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

© 2013 Ventana Research 1

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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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© 2013 Ventana Research

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



•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%



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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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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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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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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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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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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“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:

http://www.alteryx.com/inspire-2014-home Follow Alteryx on Twitter!

@Alteryx #Inspire14

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Making Predictive Analytics More Accessible to Business Analysts - Alteryx & Ventana Research...

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