Making Data Science accessible to a wider audience

This document (including, without limitation, any product roadmap or statement of direction data) illustrates the planned testing, release and availability dates for TIBCO products and services. It is for informational purposes only
and its contents are subject to change without notice. © Copyright 2000-2017 TIBCO Software Inc. All rights reserved. TIBCO Proprietary Information.
Making Data Science Accessible to
a Wider Audience
Lou Bajuk-Yorgan, Sr. Director, Product Management
Streaming and Advanced Analytics
TIBCO Software

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TIBCO’s future results or our future financial performance. Although we believe that the expectations reflected in the forward-looking
statements contained in this presentation are reasonable, these expectations or any of the forward-looking statements could prove to
be incorrect and actual results or financial performance could differ materially from those stated herein.
TIBCO could experience factors that could cause actual results or financial performance to differ materially from those contained in
any forward-looking statement made in connection with this presentation. TIBCO does not undertake to update any forward-looking
statements that may be made from time to time or on its behalf.
This document (including, without limitation, any product roadmap or statement of direction data) illustrates the planned testing,
release and availability dates for TIBCO products and services. This document is provided for informational purposes only and its
contents are subject to change without notice. TIBCO makes no warranties, express or implied, in or relating to this document or any
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Multiple paths from Data to Decision and Action
Data Science helps
deliver better
decisions faster

Scarcity of Data Science Skills
Analytical complexity of task and capability of user
Numberofusers
General
Population
Citizen Data
Scientists
(Analysts,
Engineers,
Scientists)
Data Scientists

• Citizen Data Scientist: aspire beyond pretty pictures and
simplistic dashboards
• By 2019, citizen data scientists will surpass data scientists in the
amount of advanced analysis produced.
• By 2020, more than 40% of data science tasks will be automated,
resulting in increased productivity and broader usage by citizen data
scientists.
• This is the trend. How do we make sure people have the the
right tools, to get the right answers?
5
Skeptical about Citizen Data Scientists?
http://www.gartner.com/newsroom/id/3570917

• Pros
• Easy prototyping of new models and analysis
• Huge array of analytic methods available
• The “best” method to solve a given problem is likely available
• Lots of people learning R in university
• Cons
• Performance: Not designed for real time or Big Data applications
• Hard for non-Data Scientist to use directly—exacerbates the Data Science skills
scarcity, by requiring both coding and Data Science knowledge
• Challenging to integrate and manage in enterprise applications
• Performance, commercial support and Intellectual Property concerns
• Result: Compromises which impact Agility
• Recode in a new, less agile environment
• Rewrite, use specialized R packages to solve one problem better
6
Where does R fit in?

TIBCO Analytics Platform
Numerical Models
Analytic Apps MODEL
ACTION
INSIGHT
Business User and Citizen Data
Scientists
• Data Discovery - Insight
• TIBCO Spotfire
Data Scientist
• Analytics - Model
• TIBCO Statistica and TIBCO
Enterprise Runtime for R
Developer
• Real time - Action
• TIBCO Streambase
© Copyright 2000-2017 TIBCO Software Inc.

#1. Smart Visual Analytics Recommendation driven insights
Visual analytics is like a bicycle for
your business mind.

TIBCO Spotfire Mission & Vision
9
S
Help people explore data faster, take action
sooner, and move business further…
A smart, unified, secure analytics experience
to take you & your business into the future

Current Capabilities & Differentiation
10
SIn-built TIBCO®
Enterprise Runtime for
R (TERR™)
Live R computations
Data function modules
vs. No stats
Statisticians only
Instant linked views
Smart Recommendations
Geoanalytics
Analytic applications
vs. Single chart + dashboard
Manual only analysis
Custom development
Analyze & wrangle together
Auto Self-documenting flow
Governable
vs. Separate tools
Must know transforms ahead
Messy, unwieldy models
Linked alerts & actions
Low-code applications
vs. No alerts, no real-
time, no actions
Simple to deploy, admin & scale | Smart distributed memory optimization
vs. Complex deploy, ETL scripting, vertical only scaling

TIBCO Spotfire Visual Analytics
11
• Smart Recommendation-driven
insights
• Multiple dynamic perspectives – no
“old school” single page
• Fastest in and out of memory data
engine for data big and small
• Rich, multilayer, accurate maps
• Threaded, searchable conversations
with annotations and bookmarks
• Easy configured process specific
analytic applications
• Over 40 relational, big data, cloud &
proprietary sources

#2. Numerical Models Analytic Apps

Point and Click Data ScienceS
• Contextual, “one click” calculations
make powerful methods easy to use:
descriptive stats, similarity, clustering,
correlations, fitting, forecast
• Unique commercial engine for R
language
• TIBCO Enterprise Runtime for R
(TERR)
• Any statistic can be part of Spotfire
visual aggregations or expression
language
• Easily leverage the work of your Data
Scientists from R, Statistica, SAS,
Matlab, Python
• Access to Machine Learning, Deep
Learning platforms
• TIBCO Community shares data
science components

Embedded TERR in Spotfire®
Write R code directly in Spotfire;
TERR executes locally or on server
Manage TERR analytics locally or
in Server to reuse across
community
Deploy TERR-powered
applications to the web

Spotfire TERR Data Function
contourLines(x,y)
Draw layers on Spotfire Maps with R/TERR scripts

Power of Embedded Advanced Analytics

TIBCO Spotfire® with H2O Integration
Example: Predictive Analytics for Manufacturing (“scrap parts as early as possible”)

• Comprehensive Stats and Predictive Analytics – Simple UX
• 1000’s of stats, machine and deep learning, Bayesian methods
• Algorithm marketplaces – Azure ML, Algorithmia, Apervita, H2O
• Open source – R, Python, C#, Spark, H2O, CNTK Deep NN
• Data Blending – any data, anywhere
• Model & Rule Lifecycle Management
• Create workspace, manage, version control, deploy, embed
• Citizen Data Scientists – scale best practices with Web UI
• IoT Analytics – device and gateway publish, scoring
• Security & Governance
• Repeatable, auditable; GXP validation : audit logs, version control
• Non-traditional data – image & audio; text mining; Network
Analytics with OrientDB, in-database analytics
18
TIBCO Statistica Analytic Apps

Simple UX for Data Scientist
• Drag-and-drop UI for model + rule creation and deployment
• Simplified data preparation, mash-up, and ETL
• Comprehensive palette of math and analytics
• Machine learning, deep learning, Bayesian methods
• Image, audio, text, Graph-db
• In-db and In-memory algorithms
• Flexible integration with R, Python, Scala, SAS, C++, C#, Java
Model & Rule Management and Deployment
• Metadata repository for model & rule version control, governance,
security and audit trail
• Model version and rule lineage; champion/challenger
• Model & rule publish and embed everywhere
• Publish to TIBCO Streambase for streaming analytics on live data feed
• IoT applications - publish to edge
TIBCO Statistica: Highlights
Business User
Data Scientist
Developer

#3. Streaming Analytics Continuous algorithmic awareness &
automation

Streaming Analytics with Spotfire and TERR
LiveView Dashboard
Spotfire Visualization for context, drill
down for root cause analysis
Real Time Visualizations
Alerting

Streaming Analytics
22
Visual | Powerful | Scalable | Fast | Extensible
Low/no code workflows for
accessing, transforming
and acting on Real Time
Data
Score R models in Real
Time applications using
native TERR node
(+PMML, SparkML, H2O,
etc.)

Spotfire Wiki
community.tibco.com

Spotfire Machine Learning Community
Spotfire (R) Data Functions
• Machine Learning / Deep Learning
• Gradient Boosting
• Random Forests
• Anomaly Detection: Autoencoder
• Segmentation
• Propensity
• Affinity
• Non-Linear Regression; Decline
Curves
• Modeling & Simulation
• Genetic Algorithms
• Optimization

Summary
• More demand than ever for Data Science, with too few skilled Data
Scientists
• Rise of “Citizen Data Scientists”, who need the right tools, guidance and
frameworks
• Importance of leveraging the work of Data Scientists
• TIBCO Analytics:
• Easy to embed/leverage/deploy the work of Data Scientists, from R and
beyond
• In Spotfire Visual Applications, used by business users and Citizen Data Scientists
• In real time applications, to automate decision making
• Easier for Data Scientists to create and reuse predictive analytics in
Statistica
• While leveraging the best of open source R, Python, etc.
• Rich community with examples, reusable assets, etc.
• While maintaining necessary analytic governance and model management

Making Data Science accessible to a wider audience

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