.

.

Staging

Each Business Rule is against a column: > If the Payment method column value is: ‘Visa’ , ‘1’ ,

‘VS’

> Then recode the Payment Method column value to ‘VISA’33

Page 34: 2013 Data Governance Information Quality (DGIQ) Conference session

DQP: ERP MONITORING

Business Challenge 1Introduction Business Challenge 2 Recommendations Conclusion

Measures the level of data quality = rate of compliance with business rules (DQ Tool output)

Data Quality is measured monthly, after updates in Business Rules from previous report

Data Stewards responsible for acting on DQ Dashboard metrics

Over 400+ attributes have business rules fired.

Consistently achieving 15-20% increase in the quality of data as a result of data cleansing

34

Page 35: 2013 Data Governance Information Quality (DGIQ) Conference session

REAL TIME ADDRESS VALIDATION FOR COMMERCE STORES

BUSINESS CHALLENGE 2

Page 36: 2013 Data Governance Information Quality (DGIQ) Conference session

36

THE ON-DEMAND TECHNOLOGY ADVANTAGE

Who We Are Our Focus Our Passion Experience Innovation

An Average Day, We Support:

• 1.5+ billion API calls

• Serve 60 million pages

• Send 3+ million emails

• Process 300,000 orders

• Create 5 authorizations/sec

• Host 6+ terabytes of digital content

Industry Leading 99.997% Uptime

Managed to < 40% Utilization

7 Triple Redundant Servers Worldwide

Page 37: 2013 Data Governance Information Quality (DGIQ) Conference session

37

E-COMMERCE TAILORED TO YOUR NEEDSOur partners complement existing systems, address specific technology requirements, and evolve with the market and your growing business over time.

Who We Are Our Focus Our Passion Experience Innovation

Page 38: 2013 Data Governance Information Quality (DGIQ) Conference session

38

API FIRST METHODOLOGY

Who We Are Our Focus Our Passion Experience Innovation

APIs

Page 39: 2013 Data Governance Information Quality (DGIQ) Conference session

39

CLOUD COMMERCE BILLING & SHIPPING ADDRESS ORDER ERRORS

Business Challenge 2Business Challenge 1Introduction Recommendations Conclusion

Incorrect Cloud Commerce Billing and Shipping Address Order Errors Challenges:

Increased Lost / Returned Package costs Incorrect taxation on orders

Cons: Increased customer service costs Unsatisfied customers Loss of products and sales Potential for undetected fraud Many manual work efforts to go around the challenge

Digital River Solution: Digital River implemented Real-Time Address validation

(RTAV). A Data Quality Traffic Monitor/Router and a Data Quality Tool were selected for the RTAV.

Enterprise Software licenses were acquired and Country Postal Templates and Country Postal Subscriptions were subscribed to.

Data Management team was made responsible for the and Data Governance and Data Quality efforts pertain Addresses.

And DQ efforts moved upstream from ERP batch to real-time.

Page 40: 2013 Data Governance Information Quality (DGIQ) Conference session

40

BUSINESS IMPACT/ BENEFITS AND RETURN ON OBJECTIVE FOR RTAV

Business Challenge 2Business Challenge 1Introduction Recommendations Conclusion

Page 41: 2013 Data Governance Information Quality (DGIQ) Conference session

41

DUE DILIGENCE: ADDRESS DATA QUALITY VENDOR REVIEW

Business Challenge 2Business Challenge 1Introduction Recommendations Conclusion

Page 42: 2013 Data Governance Information Quality (DGIQ) Conference session

42

LENGTH OF TIME RTAV HAS BEEN IN PLACE/PROGRAM EVALUATION

Business Challenge 2Business Challenge 1Introduction Recommendations Conclusion

DQP: HOW RTAV WORKS

Page 43: 2013 Data Governance Information Quality (DGIQ) Conference session

43

SCALE OF THE RTAV RELEASE PROCESS SOLUTION (ENTERPRISE)

Business Challenge 2Business Challenge 1Introduction Recommendations Conclusion

Page 44: 2013 Data Governance Information Quality (DGIQ) Conference session

44

DQP: REAL TIME ADDRESS VALIDATION (RTAV)

Business Challenge 2Business Challenge 1Introduction Recommendations Conclusion

E-Com Platform 3

E-Com Platform 2

E-Com Platform 1

ETL

Global Postal Directories

DQP Tool

ERP System

Traffic Router

Real Time Cleansing

Hourly Batch Cleansing Bad Addresses

Bad Addresses

Cleansed Addresses

Clean Addresses

Impact assessment

Identification

IT Bus.

Clarification & remediation

Monitoring

Business Consumers/Owners

IT Owners,Code

Owners,Tech. SME’s

DataStewards

Countries covered• N.America (2)• W. Europe Bundle (16)• LAM Bundle (1)• APAC Bundle (2 Multi-byte,

1 single byte)

Future Expansion• E.Europe

expansion• APAC expansion• LAM expansion

Data Quality & Traffic Monitoring Service• 3 Data Center red.

solution• Load balanced• Code Promotion (Dev,

Sys)..• Platform Release Cycle

Data Quality & Profiling Discovery Tool• 1 Data Center solution with backup• Load balanced• Code Promotion, Dev, Sys, Int, Prod• ERP Release Cycle

Page 45: 2013 Data Governance Information Quality (DGIQ) Conference session

45

THE TEAM EVOLUTION: DATA MANAGEMENT AT DIGITAL RIVER (2008-13)

Business Challenge 2Business Challenge 1Introduction Recommendations Conclusion

Vice PresidentOperations

Vice PresidentStrategic

Technologies

Sr. Director EDM

Data Steward

Data Steward

Data Steward

Enterprise Data Management Data Governance Steering Committee

Vice PresidentOperations

Vice PresidentFinance

Sr. DirectorEDM

Vice PresidentStrategic

Technologies

Vice PresidentStrategic

Marketing

Vice PresidentTax

Vice PresidentEnterprise Systems

and Data Management

Vice PresidentEnterprise Systems

and Data Management

CFO

Vice PresidentStrategic

Technologies

Data Steward

Manager Data Quality

Data Steward

Enterprise Data Management Data Governance Steering Committee

Vice PresidentFinance

Vice PresidentStrategic

Technologies

Vice PresidentTax

Vice PresidentInternal Systems

CFO

Vice PresidentInternal Systems

Vice PresidentProduct

Manager Data Quality

CIO

Vice PresidentGovernance &

Compliance

Sr. Software Engineer

Sr. Manager Data Governance, DQ Tool Product

Manager

Data StewardERP

Enterprise Data Management Data Governance Steering Committee

Vice PresidentFinance

Vice PresidentTax

Vice PresidentInternal Systems

CFO

Vice PresidentInternal Systems

CIO

Vice PresidentGovernance &

Compliance

Vice PresidentProduct

Vice PresidentDevelopment

CMO

Sr. Manager Data Governance, DQ Tool Product Manager

COO

2008

2010

2013

Page 46: 2013 Data Governance Information Quality (DGIQ) Conference session

46

OVERALL BENEFITS OF THE DATA QUALITY PROGRAM

Business Challenge 2Business Challenge 1Introduction Recommendations Conclusion

Data Quality provides - Single, independent environment manages all business rules that ensures data quality for ERP

DQ Traffic Routing Tool and DQ Tool provides the ability to conduct Real Time Address validation for the Commerce platforms and other batch mode cleansing functionality for the ERP

DQP Tool Advantage: When new e-commerce platforms are integrated to the ERP, existing business rules are reused, minimizing redundant development, and centralized management of Business rules

DQP: A 4-step process that requires People, Process and Technology to support our Data Governance efforts

2010 Pitney Bowes Software survey - 2/3 of organizations (revenues > $1Billion), have Data Governance activities underway (including MDM projects)

http://www.information-management.com/newsletters/data_governance_MDM_maturity_ROI-10022164-1.html

Page 47: 2013 Data Governance Information Quality (DGIQ) Conference session

WHAT OTHER CHANGES COULD POTENTIALLY WORK BETTER?

FURTHER RECOMMENDATIONS

Page 48: 2013 Data Governance Information Quality (DGIQ) Conference session

48

Recommendations

PEOPLE, PROCESS, TECHNOLOGY

Business Challenge 1 Business Challenge 2Introduction Conclusion

>Data Governance need not be invented from scratch:HR Governance Financial Governance Data Governance

People HR associatesFinancial analysts;

accountantsData Stewards

ProcessHuman Capital Management

Finance & Accounting Data Management

Technology HR systemsAccounting systems(G/L; Tax; Treasury)

Data Quality; MDM; MDR systems

Functional Programs

Skill set mgmtRecruiting

Benefits mgmtCompensation framework

Contractor mgmtTraining

Budget & forecastingTreasury

Financial reportingTax

Investment Mgmt

Data Quality ProgramMDM ProgramMDR Program

Managed asset Labor forceFinancial assets &

liabilitiesData

Policies & Regulations HR policiesSOX, SAS 70, SEC, IFRS,

etc…Privacy laws; HIPAA; SOX; DM

Policies; etc…

Functional leadersTraining Mgr

Recruitment MgrBenefits Mgr

ComptrollerTax Mgr

Investment Mgr

DQP MgrMDM MgrMDR Mgr

Process owner VP of HR VP of Finance / CFOVP of Data Management / CDO

(Chief Data Officer)

Page 49: 2013 Data Governance Information Quality (DGIQ) Conference session

49

Recommendations

NEW ORG. ROLES CHIEF DATA OFFICER/VP OF DATA MGMT.

Business Challenge 1 Business Challenge 2Introduction Conclusion

CIO / VP Technology

Manager / Director

CDO / VP Data Mgmt.Data

Governance+IT

Governance

Focus: Process Mgmt Focus: Data Mgmt

Data Governed as an Independent Asset

Centralized authority: CDO / VP Data Mgmt.

Improved control over compliance and financial risks

Clear accountability for all aspects of data

Cost reductions from uniform DM processes

Data scalable across the enterprise, and over time (growth, acquisitions…)

Data Management no longer dependent on IT strategy

Cannot be governed Independently

Not managed as a Strategic Asset

Conflict of interests between Technology and Data Management

Difficult to enforce Quality rules across the enterprise

High cost and low returns

Data becomes silo-driven (like IT…)

Responsibility without authority

Page 50: 2013 Data Governance Information Quality (DGIQ) Conference session

50

Recommendations

EXPANSION OF THE EDM MATRIX ORGANIZATION

Business Challenge 1 Business Challenge 2Introduction Conclusion

* Chief Data Officer (typically reports to CTO, CIO, CEO, CMO, CSO) http://en.wikipedia.org/wiki/Chief_data_officer** Data Management Area: typically determined using a Data Consumption Matrix (regularly updated)*** Data Stewards can either belong to the EDMO, remain in their respective DMA, or both.

CDO*

DQ MDRMDM LDM . . .Program Managers

Senior DM Executives

Data

Ste

ward

s **

* DMA** 1

DMA** 2

DMA** 4

DMA** 3

DM Council/Steering Committee

Page 51: 2013 Data Governance Information Quality (DGIQ) Conference session

51

Recommendations

DATA GOVERNANCE SCOPE OF CONTROL

Business Challenge 1 Business Challenge 2Introduction Conclusion

© Copyright Baseline Consulting Group, 2013. Used with permission from SAS Institute.

Page 52: 2013 Data Governance Information Quality (DGIQ) Conference session

WHAT ARE THE LESSONS LEARNED?

CONCLUSION

Page 53: 2013 Data Governance Information Quality (DGIQ) Conference session

53

Data Governance and the DQP: Managed process oversight to

ensure that data-related processes and controls are being followed

Data Governance at Digital River

Is a Strategic and Permanent investment to treat Data as a Strategic Asset

It exists through a functional Enterprise Data Management program

Data Quality Program (DQP)

A 4-step process. Requires People, Process and Technology to support our Data Governance efforts

Reduces Operational costs for order checkout and info. delivery processes

Reduces Risk exposures (financial, regulatory, market and strategic)

Both Require:-

An organizational change to the Ternary model (Business / Data / IT)

A “Data Governor Authority” (e.g. VP of Data Mgmt.) and a dedicated EDM team

Effective use of Data Quality tools (for Profiling, Discovery, Cleansing etc.)

Contrary to many beliefs the Data Quality Tool is NOT a Database

It is a repository of business rules; Rules can be managed and reused.

DATA GOVERNANCE AT DIGITAL RIVER

ConclusionBusiness Challenge 1 Business Challenge 2 RecommendationsIntroduction

Impact assessment

Identification

IT Bus.

Clarification & remediation

Monitoring

Page 54: 2013 Data Governance Information Quality (DGIQ) Conference session

54

DEEPAK BHASKARSr. Manager, Data Governance, Trillium Product Governance and ComplianceDigital River, Inc.

http://www.linkedin.com/in/dbhaskar1

DB_2008

dbhaskar03

dbhaskar2008