1.
Big Data Readiness &
BI Capabilities Matrix
Philadelphia Technology for Value-based Healthcare
Michael Ghen

2.
Overview
Big Data Readiness:
● What is big data?
● Why does it warrant a different approach?
● Rubric
Business Intelligence Capabilities Matrix:
● What is business intelligence?
● Four capabilities
● Measuring BI maturity

3.
“Big Data”
Gartner’s IT Glossary:
Big data is high-volume, high-velocity,
and high-variety information assets
that demand cost-effective,
innovative forms of information
processing for enhanced insight and
decision making.
SAS:
Big data is a term that describes the
large volume of data – both
structured and unstructured – that
inundates a business on a day-to-day
basis

4.
Beyond a marketing definition of “big data”
● Description is not a definition
● Do you really have a “big data” problem?
● Are you really using a “big data” solution?
● Fundamentally:
Big data is about applying innovative and cost effective techniques for solving
existing and future business problem whose resource requirements exceed the
capabilities of traditional computing environments as currently configured
within the enterprise.

5.
Beyond a marketing definition of “big data”
Do you really have a “big data”
problem?
● Are there existing tools available
within your enterprise to solve
the problem?
● Are resources available?
● Is this a local problem or a global
problem?
Are you really using a “big data”
solution?
● Is the solution cost-effective?
● Does it leverage new techniques
and capabilities?
● Does it solve for future business
problems? (local vs. global)

6.
Big Data vs. Small Data
Small Data:
● Electronic medical records from
one hospital
● Single click event from
telemedicine system
● Claims data for patients of a
single insurer
Sample of data
Big Data:
● All EMRs from all hospitals in a
health system
● All user activity from a
telemedicine system
● All payers all claims data
The complete set of all data

7.
Big Data Approach vs. Small Data Approach
Small Data Approach:
● Use the data you can handle
● Sample the data
● Simplify the analysis, make
assumptions
● Solve the local problem
● Use rule-based systems
Analyst’s Approach
Big Data Approach
● Use all the data you can get
● Cleanse the data, focus on data
quality
● Use advanced analysis techniques
● Create global solutions
● Use inferential systems
Scientist’s Approach

8.
What is driving businesses to adopt
big data solutions?
● Increased data volumes being captured and stored
● Rapid acceleration of data growth
● Increased data volumes pushed into the network
● Growing variation in types of data assets for analysis
● Alternative and unsynchronized methods for facilitating data delivery
● Rising demand for real-time integration of analytical results

9.
Lowering the
barrier to entry
● More analytics and
BI tools exist today
than ever before
● Cloud computing
● “Free trials”

10.
Big Data Readiness Assessment
Measures:
● Feasibility
● Reasonability
● Value
● Integrability
● Sustainability
Meaning:
● Are we capable of doing this?
● Do we need to be doing this?
● Will this provide value?
● Can we incorporate this?
● Are we able to keep doing this?

11.
How ready are
you?
Complete the rubric for your
organization
Are you currently explore big data
solutions?
What challenges are you facing as an
organization?
Does your score align with your
challenges?

12.
Feasibility
0 1 2 3 4
Evaluation of new
technology is not
officially sanctioned
Organization tests new
technologies in reaction
to market pressure
Organization evaluates
and tests new
technologies
aftermarket evidence of
successful use
Organization is open to
evaluation of new
technology. Adoption of
technology is on an ad
hoc basis based on
convincing business
justifications.
Organization
encourages evaluation
and testing of new
technology. Clear
Decision process for
adoption or rejection.
Organization supports
allocation of time to
innovation.

13.
Reasonability
0 1 2 3 4
Organization's resource
requirements for near-,
mid-, and long-terms
are satisfactorily met
Organization's resource
requirements for near-,
and mid-terms are
satisfactorily met,
unclear as to whether
long-term needs are
met
Organization's resource
requirements for
near-term is
satisfactorily met,
unclear as to whether
mid- and long-term
needs are met
Business challenges
are expect to have
resources requirements
in the mid- and
long-terms that will
exceed the capability of
the existing and
planned environment
Business challenges
have resource
requirements that
clearly exceed the
capability of the existing
and planned
environment.
Organization's
go-forward business
model is highly
information-centric.

14.
Value
0 1 2 3 4
Investment in hardware
resources, software
tools, skills training, and
ongoing management
and maintenance
exceeds the expected
quantifiable value
The expected
quantifiable value
widely is evenly
balanced by an
investment in hardware
resources, software
tools, skills training, and
ongoing management
and maintenance
Selected instances of
perceived value may
suggest a positive
return on investment
Expectations for some
quantifiable value for
investing in limited
aspects of the
technology
The expected
quantifiable value
widely exceeds the
investment in hardware
resources, software
tools, skills training, and
ongoing management
and maintenance

15.
Integrability
0 1 2 3 4
Significant impediments
to incorporating any
nontraditional
technology into
environment
Willingness to invest
effort in determining
ways to integrate
technology, with some
successes
New technologies can
be integrated into the
environment within
limitations and with
some level of effort
Clear processes exist
for migrating or
integrating new
technologies, but
require dedicated
resources and level of
effort
No constraints or
impediments to fully
integrate technology
into operational
environment

16.
Sustainability
0 1 2 3 4
No plan in place for
acquiring funding for
ongoing management
and maintenance costs.
No plan for managing
skills inventory
Continued funding for
maintenance and
engagement is given on
an ad hoc basis.
Sustainability is at risk
on a continued basis
Need for year-by-year
business justification for
continued funding
Business justifications
ensure continued
funding and
investments in skills
Program management
office effective in
absorbing and
amortizing
management and
maintenance costs.
Program for continuous
skills enhancement and
training

17.
What is Business Intelligence?
Gartner IT Glossary:
Business intelligence is an umbrella term that
includes the applications, infrastructure and
tools, and best practices that enable access to
and analysis of information to improve and
optimize decisions and performance
Sabherwal & Becerra-Fernandez:
Providing decision makers with valuable
information and knowledge by leveraging a
variety of structured and unstructured
information

18.
Data, Information, and Knowledge
Data:
● Facts, observations, or perceptions, which
may or may not be correct
● Represents raw numbers or assertions,
and may therefore be devoid of meaning,
context, or intent
Information:
● Data that possesses context, relevance,
and purpose
Knowledge:
● Justified beliefs about relationships
among concepts relevant to a particular
area

19.
The
Refinery
Analogy

20.
Data, Information, Knowledge, and Decisions

21.
Four Synergistic BI Capabilities
Capabilities:
● Organizational Memory
● Information Integration
● Insight Creation
● Presentation
Description:

22.
How capable
are you?
Complete the rubric for your
organization
Are you doing business intelligence?
How intelligent is your business?
Are you doing analytics or just some
form of pseudo-analytics?

23.
Organizational Memory
Description
● Represents an organization's accumulated
history, including data, information, and
knowledge
● Focuses on the storage of intellectual
sources (data, information, and explicit
knowledge) in such form that they can
later be accessed and used
Capability Matrix Items:
● Operational Databases
● Data Lake
● Data Warehouse
● Data Markets
● Knowledge Repositories

24.
What is a data lake?

25.
Information Integration
Description
● Represents the ability to link past
structured and unstructured content from
a variety of sources that comprise
organizational memory with the new,
real-time, content
Capability Matrix Items:
● Environmental Scanning
● Text Mining
● Web Mining
● Integrating External Structured Data
● Integrating External Unstructured Data
● Integrating Internal Structured Data
● Integrating Internal Unstructured Data

26.
Insight Creation
Description
● Focuses on the utilization of “raw
materials” to produce valuable new
insights and enable effective decisions
making based on continual rather than
periodic analysis.
Capability Matrix Items:
● Data Mining
● Business Analytics
● Real-time Decision Support

27.
Presentation
Description
● The point of contact between BI and the
end user
● Focuses on presenting the appropriate
information in a user-friendly fashion
based on the user's role, the specific task,
and the user's inputs regarding the nature
of the presentation
Capability Matrix Items:
● Enterprise OLAP
● Visual Analytics
● Performance Dashboards
● Scorecards
● Enterprise Key Performance Indicators
● Vigilant Information Systems

28.
Four Synergistic BI Capabilities
Capabilities:
● Organizational Memory
● Information Integration
● Insight Creation
● Presentation
Description: