The document discusses managing a heterogeneous business intelligence (BI) landscape. It recommends segmenting the BI landscape based on the types of tools, users, and questions. Enterprise reporting tools should be used for high-quality presentation reporting, department tools for intermediate business questions, and specialized tools for data mining and analytics. Companies should develop a strategic plan to transition their BI landscape, focusing on phased implementations of best-in-class solutions for each segment. The transformation will require changes to technology, roles, and processes, and the plan should aim to deliver value and earn a return on investment.

1. Managing a Heterogeneous BI Landscape
Douglas R. Briggs
Director, Business Intelligence
Washington University in St. Louis

2. Who am I?
• Education:
– BA, Williams College (go Ephs!)
– MS, University of Illinois at Urbana-Champaign
• Business:
– Director of Business Intelligence at Washington University
– 14+ years at Anheuser-Busch Inbev, managing BI and Data
Warehouse support, development, and architecture
– Managing Editor of Data Hub Australia (
http://datatalent.com.au/datahub-australia)
– Advise companies throughout the Midwest on BI & DW matters

3. The place I love to work
• Washington University is:
– Not The University of Washington
– Not George Washington University
• Washington University in St. Louis is (US News & World Report 2014 rankings):
– #14 National University
– #22 Best (Graduate) Business School
– #18 Best Law Schools
– #6 Best Medical Schools: Research
– #5 Best Graduate School: Genetics/Genomics
– #3 Best Graduate School: Physical Therapy
– #2 Best Graduate School: Occupational Therapy
– #1 Best Graduate School: Social Work
• Our mission:
– Washington University’s mission is to discover and disseminate knowledge, and protect the
freedom of inquiry through research, teaching, and learning.

4. … but enough about me, let’s talk about data …

5. Background and Ancient History
• BI used to be done “inside the house”
• As cloud became more viable, more vendors supporting it,
more stuff went into the cloud, including BI!
• Some companies rushed into the cloud, resulting in
– Failure to deliver ROI
– Failure to satisfy user expectations
– Failure to “play nicely” with IT’s other systems
• Cloud got a tarnished reputation, BI seen as risky for
moving “out of the house”
• Now, confusion!

6. Current State
• Companies charting a course that accomplishes three
goals:
– Plan: create a roadmap to a destination that is reachable given
the company’s culture, resources, and landscape
– Deliver: provide safe and robust service where it’s needed
– Earn: Maximize ROI
• How do we do this? We need to know: where is BI now,
and where is it going?

7. A Map of BI Tools & Uses
Mining &
Exploration
Dashboards
Big Data
Ad-hoc
Reporting
&
Analysis
OLAP &
OLTP
Presentation
Quality/"Pixel-
Perfect"
Reporting
Excel-based
Reporting &
Analysis
Narrower Wider
More
General
Questions
More
Focused
Questions
Deployment
Footprint

8. The Natural Partition
• Enterprise-wide reporting solutions:
– High-quality presentation
– Standardized, repeatable processes
• Department-wide reporting
– Intermediate-scope business questions
– Multiple delivery channels
– Parameterization, customized look & feel
• Specialized data tools
– Data mining, powerful analytics, data discovery
– Used by enclaves of power users who know the data intimately

9. Implications
• Vastly different tools for different audiences!
• Single tools can be unsuitable for use across the segments
• You can refocus your landscape on best-in-class solutions
for each segment
• Some vendors have multiple products in their suite that
can work in each segment, but don’t discount niche
players focused on specialized needs

10. Your Challenge
• Remember your goals:
– Create the viable roadmap that gets you from here to there
– Deliver the goods
– Make it pay for itself
• You need the appropriate segmentation between
components that provide the best facility and agility
– Facility = effective feature-set given your institutional needs
– Agility = robust, extensible solution that meets present and future
needs

11. Goals for delivery: safe, robust, accessible
• Safety means all of these things (and more):
– Regulatory compliance
– Data & information protection (including models & algorithms)
– Business process resumption & disaster recovery
• Data governance can help facilitate this
• Credibility is the first casualty if it’s inconsistent or
unscalable
• Delivery at the user-interaction endpoint is tailored

12. Managing the Transformation - Technology
• Rip-out & Replace:
– Focus change and time-box the impact
– Costly, and highest risk for “institutional inertia” to cause delays &
overruns
• Phased:
– Minimize risk and pivot quickly
– Landscape is constantly in flux
– Requires thoughtful landscape architecture & effective
communication to foster credibility!

13. Managing the Transformation - Organizational
• Roles:
– Development & support teams
– May require changes to staff, retraining, or reorganization of
leadership
• Processes:
– Governance, architecture, & business alignment
– Grow it over time, especially if you’re phasing in BI components
– Vendors & integration partners are excellent resources for best-practices

14. Make it Earn its Keep
• Find your partners and advocates
• Select targeted opportunities:
– Short ROI horizons
– Cheap investments with outsized returns
• Handcuff the organization to the results
– Nothing motivates like skin in the game
– Vendors too!

15. Strategies
• Decouple segment-based solutions from each other
• Leverage SaaS paradigms selectively
• Allows departments to build effective point-solutions
• Your landscape will (probably) become heterogeneous
organically – that’s okay.

16. Change is coming …
The vendor offering landscape is (once again) gravitating
toward consolidated solutions
• OLAP à OLTP
• Increasingly sophisticated, presentation-style graphics to
merge traditional dashboards and pixel-perfect reporting
• Hardware acceleration and advanced storage & retrieval is
allowing traditional data discovery and exploration tools to
encroach into the Big Data space

17. Your next steps
• Understand alignment between your current landscape
and the segmentation map
– Talk to your BI architects, they will show you the fit/gap
– Close gaps with effective tool choices & process changes
• Develop the strategic plan, but …
• Make sure you seed the path (especially in the beginning)
with the projects that meet your goals:
– Part of a feasible plan
– Deliver the goods
– Pay for themselves

18. Take-aways
• Natural user & use-case partition à landscape
segmentation
• Best-in-class is a more effective strategy than it’s been for
the past several years
• Expect some solutions to migrate to SaaS organically
• Expect tool consolidation to muddy the waters

19. Questions?
(I have some answers)

20. Please keep in touch!
• My interests and specialties:
– BI competency centers
– Data governance
– BI change management
• Contact:
– douglas.briggs@wustl.edu
– www.linkedin.com/douglasrbriggs

21. Thank you and good luck!

22. Thank you and good luck!

23. Thank you and good luck!