VSP Global, a leading not-for-profit vision benefits company, addresses challenges from data chaos due to growth and acquisitions by proposing solutions to unify data environments. Their envisioned solution includes integrated data management and analytics to improve data quality and delivery efficiency. Key lessons learned emphasize the importance of business participation, governance, and iterative development for successful data strategy implementation.

1. O C T O B E R 1 8 , 2 0 1 6 S A N F R A N C I S C O B A Y A R E A , C A
#DenodoDataFest
RAPID, AGILE DATA STRATEGIES
For Accelerating Analytics, Cloud, and Big Data Initiatives.

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Tim Fredricks
Enterprise Data Architect, VSP Global
Enterprise Analytics and Information Management

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AGENDA
About VSP Global
Problem Definition
Envisioned Solution
Business Benefits
Future Roadmap
Lessons Learned

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ABOUT VSP GLOBAL
Seamless, multi-
channel way for
consumers to engage
professional
optometry for their
eye care and
eyewear, to protect
their vision and
overall health.
Largest national not-
for-profit vision
benefits and
services company.
Connecting 34,000
network providers
and 80 million
members worldwide.
Eyewear frame company
offering winning brands,
including prestigious
fashion and sports
labels, with over 18
million frames sold
annually in over 100
countries.
Ophthalmic
technology, lens
products,
and lab services.
UNITY® is the fastest
growing lens brand in
the industry.
Practice management
and EHR software
solutions that integrate
technology products
and services to
enhance patient care
while streamlining the
everyday complexities
of managing a
business.

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PROBLEM DEFINITION
• Growth, Expansion, Acquisitions created disparate data environments
• Increased interdependence of LOBs requires new perspectives
• Direct to consumer, Omni-Channel initiatives
• Directive: Unification and Shared Consciousness
• Future: Information as a Product

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DATA CHAOS

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ENVISIONED SOLUTION
Data Sources
etc…
Data Integration Data Repository
Batch
Replication
Messaging
Events
Delivery, Presentation
Operational
Analytical
Predictive
Innovative
Provider
Order
Consumer
Other…
LDW
Raw, Relational
Refined, Dimensional
Data Governance – glossary, metadata, lineage, stewardship
SingleAccessPoint
DataVirtualization

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BUSINESS BENEFITS
• Data Analysis vs Data Discovery – time and cost savings
• Consolidated Data Modeling – business view
• Improved Data Quality/Consistency – single source of truth
• Faster delivery, prototyping - define/refine requirements/deliverables
• Single Access Point – analytics and business intelligence

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FUTURE ROADMAP
• Quick Wins for business problems – reinforce value, agility
• Enterprise Domain Models – evolving and complex
• Cross LOB Use Cases – integrated view of data across business areas
• Predictive vs Operational Views – future vs historical

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LESSONS LEARNED
• Business Requirements and Participation are paramount
• Governance, Metadata, and Lineage are critical
• Iterative Releases increase engagement
• Enterprise Data Models are elusive
• Performance and Expectations must be managed carefully

11. Panel
M O D E R A T E D B Y :
Tim Fredricks
Enterprise Data Architect, VSP Global
Rick Hart
Director of Global Technology Solutions,
BioStorage Technologies
Jeff Veis
VP Big Data Platform Marketing,
Hewlett Packard Enterprise
Mike Litzkow
Sales Director, Denodo