Digital River was dealing with data quality issues due to having commerce data spread across multiple platforms as a result of acquisitions. They addressed this by centralizing all transaction data into a single source of truth enterprise resource planning (ERP) system with the aid of a data governance program. This involved aligning data from different platforms that had various data capture points, workflows, payment methods and terminology. They established a data governance framework based on the Data Management Body of Knowledge (DMBOK) to define governance processes, roles and technology to manage data quality.

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

2. AGENDA

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
3

4. SPEAKER BIO:
4
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 BHASKAR
Sr. Manager, Data Governance, Trillium Product.
Governance and Compliance.

5. COMPANY OVERVIEW
DIGITAL RIVER

6. DIGITAL RIVER
6
Generating Revenue in Virtually Every
Country on the Planet
38 Patents Issued in Commerce,
Marketing and Payments
Technology Pioneer, Founded in 1994
2012 FINANCIAL HIGHLIGHTS
Revenue $386 MILLION
R&D Investment $64 MILLION
Strong Financial Balance Sheet
NASDAQ: 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

7. SIMPILFY THE COMPLEX
Shopping Cart
Export
Compliance
Global Capabilities
Payments, Multi-lingual
Advanced Business Models
Subs, 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

8. UNMATCHED GLOBAL EXPERIENCE AND REACH
8
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

9. DIGITAL RIVER PROMISE
9
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

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.
10
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

11. SERVICES
11
Store
Architecture
Store
Content
Local
Fulfillment
Customer
Service
Subscriptions
Reporting
& Analytics
Locale
Merchandising
Email
Marketing
Search
Optimization
Affiliate
Marketing
Brand
Development
Currency
Pricing
Local/VAT
Tax Support
Global
Processing
Transaction
Routing
Fraud
Screening
Site
Optimization
WORLDWIDE
PAYMENTS
WORLDWIDE
COMMERCE
WORLDWIDE
MARKETING
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

12. 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

13. SOFTWARE &
SERVICES
GAMES AND
ENTERTAINMENT
WORLD-CLASS CUSTOMERS
13
TRAVEL
E-TAIL
EDUCATION
Who We Are Our Focus Our Passion Experience
Consumer
Electronics
Innovation

14. OPEN. MODULAR. ECOSYSTEM
14
Who We Are Our Focus Our Passion Experience Innovation

15. BATCH MODE DATA CLEANSING: CENTRALIZING
COMMERCE DATA
BUSINESS CHALLENGE 1

16. EARLY YEARS (MID-90’S): SINGLE E-COMMERCE PLATFORM
16
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

17. TODAY: MANY CLOUD COMMERCE PLATFORMS (A RESULT OF ACQUISITIONS)
17
Introduction Business Challenge 1 Business Challenge 2 Recommendations Conclusion
E-Com1
E-Com2
E-Com3
E-Com4
E-Com5
E-Com6
E-Com7
E-Com8

18. BATCH MODE DATA CLEANSING: CENTRALIZING COMMERCE DATA
Business Challenge 1
Introduction 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

19. DATA MANAGEMENT ASSOCIATION (DAMA)
Business Challenge 1
Introduction 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

20. DATA MANAGEMENT ASSOCIATION (DAMA)
Business Challenge 1
Introduction 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

21. DATA MANAGEMENT ASSOCIATION (DAMA)
Business Challenge 1
Introduction Business Challenge 2 Recommendations Conclusion
© DAMA-DMBOK2 (Apr 2012)
Data Management Functions Environmental Elements
21

22. WHAT IS DATA GOVERNANCE?
Business Challenge 1
Introduction 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

23. BUSINESS IMPACT/BENEFITS AND RETURN ON OBJECTIVE
Business Challenge 1
Introduction 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 enterprise
23

24. THE DATA MANAGEMENT WHEEL: BINARY VS. TERNARY
Business Challenge 1
Introduction Business Challenge 2 Recommendations Conclusion
 In 2008 embraced DM which meant fundamentally
changing the organizational structure of Digital
River:
IT
Bus
IT
Bus
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

25. ENTERPRISE DATA MANAGEMENT MATRIX ORGANIZATION & ACTIVITIES
Business Challenge 1
Introduction Business Challenge 2 Recommendations Conclusion
Data Management
Data
Governance
Policies and
processes
governing the
management of
the data
environment
Data Quality
People,
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 Warehousing
Integrated environment enabling the implementation of all data rules and processes
Data Stewardship
Organizational resources carrying out and supporting all Data Management activities
25

26. SIMPLIFYING PLATFORMS DOING SIMILAR THINGS
Business Challenge 1
Introduction 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

27. SOLUTION: ERP
Business Challenge 1
Introduction 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

28. SOLUTION: ERP SYSTEM FED BY COMMERCE PLATFORM DATA
Business Challenge 1
Introduction Business Challenge 2 Recommendations Conclusion
ERP
ETL
E-Com1
E-Com2
E-Com3
DATA QUALITY
ERP
ERP
Integration
Structure (ETL)
• Extract
• Transform
• Load
Content (Data Quality Tool)
• Quality Rules
• Governance
• Certification
ERP
DW
BI
REPORTING
Process (ERP)
• Integration
• Productivity
• Controls
Reporting
• Accuracy
• Flexibility
• Scalability
Ancillary systems
ERP
MDM
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

29. THE DATA QUALITY PROGRAM (DQP): PROCESS COMPONENT
Business Challenge 1
Introduction 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

30. DATA QUALITY PROGRAM (DQP FOR ERP): PEOPLE COMPONENT
Business Challenge 1
Introduction 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

31. DQP ROLES
Business Challenge 1
Introduction Business Challenge 2 Recommendations Conclusion
31

32. DQP: ERP IMPACT ASSESSMENT
Business Challenge 1
Introduction 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

33. DQP: ERP CLARIFICATION & REMEDIATION
Business Challenge 1
Introduction 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_type
varchar2 (32 byte)
Visa
payment_id
number (2)
1
pay_method
char (2 byte)
VS
payment_method
varchar2 (32 byte)
VISA
payment_method
Visa
1
VS
payment_method
VISA
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

34. DQP: ERP MONITORING
Business Challenge 1
Introduction 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

35. REAL TIME ADDRESS VALIDATION FOR COMMERCE STORES
BUSINESS CHALLENGE 2

36. THE ON-DEMAND TECHNOLOGY ADVANTAGE
36
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

37. E-COMMERCE TAILORED TO YOUR NEEDS
37
Our 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

38. API FIRST METHODOLOGY
38
Who We Are Our Focus Our Passion Experience Innovation
APIs

39. CLOUD COMMERCE BILLING & SHIPPING ADDRESS ORDER ERRORS
39
Business Challenge 2
Business Challenge 1
Introduction 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.

40. BUSINESS IMPACT/ BENEFITS AND RETURN ON OBJECTIVE FOR RTAV
40
Business Challenge 2
Business Challenge 1
Introduction Recommendations Conclusion

41. DUE DILIGENCE: ADDRESS DATA QUALITY VENDOR REVIEW
41
Business Challenge 2
Business Challenge 1
Introduction Recommendations Conclusion

42. LENGTH OF TIME RTAV HAS BEEN IN PLACE/PROGRAM EVALUATION
42
Business Challenge 2
Business Challenge 1
Introduction Recommendations Conclusion
DQP: HOW RTAV WORKS

43. SCALE OF THE RTAV RELEASE PROCESS SOLUTION (ENTERPRISE)
43
Business Challenge 2
Business Challenge 1
Introduction Recommendations Conclusion

44. DQP: REAL TIME ADDRESS VALIDATION (RTAV)
44
Business Challenge 2
Business Challenge 1
Introduction 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
Data
Stewards
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

45. THE TEAM EVOLUTION: DATA MANAGEMENT AT DIGITAL RIVER (2008-13)
45
Business Challenge 2
Business Challenge 1
Introduction Recommendations Conclusion
Vice President
Operations
Vice President
Strategic
Technologies
Sr. Director
EDM
Data Steward Data Steward Data Steward
Enterprise Data Management Data Governance Steering Committee
Vice President
Operations
Vice President
Finance
Sr. Director
EDM
Vice President
Strategic
Technologies
Vice President
Strategic
Marketing
Vice President
Tax
Vice President
Enterprise Systems
and Data
Management
Vice President
Enterprise Systems
and Data
Management
CFO
Vice President
Strategic
Technologies
Data Steward
Manager
Data Quality
Data Steward
Enterprise Data Management Data Governance Steering Committee
Vice President
Finance
Vice President
Strategic
Technologies
Vice President
Tax
Vice President
Internal
Systems
CFO
Vice President
Internal
Systems
Vice President
Product
Manager
Data Quality
CIO
Vice President
Governance &
Compliance
Sr. Software
Engineer
Sr. Manager
Data Governance,
DQ Tool Product
Manager
Data Steward
ERP
Enterprise Data Management Data Governance Steering Committee
Vice President
Finance
Vice President
Tax
Vice President
Internal
Systems
CFO
Vice President
Internal
Systems
CIO
Vice President
Governance &
Compliance
Vice President
Product
Vice President
Development
CMO
Sr. Manager
Data Governance, DQ
Tool Product Manager
COO
2008
2010
2013

46. OVERALL BENEFITS OF THE DATA QUALITY PROGRAM
46
Business Challenge 2
Business Challenge 1
Introduction 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

47. WHAT OTHER CHANGES COULD POTENTIALLY WORK BETTER?
FURTHER
RECOMMENDATIONS

48. Recommendations
PEOPLE, PROCESS, TECHNOLOGY
48
Business Challenge 1 Business Challenge 2
Introduction Conclusion
>Data Governance need not be invented from scratch:
HR Governance Financial Governance Data Governance
People HR associates
Financial analysts;
accountants
Data Stewards
Process
Human Capital
Management
Finance & Accounting Data Management
Technology HR systems
Accounting systems
(G/L; Tax; Treasury)
Data Quality; MDM; MDR
systems
Functional Programs
Skill set mgmt
Recruiting
Benefits mgmt
Compensation framework
Contractor mgmt
Training
Budget & forecasting
Treasury
Financial reporting
Tax
Investment Mgmt
Data Quality Program
MDM Program
MDR Program
Managed asset Labor force
Financial assets &
liabilities
Data
Policies & Regulations HR policies
SOX, SAS 70, SEC, IFRS,
etc…
Privacy laws; HIPAA; SOX; DM
Policies; etc…
Functional leaders
Training Mgr
Recruitment Mgr
Benefits Mgr
Comptroller
Tax Mgr
Investment Mgr
DQP Mgr
MDM Mgr
MDR Mgr
Process owner VP of HR VP of Finance / CFO
VP of Data Management / CDO
(Chief Data Officer)

49. Recommendations
NEW ORG. ROLES CHIEF DATA OFFICER/VP OF DATA MGMT.
49
Business Challenge 1 Business Challenge 2
Introduction 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

50. Recommendations
EXPANSION OF THE EDM MATRIX ORGANIZATION
50
Business Challenge 1 Business Challenge 2
Introduction 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 MDR
MDM LDM . . .
Program Managers
Senior DM Executives
Data
Stewards
***
DMA** 1
DMA** 2
DMA** 4
DMA** 3
DM Council/
Steering Committee

51. Recommendations
DATA GOVERNANCE SCOPE OF CONTROL
51
Business Challenge 1 Business Challenge 2
Introduction Conclusion
© Copyright Baseline Consulting Group, 2013. Used with permission from SAS Institute.

52. WHAT ARE THE LESSONS LEARNED?
CONCLUSION

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
53
Conclusion
Business Challenge 1 Business Challenge 2 Recommendations
Introduction
Impact
assessment
Identification
IT Bus.
Clarification &
remediation
Monitoring

54. 54
DEEPAK BHASKAR
Sr. Manager, Data Governance, Trillium Product
Governance and Compliance
Digital River, Inc.
http://www.linkedin.com/in/dbhaskar1
DB_2008
dbhaskar03
dbhaskar2008