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Making Predictive Analytics More Accessible to Business Analysts - Alteryx & Ventana Research...
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© 2013 Alteryx, Inc. Confidential.
Making Predictive Analytics More
Accessible to Business Analysts
Matt Madden- Alteryx
Tony Cosentino- Ventana Research
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Tony Cosentino
VP & Research Director, Ventana Research
Tony is responsible for the business analytics research
practice including business intelligence, location intelligence
operational intelligence, and predictive analytics. Tony is
responsible for researching analytics, big data, cloud
computing, business collaboration, mobile technology and
social media.
Tony is an accomplished author with his book titled Into the
River: How Big Data, the Long Tail and Situated Cognition
are the Changing the World of Market Insights Forever. His
work has been published in Business 2.0, Marketing News,
Information Management, SmartDataCollective, and many
other publications.
You can find Tony on Twitter at @tonycosentinovr, via email
at [email protected] or via his blog at
http://tonycosentino.ventanaresearch.com.
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Predictive Analytics Insights from Benchmark Research
Webinar Presentation
Tony Cosentino
VP & Research Director, Business Analytics
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What is
Predictive
Analytics?
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The Ethos of Big Data Analytics
• Moving from 20th to 21st
century analytics:
designed data and
organic data
• Moving beyond internal
and external data silos
• Moving beyond
analytical silos
• Moving from the V’s to
the W’s
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Four Pillars of Big Data Analytics
• Intersection of BDA and
traditional analytics: bringing structured and
unstructured data together
• Visual and data
discovery: exploring data in
many ways
• Predictive analytics: reducing complexity and
broadening scope
• Real-time and right-time
analytics: operationalizing
analytics on an industrial
scale
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Enabling the Five Analytic Personas
A big data foundation must meet
the following roles &
responsibilities: Information Consumers • Digest information and perform basic
interactions
Knowledge Workers • Utilize and interact analytics to drive
actions and decisions.
Designers • Enable the design and use of information
across roles.
Analysts • Mash-up data and design analytics to
provide foundational insights for business.
Data Geek • Enable big data to be exploited in an
immature world through Data Scientists.
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Key Insights into Predictive Analytics
Source: Ventana Research
Predictive Analytics Benchmark Research
•Predictive analytics is very
important to organizations
•Predictive analytics maturity
varies widely among
organizations and people.
•Revenue-generating functions
are primary users of predictive
analytics.
•Various teams handle
implementation of predictive
analytics.
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Key Insights into Predictive Analytics
Source: Ventana Research
Predictive Analytics Benchmark Research
•More timely results, and more
frequently updated models are
needed.
•Inadequate resources and
training for predictive analytics
projects.
•Line of business is funding
predictive analytics projects.
•Organizations expect further
predictive analytics to have a
positive impact.
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Opportunities
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Areas of Opportunity
Marketing Analytics
Human Capital Analytics
Operational Analytics
Risk and Compliance
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Top Five Benefits of Predictive Analytics
Achieve competitive advantage
New revenue opportunities
Increased profitability
Increased customer
service
Operational
efficiencies
68%
55%
52%
45%
44%
Source: Ventana Research
Predictive Analytics Benchmark Research
How has your benefited from predictive
analytics: Related Research Points:
•Management (76%) has no
doubts that predictive
analytics is a top priority.
•Almost two thirds (65%)
of marketing use
today and another
fifth (19%) by end
of 2015.
Key benefits of represent achievement
in the process and using technology.
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Barriers
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Foundational Information Challenges
Top five barriers facing organizations today
Multiple versions of
the truth
64%
Data spread across
too many apps and
systems
67%
Data not timely
enough
60%
Data not clean
enough to use
58%
Technology not
able to meet needs
57%
Source: Ventana Research Information Management Benchmark Research
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Source: Ventana Research
Predictive Analytics Benchmark Research
Technical Challenges in Predictive Analytics
Difficult integrating into our
information architecture
Cannot access the
necessary source data
Results not
accurate
No
challenges
Too hard
to use
55%
35%
22%
20%
18%
What technical challenges have been
encountered in its use of predictive analytics: Related Research Points:
•Midsize (73%) and Very Large
(65%) businesses especially
have difficulty integrating
predictive analytics into their
information architecture.
•Largest barrier to making
changes to predictive analytics
technology is lack of resources
(59%).
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Changing Needs of Buyers
Related research:
• Small companies (83%)
consider usability to be
a very important
consideration.
• Functionality becomes
relatively more
important as company
size increases
Usability
Capability
Reliability
Adaptability
TCO/ROI
Manageability
Validation
Category % selecting
Very Important
70%
60%
58%
47%
47%
33%
26%
Source: Ventana Research Technology Innovation Benchmark Research
User experience and
simplicity is most
critical.
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What To Do Next
Think broadly to educate and specifically to implement (e.g. The V’s, the W’s, 4 Pillars of BDA, Time-to-Value)
Determine use case and best practices; address big data and revenue generating functions
Evaluate the maturity of your organization with respect to People, Process, Information and Technology
Create a cross-functional plan to specifically address skillsets and deployment process and tools
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What To Do Next
In starting out, find resources for deployment and raise awareness about the value of them.
Identify other tools and applications with which predictive analytics should be integrated
Move to more granular models, right-time models, updated models
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© 2013 Ventana Research
Predictive Analytics Insights from Benchmark Research
Webinar Presentation
Tony Cosentino
VP & Research Director, Business Analytics
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© 2013 Alteryx, Inc. Confidential.
Perception of the Immovable Object Between Big
Data, Customer Analytics, and Business Value
CUSTOMER INSIGHT IS FOUND IN MORE PLACES THAN EVER THAT ARE NOT ACCESSIBLE TO THE BUSINESS ANALYST
LONG, MULTI-USER IT ONLY PROCESSES SLOW INNOVATION AND ABILITY TO RESPOND
CODING REMAINS A REQUIRED SKILL FOR ANALYTICS, WHILE DATA PROCESSING JUST TAKES TOO LONG
LEGACY BI PLATFORM DELIVERS SLOW INNOVATION & FAIL THE HARD QUESTION TEST
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© 2013 Alteryx, Inc.
Alteryx’s Mission is To Humanize Big Data and
Empower Data Artisans
Data Artisan
Capabilities of Data Scientist that
Drive Largest Value Today
Line of Business Data or
Business Analyst
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Fastest data
blending in the
hands of the
business analyst
Sophisticated
analytics that are
easier to use: no
coding required
Automatically
share the insight
and foresight of
analytics with
decision makers
Alteryx Empowers the Business Analyst
Answering the important questions faster & simpler
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© 2013 Alteryx, Inc. Confidential.
Utilize &
Integrate any
data source
Ble
nd
Rapid design of
predictive analytics
with unique spatial
understanding
Analy
ze
Share
All Relevant
Data
Enrich
Packaged Market &
Customer Data
Consumerize
the use of
sophisticated
analytics
The Alteryx Solution For Analyst Enablement
Blend, Analyze, Share
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© 2013 Alteryx, Inc. Confidential.
Fastest data
blending in the
hands of the
business analyst
Sophisticated
analytics that are
easier to use: no
coding required
Automatically
share the insight
and foresight of
analytics with
decision makers
Alteryx Empowers the Business Analyst
Answering the important questions faster & simpler
© 2012 Alteryx, Inc. Confidential. 7
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30+ prepackaged R tools to make
predictive analytics accessible in
any analytic workflow
Programmers can write their own
script or incorporate other R script
into the workflow
Making Predictive Analytics Accessible To the Data
Artisan By Bridging the Data Scientist Skills Gap
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© 2013 Alteryx, Inc. Confidential.
Predictive Analytics across the Cycle
Preparation
Investigation
Grouping
Forecasting
Prediction
Missing Data
Binning Data
Data
Descriptions
Impute Values
Multi-Field
Binning
Association
Analysis
Append
Clusters
K-Centroids
Analysis
K-Centroids
Diagnostics
Principal
Components
K-Nearest
Neighbor
Clustering
TS ARIMA
TS Compare
TS ETS
TS Forecast
TS Plot
Future
outcomes over
time
Test of
Means Stepwise Linear
Regression
Score Logistic
Regression
Scoring
Nested
Tests
AB
Treatments
AB
Trends
AB
Controls
AB Test
Analysis Count
Regression
Decision
Tree
Forest
Model
Lift
Chart
Market
Basket
Rules
Market
Basket
Inspect
Testing Modeling
Oversample
Field
Plot of
Means
Field
Summary
Report
Contingency
Table
Frequency
Table
Histogram
Spearman
Correlation
Coefficient
Create
Samples
Pearson
Correlation
Coefficient
Scatterplot
Data
Understanding
Associations
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Demonstration
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Try it yourself..
Download Alteryx Project Edition today to
begin creating your own analysis
www.alteryx.com/download
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© 2013 Alteryx, Inc. Confidential.
“This reminds me of our conference – similar audience passion for analytics and
for the product & company.” Stephen McDaniel, Tableau
Inspire 2014 │Analytic Freedom Learn more:
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@Alteryx #Inspire14