Peter Sprague, VP of Product Marketing, Pyramid Analytics The Last Mile Implementing Your Data Strategy
Jan 22, 2018
Peter Sprague, VP of Product Marketing, Pyramid Analytics
The Last Mile Implementing Your Data Strategy
Where others see trees, CD&AOs need to see the forest.
• Lead Data Strategy
• Organizational Change Agents
• Open Government Initiatives
Government CDO’s: Many Expectations
The last mile problem…
Legacy systems make this problem much worse.
The organization’s need for:
• Governance
• Compliance
• Transparency
Balanced with users’ needs:
• Agility
• Accessibility
• Self-Direction
All require an analytics strategy.
Build your analytics strategy
around a complete set of shared
enterprise assets. Analytics Repository
An Analytics Repository is Critical to Manage Large Deployments
• Encourage collaboration
• Encourage re-use • Leverage shared organizational logic
• Ensure transparency • Promotes both increased discovery as well as increased trust
Provide for Curated Content
• Both official and self-service content in the same context
• Allow users to understand the source of content
• Seed content for self-service systems
Example: Analytics Repository
Concordia University
Deliver analytics best
practices across the
organization as a service. Analytics-as-a-Service
Analytics-as-a-Service Can Be Transformational
• Accelerate the organization’s analytic maturity
• Make the systems scalable, reliable
• Have your BI resources, IT staff, and business users focused on what they do best
Deploy BI Solution Centers
• Centralize analytics expertise
• Decentralize content creation
• Can also improve and influence the analytics maturity of partner organizations
“Not your father’s BI Center of Excellence.”
Example: Analytics as a Service
Department of Veterans Affairs
ML is another type of
organizational logic that
needs to be integrated.
Operationalized
Machine Learning
Operationalized ML is Critical
• To be useful most algorithms need to be applied at the grain
• End users need to have access to ML algorithms
• ML algorithms need to be a first-class citizen in the analytics repository
Use ML to Realize the Value of Big Data
• ML is the secret to finding the
value in data swamps
• ML and data lake access must be
available to the person that
understands the business
problem—not just those who
understand the technology
• Use in-place analytics to avoid
the “elephant in the room”
Example: Operationalize Machine Learning
Local Paramedics Organization
Summary
Create a separate analytics strategy with:
• A well-managed repository
• Analytics-as-a-Service
• Operationalized ML
Contact Me
Exhibitor’s Table
@petesprague
Peter Sprague
VP Product Marketing Pyramid Analytics