The document discusses the journey organizations take to establish trusted data through effective data management. It outlines common barriers to coordinating data initiatives and how the gap between IT and business needs can be closed. A maturity model is presented showing how organizations evolve their data practices from being IT-driven to enabling personalized customer experiences. The key is establishing repeatable processes through a single data management platform that provides data quality, integration and master data management capabilities.

1. “The Journey to Trusted Data”
Saul Cunningham
DataFlux ANZ General Manager
10 March 2011

2. Welcome
Saul Cunningham
Managing Director, DataFlux ANZ
2

3. Where are you on your data journey?
3

4. Planning is the Key
4

5. The Evolution of Data Awareness
5

6. The Current State of Data Management
The top four potential barriers to coordinating data management initiatives
6

7. The Data Disconnect
7

8. Understanding the Gap
IT Drivers for Data Management Business Drivers for Data Management
•Back Office Applications •Front Office Applications
•IT Infrastructure •Customer Oriented
•Operational Efficiency •Revenue Generation
•Proven Technologies •Leading Edge Technologies
•Methodical in Approach •Process Oriented
8

9. Closing the Gap
It’s a question of ownership It’s a question of sponsorship
•Business owns the processes •Organisations can place a value on
•IT owns the systems almost all assets (buildings,
machinery, employees, bandwidth)
•Data is, at its core, viewed by the
business as a by-product of IT assets
It’s a question of technology
adoption
•Traditional data management
capabilities are lacking
•Right technology at the right time

10. The Data Governance Maturity Model
Sales Force Data Warehouse Customer MDM Business Process
Automation Product MDM Automation
ERP Materials MDM
Database Marketing Employee MDM
CRM Asset MDM MDM
IT-driven Line of business IT and business Business
projects influences IT projects groups collaborate requirements drive
IT projects
Duplicate, Little cross-functional Enterprise view of Repeatable, automated
inconsistent data collaboration certain domains business processes
Inability to adapt to High cost to maintain Data is a Personalized customer
business changes multiple applications corporate asset relationships and
optimized operations

11. Establish Repeatable Processes

12. Our Mission
Your Data. Your Business. One Solution.
DataFlux enables business agility and IT efficiency by providing
innovative data management technology and services that
transform data into a strategic asset.

13. DataFlux - Proven Market Leader in Data
Management
• Recognised as a leading provider of
data quality, data integration and
MDM solutions
• Over 2300 customers worldwide
• Been in the leadership position
within the Gartner DQ MQ since
2006
• Single home grown platform
providing DQ, DI and MDM
capabilities
• Wholly owned subsidiary of SAS

14. DataFlux – one solution with broad application across
your business
“It’s like having a “Swiss Army knife” suite of tools
to characterise, clean, integrate and monitor the
quality of BP’s data.”
Ken Dunn (BP Data Architecture Manager)
14

15. Scenario 1: Business Reporting
Data Warehouse
Business Intelligence
? The “classic” use of Data Quality
? Access and integrate data in batch & real-time for
DW /
DW /
analytics DM
DM
? Apply Data Quality business rules to ensure trusted
data for reporting - improve User confidence in the Batch DQ
data
DataFlux DQ
Platform
Real-time DQ Data
Data
Legacy
Legacy Mart
Mart
Systems
Systems
Application
Systems

16. Scenario 2: Business Process Improvement
Ensuring quality information at User interface
? Improve data quality at the “Point of data entry” into
your Enterprise Applications
? Eliminates duplicate data entering the system
? Data quality management over the life of an ERP/CRM
system
DataFlux
DataFlux
Quality
Quality
Firewall
Firewall
Business Users DataFlux DQ Enterprise
Enterprise
Platform Applications
Applications

17. Scenario 3: Reduce Risk in Data Migrations
Data Migrations
? Migrate cleansed and standardised legacy application
data into new or upgraded Enterprise Application
? Reduce risk and ensure timely delivery of application
go-live
? Monitor DQ issues during Data Migration process to
increase confidence for key stakeholders
ERP/
ERP/
CRM
CRM
DataFlux DQ
Platform
Legacy
Legacy
Systems
Systems
New Enterprise
Legacy Systems
Application

18. Scenario 4: Data Governance process
Data Governance Enterprise
Apps
? Meet compliance requirements with ability to trace
and audit data
? Consolidate enterprise data to establish a single
version of customer, product or employee
Business
Users
DataFlux DQ
Platform
Legacy
Legacy
Systems
Systems
Application MDM
Systems

19. Questions?

20. • Improve Business User productivity with
ease of use and process reuse and
sharing for collaboration
• Helps Users make decisions
with confidence using trusted
information
• Flexibility to scale from small
pilot projects to enterprise-wide
deployments
• Reduce costs and Total
Cost of Ownership with a
single easy-to-use product
solution
• Flexibility to support multiple data types
and emerging technologies such as SOA
and Web Services

21. Conceptual View of Master Data Management
Data Profiling
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Business Rule Definition
Entity Definition
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Data Quality
Data Model
Business Services
Stewardship Console
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Apex Construction | Newcastle NSW
Identity Management
Reporting