Self-service Analytic for Business Users-19july2017-final

Self-Service Business Analytic
Santisook L.
22 July 2017
DataCube 4th Conference

The Buzz Around Big Data& AI Continues

Focus Has Been on Wrong Issues
Value ?
$

Strategic Planning:
where should we put
our next store?
CEO: how do we
mitigate the risk of
M&A
Merchandizing: are we
pushing the right
products at each store?
Customers: how can I
ensure my profitable
customers don’t churn
Product Strategy: do
we need to acquire or
partner?
CMO: how do I ensure
my social media
investment = sales
Driving more revenue from your
existing business
Expanding your business with
confidence
What are the most important decisions?

Organization target and KPI
Organization
Business
Functional
Target Outcomes
• Company Vision
• Key Markets
• Org structure
• Competitive
differentiation
• Sustainability
• Operational planning
• Business execution
• Resource management
• Departmental
management

What’s Value from Business Perspective

Common Type of Business Analytics
• Reporting : summarize historical data
• Trending : identify pattern in time series data
• Segmentation : identify similarities within data
• Predictive Modeling : prediction future of events
Source: The value of business analytics,Evan Stubbs,Wiley and SAS.

© 2016 Alteryx, Inc. | Confidential Download a FREE Trial: alteryx.com/trial
PROCESS
TOOLS
COMPETENCIES
STRUCTURE
CULTURE
POLITICS
ECONOMY
CUSTOMERS
SUPPLIERS
REGULATION
COMPETITORS
BRAND
MARKET
CHALLENGES
ORGANIZATIONAL
CHALLENGES
TEAM
CHALLENGES
Sources of Challenges for Business Analytic

Top five barriers facing organizations today
Foundational Information Challenges
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

TOP FIVE BENEFITS OF PREDICTIVE ANALYTICS
Achieve competitive advantage 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.
New revenue opportunities
Increased profitability
Increased customer service
Operational efficiencies
Source

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%).
Technical Challenges In Predictive Analytics
Source

Data Science vs People-Process-Technology

Start Business Analytic
Start focus on People…

Empowering the Business Analyst

Business
Knowledge
Skill Required for Data Scientist
Business
Knowledge
Predictive
&
Modeling
Hacking
data Skill
What if Self-service Technology
drive process for People.
DataBlend
&Predictive

Role Core Focus Likely Background Value Provided
Analytics Team Laed Lead the team and define
strategic direction.
Analytics management Ensure value creation and interface with
management.
Advance Analytics Modeler Develop and maintain predictive
models.
Statistics,
business analytics
Deliver insight through predictive models.
Ad Hoc Analytics Analyst Respond to ad hoc queries from
the business.
Reporting Assist the business with ongoing insight.
Domain Expert Provide business-level experience
and acumen.
Business Ensure relevancy of insight.
Data Steward Standardize analytical data and
encourage automation.
Data modeling,
Data warehousing
Minimize data management overhead.
Analytics Process Designer Create and enforce reusable and
common processes.
Management
consulting
Increase repeatability and reduce
execution time.
Monitoring/Validation
Analyst
Establish and enforce common
measures within the
measurement platform.
Performance management/
Finance, business analytics
Measure value and optimize focus.
Deployment Specialist Ensure fast and robust model
deployment.
Data warehousing Reduce time to market and interface
with IT.
Core Roles within and Analytic teams

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.
Enabling The Five Analytic Personas

Business Analysts Can Help Close the Gap
Data Artisan
Capabilities of Data Scientist
that Drive Largest Value Today
Business or Data Analyst

• Line of business focused
• Understands business requirements
• Analytic thinker
• Accesses data, blends
and analyzes
• Drives business change
• Consumes reports, analytic apps,
and
analyst insight
• Shares insights with colleagues,
management, etc.
Data Analyst
Business
Decision Maker
Analytics Must Deliver Business Insight
Through Those Who Know the Business

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Business
Understanding
Data
Understanding
Data
Preparation
Modelling
Evaluation
Deployment
Data Mining Process
Cross Industry Standard Process for
Data Mining
Developed in 1996 by big players
in data analysis
SPSS, Teradata, Daimler, OCHRA, NCR
Most popular methodology for
data-centric projects
See KDNuggets Polls 2007,2014
Agile
Introduces almost no overhead
Emphasizes adaptive transitions
between project phases

Business Understanding
Determine business objectives
Assess situation
Resources (data!), risks, costs & benefits
Determine data mining goals
Ideally with quantitative success criteria
Develop project plan
Estimate time line, budget, but also tools and
techniques
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Business
Understanding
Data
Understanding
Data
Preparation
Modelling
Evaluation
Deployment

Collect initial data
Describe data
Persist results
Explore data
Persist results
Verify data quality
Carefully document problems
and issues found!
Data Understanding
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Business
Understanding
Data
Understanding
Data
Preparation
Modelling
Evaluation
Deployment

Select data
Clean data
Construct data
Generate derived
attributes
Integrate data
Merge information from
different sources
Format data
Convert to format convenient for
modelling
Data Preparation
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Business
Understanding
Data
Understanding
Data
Preparation
Modelling
Evaluation
Deployment

20% 20%
14%
10% 10%10%
Data understanding and preparation will usually consume half or more
of your project time!
What % of time in your data mining project(s) is
spent on data cleaning and preparation?
8%
4%
25%
25%
39%
Percentage of responses
Percentageoftime
Source : M.A.Munson, A Study on the Importance of and
Time Spent Different Modeling Steps, ACM SIGKDD
Explorations Newsletter
13, 65-71 (2011)
Source: KDNuggets Poll 2003
Data Preparation

2-4 Sources
31%
5-10 Sources
40%
11-15 Sources
9% 13%
Over 15 Sources
Only 6%
of organizations
have all their
data in
one place
SOURCE: “Lack of Data Blending Capability is Costing Time and Money” survey of data
analysts
How Many Data Sources do Organizations Use ?

Organizations are Stuck in Excel
Limited Functionality
8% ofWorkforce
26 Hours PerWorker Week
NotAutomated; Not Controlled
80% of Data Input is
Manual Copy / Paste
26 hours
80%
-$60B
5M Advanced Spreadsheet users in US x 8 hours / week
on repetitive manual tasks
Wastes $12,000 per user per year. 1.3B hours/year
Source: IDC

Generate test design
Build model
Feature eng.,
optimize model parameters
Assess model
Iterate the
above
Select modelling technique
Assumptions, measure of
accuracy
Modelling
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Business
Understanding
Data
Understanding
Data
Preparation
Modelling
Evaluation
Deployment

Where your model will be deployed ?
Do you need to distribute your
computations? (avoid!)
C++
Java
C#
R
Matlab
Mathematica
Python
Scala
F# Clojure
Breadth
(quality of general purpose tooling)
Depth
(qualityofdataanalysistooling)
Should I use general purpose language?
Breadth = performance, lots of general
purpose libraries and tooling, easy
creation of web services
Should I use data analysis language?
Depth = easy data manipulation, latest
models and statistical techniques available
Can I afford a prototype?
Modelling-Tooling Selection

Review process
Determine next steps
To deploy or not to deploy?
Evaluate results
Business success criteria fulfilled?
Evaluation
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Business
Understanding
Data
Understanding
Data
Preparation
Modelling
Evaluationn
Deployment

Plan monitoring
and maintenance
Produce final report
Plan deployment
Review project
Collect lessons learned!
Deployment
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Business
Understanding
Data
Understanding
Data
Preparation
Modelling
Evaluation
Deployment

How Self-service Analytic Help
People and Organization

Self-service Data
Analytic Solution
For
Business Users
Self-service
Machine Learning
For
DA or DS.
Self-Service Visual
Analytic
For
Business Users
DataPrep Predictive Visual Analytic

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
Solutions empowers the Business Analyst Answering
the important questions faster & simper

Analytic Consumption is Fragmented
12%
…..of users leverage Alteryx to push to
VisualAnalytics platforms

38
1. Complexity of Analysis
Data Analysts need more power tools
to drive the growing size and number
of data sources in their daily analytic
work.
2. Ease of Use
Alteryx sophisticated data blending
and analytics is easier to use than
most of today’s dashboarding and
reporting tools.
3. Business Benefits
Today’s BI/Analytics tools have failed
to drive business benefits. We are in
rarified air.
Complexity of Analysis
vs. Ease of Use

Single, easy to use workflow for analysts
=
Efficient creation of predictive analysis
and visualization on BI
=
Saves time for analysts & delivers a
more agile business
Build Analytic Workflows With No Coding, No Specialist Tools

It is often said Analysts spend 80% of their time prepping and cleaning data
According to users of Alteryx, Designer cuts data prep by 30% leaving more time for testing hypothesis
and evaluating models
Data Preparation
The Data Preparation palette offers 20 standard tools with a range of capabilities

Many of us face the reality that our data is not stored in just one system. Accessing and
blending that data is just one step in the analytic workflow
With Alteryx Designer, blending data from multiple sources is easily accomplished, regardless
of data structure and format
Data Blending

Predictive analysis is about forecasting events using a range of statistical and machine learning
techniques
By highlighting and extracting certain traits from our data we can identify trends and use these to predict
behaviours which may occur / have occurred in the past, present or future
Predictive Analysis
Alteryx Designer offers over 30 predictive tools based on the R statistical programming language.
Each tool is highly customisable to meet your specific needs

43
Histogram
Frequency
Table
AB Test
Analysis
Market
Basket
Rules
K –Nearest
Neighbor
Example Drag & Drop No Coding Analytics
30+ tools, based on R, for most common
predictive tasks including forecasting, testing,
clustering and decision modeling
Sophisticated Analytics With Simple Drag & Drop UI Add
Forecasting, Clustering etc. to Visualizations

No Coding
Repeatable Workflow
Enterprise scalability
Scale analytics to service users in the
systems/technologies they depend on
Ensure data governance
Ensure data quality by providing transparent
data management and auditability to data
sources, authors and transformation
Eliminate data & analytic silos
Bridge the gap between disparate teams and
departments by collaborating in a secure,
centralized analytic platform
Unlock all your data
Securely connect business users to all data regardless
of source or data type
Automate time-consuming, manual data
tasks, and adjust analytic queries easily
Drag & drop tools using an intuitive user
interface to prep, blend, and analyze data
Platform Differentiation

Platform for Self-Service Data Analytics
Enrich
Prep & Blend Analyze
Input All Relevant Data
Share
Output All Popular
Formats
Descriptive->Predictive

Predictive modeling is slow
because...
Solution
Modelers have to research the right
approaches for solving new problems
DataRobot knows hundreds of
modeling approaches and evaluates
them in parallel
Model validation and model tuning
take a long time to get right
DataRobot automates model validation
in a safe way and tunes models
automatically
Traditional integration approaches are
labor intensive and error prone
An API-based implementation reduces
implementation time from months to
hours
Modelers can only work on a couple of
problems at a time
The modeling API enables modelers to
work on hundreds of problems at the
same time
Can data scientists have more
productivity and business outcome?

$111M+
120+
IN FUNDING
250,000,000+
MODELS BUILT ON
DATAROBOT CLOUD
I N S U R A N C E B A N K I N G H E A L T H C A R E F I N T E C H OIL & GAS
#1 RANKED
DATA SCIENTISTS
4
50+
TOP 3 FINISHES
The world’s most advanced Enterprise Machine Learning platform
DATA SCIENTISTS &
ENGINEERS (OF
200+)
2012FOUNDED
HQ in Boston, MA

Lift Chart Model X-ray
Model Explanation & Selection

Self Services BI : Helps People Understand Their Data

Visual Analytic vs Data Visualization
!=

Visual Analytics Data Visualization
Self-Reliant
Unknown Unknowns Known Unknowns

Visual Analytic
What questions we are going to
ask?
Data Visualization
What chart to visualize
our data?
How to create ABC
reports?
World of wizard
Let’s gather business
requirement
How can I use data to introduce
measurable business benefit?
Transition from insight to action
Let’s brainstorm

Self-service Business Analytic…
Data Analyst
Business
Decision Maker

Increase
Revenue
Compliance &
Risk
Competitive
Advantage
Reduce Cost
Increase
Productivity
USE-CASES AND SUCCESS STORY
www.community.alteryx.com
www.slideshare.net

© 2016 Alteryx, Inc. | Confidential Download a FREE Trial: alteryx.com/trial59
Omid Madadi
Operations Research Developer
Southwest Airlines
“Alteryx is the greatest tool I have ever seen
for data analytics and data preparation.
Also it makes life much easier and it can
save a lot of time by not writing code.”
https://www.slideshare.net/Alteryx/southwest-airlines-empowering-data-users-into-data-
warriors-with-selfservice-analytics-southwest-airlines-inspire-2016?qid=6ef9a65c-7b61-4253-
a45c-41dbadbfac57&v=&b=&from_search=2

Charles Coleman
Senior Analyst
The Home Depot
“With Alteryx, the time to blend sales data
from different stores plummeted from two
weeks to less than one hour almost
instantaneously.”

“It took 100 hours every month to produce
these reports. When I plugged that into
Alteryx, it ran in 5 minutes. It’s probably
my go to tool for everything I do.”
Erik Miller
Sr. Systems Engineer –
Cyber Security Analytics
Western Union

Unilever:
• Successfully cleansed & blended 40+ product formats from 28
countries & numerous languages for a universal view of laundry
demand. Providing insights to 10,000 marketers globally.
CROSSMARK:
• Reduced data prep time from 9+ months to 14 days. The
company now expects to deliver insights to 9x its customer
base, going to 90% from earlier 10%.
“We need Alteryx to take what has happened before and blend it with real-time data from anywhere we can possibly
find it, andTableau to visualize that, so we make better decisions at the right time.”
Ryan Howarth,Global Market Insight & Analytics Manager, Unilever
Move from spending 90% of
your time in data
preparation to 90% in data
analysis and discovery.
Data Discovery
Data Preparation
Without
Alteryx
With
Alteryx
Customers Love Alteryx &TableauTogether

Deeper Insights Hours vs.Weeks Intuitive Workflow
Rosenblatt Securities uses Alteryx to perform sophisticated data analyses for clients,
leveragingTableau Software to visualize the results.
Deliver asset and investment
analysis for visualization in
Tableau at
lower cost and in
less time. Organization
can
scale and be more agile in
serving clients
Simple drag-and-
drop visual
workflow
replaces scripts & coding -
pulling from 7 different
sources, analyzing and
outputting directly toTableau,
Processes move from weeks
down to hours or minutes.
Adhoc client requests
delivered in less
than a minute
63

Southern States Cooperative uses Alteryx to leverage predictive modeling for their
direct mail campaigns to gain better customer reach and targeting.
Predictive Modeling for direct
mailers to customers showed a
10% Redemption Rate &
59% increase
in ROI
for campaigns
Blended Data from
1200+ Retail
Locations
in 23 states, 1,000’s of SKU’s,
Firmographic, Demographic &
CRM Content. Create deep
predictive model using Alteryx
R tools
Southern States created 8
optimized
Campaign using predictive mode
in Hours vs. weeks
each quarter
with average marketing ROI of
186%

Ford Motor Corporation uses Alteryx to blend consumer, dealer and marketing data to
analyze and support their dealer / service center network
100% of dealerships
can accomplish
new car “test drives”
within the allotted time,
saving $30M
in annual testing costs
Blended TomTom road speeds
with millions of rows of data
from
3,200 dealersthen
delivered spatial focused
analytics
Dealer level analysis
between in
18 seconds to
2.5 hrs
65

Experian Marketing Services improve their customer service by empowering line of
business users to blend very large client and Experian datasets independently of IT
Improve response
times
for delivering
enriched client data
by 70%
Preparing and blending
customer files with proprietary
data in
28m+ row
reports
in the business unit
1 Hour
vs.
1 Day

Time Warner Cable Media uses Alteryx to prioritize their content offerings,
while helping their advertisers determine and reach their most likely customers
Advertising Pay PerView
movies and events on networks
that previous buyers watch
drove a
10% increase in
PPV revenue
Blends set-top box data from
7.9 million
subscribers
with ratings, online
transactions and detailed
demographic data
Customized media
proposals can be created
while meeting with clients
in
2 minutes vs. 2
weeks
of manual, repetitive work
67

#inspire15
AnalyticsWithout Limits
Our Businesses Moving Faster

#inspire15
Innovation
Zone
Various data
sources
Rapid Prototyping
and iterative changes
Rapid
Analytics
Delivery
Facilitate 360 views
Data Driven Decisions
Business Owned Innovation: Alteryx and Tableau Platform

#inspire15
Solving Problems Faster
• Resource Optimization
• Ad hoc Reporting
• Data blending and transformation
• Deprecation of custom code
• Geo Coding
• Prototyping
• Logic Consistency
• Data Validation
• What If Testing

#inspire15
• Custom code maintenance eliminated
• Shadow IT tasks no longer needed
Right technology, right fit, right solution: Alteryx + Tableau Platform

#inspire15
• Sample – disparate
data sources
• Deprecate old code
• TDE generates in
minutes
Right technology, right fit, right solution: Alteryx + Tableau Platform

#inspire15
Feedback from our platform users
• “With Alteryx…I feel like I can do anything and then visualize it in Tableau”
• “On average, I am able to get back at least a full day of each week”
• “…the tool is easier, more intuitive and scalable to use (for immediate and
future needs)”
• “I am able to see my results in 30 minutes instead of the 6 hours it used to
take…”
• “Alteryx is allowing me to create prototypes of data sets quickly that allow me
to create a Tableau output for visualizing…”
Our Business Moving Faster

#inspire15
Spread the Word…Collaborate and Share
• Humble beginnings
• Teams curious enough to try
• Field Operations
• Finance
• R&D
• GHE
• New teams reaching out
• RSA
• Presales
Keeping the Momentum Going

#inspire15
Spread the Word…Community
• Meet Ups and
User Forum
• Data Visualization
and Analytics
Conference
• Analytics
Enablement
Center
Keeping the Momentum Going

www.stelligence.com
www.facebook.com/stelligence
@stelligence
Tel : 0 2024 6661
Fax : 0 2513 5755
Contact Us
Thank you

Self-service Analytic for Business Users-19july2017-final

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