© Copyright 2000-2014 TIBCO Software Inc.

Applying R in Streaming and Business Intelligence Applications

Lou Bajuk-YorganSr. Dir., Product ManagementTIBCO Softwarelbajuk@tibco.com@loubajuk

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Analytic Challenges for Enterprises

• Big Data– More and more data, and the

expectation to do something with it

• Competitive Pressures– Deeper insights into data--Apply

Advanced Analytics– Smarter Decisions--Broaden analytic

usage to wider community beyond Data Scientists

– Faster Decisions—both human and automated

• Agile response to evolving opportunities and threats

– Answers (and the questions to ask) change rapidly

• Agile– Easy prototyping of new

models and analysis

• Deeper insights– Huge array of analytic

methods available– The “best” method to solve a

given problem is likely available

• Performance• Not designed for real time or Big

Data applications

• Broader usage• Hard for non-Data Scientist to use

directly• Challenging to integrate into

enterprise applications • Performance, commercial support

and Intellectual Property concerns

• Compromises which impact Agility• Recode in a new, less agile

environment• Rewrite, use specialized R packages

to solve one problem better

R can help…

…but has it’s own challenges

What would the ideal solution look like?

• A single environment that would allow you to prototype in R, and deploy to production in R– Without recoding, without delay, without compromises– Enable agile response to changing opportunities and threats

Requires• Analytic flexibility, power and breadth of R• High performance, scalable, robust platform• Easy to embed in Business Intelligence, Real time and custom applications• Fully supported for mission critical applications• Allows R users to continue to work in their preferred development environments (e.g.,

RStudio)

TIBCO Enterprise Runtime for R (TERR)

• Unique, enterprise-grade engine for the R language, built from the ground up by TIBCO – Based on TIBCO’s long history and expertise with S+ – Better performance and memory management than open

source R

• Designed for R language compatibility– Wide range of built-in analytic methods– Compatible with thousands of CRAN packages (dplyr,

data.table, etc.)

• Designed for commercial embeddability – TIBCO licensed & supported product – Not GPL, not a repackaging of the Open source R engine

• TERR extends the reach of R in the enterprise– Develop code in open source R– Deploy on a commercially-supported and robust platform– Without the delay and cost of rewriting your code– Embed in Data Discovery, BI and real time applications

Example 1: Embedded TERR in Spotfire

• Spotfire: Data Discovery and Visualization platform for Business Users and Analysts– Separate analytics platform, independent of TERR/R

• Easily enhance Spotfire analyses and applications with R language scripts– Extend the impact of the Data Scientist/R by making their analytic insights available to a wider audience

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

Illustrating the power of embedded Advanced Analytics

Advanced Analytic Applications in Spotfire

Customer Churn: • Retain your most profitable customers• Increase upsell, decrease churn

Fraud Detection: • Reduce losses due to fraudulent

transactions

Supply Chain Optimization: • Anticipate peaks and lulls• Optimize distribution centers

HR Planning: • Predict employee attrition and

optimize retention

• Real-time advanced analytics– Apply predictive model in response to some triggering event

Sensors on industrial equipment trending negative; customer walks into your store or purchases online, etc.

– Trigger the right decision in response Extend a mobile offer to a customer; stop a fraudulent transaction in process; alert the equipment

operator or shut down the equipment

Example 2: TERR and Streaming Data

ModelDevelop model

Deploy via TERR in TIBCO Streambase

ActAutomatically monitor real-time transactionsAutomatically trigger

action

AnalyzeAnalyze data in Spotfire

Uncover patterns, trends & correlations

© Copyright 2000-2013 TIBCO Software Inc.

• Oil & Gas Extraction– Maintenance Downtime and Equipment failures

are costly– Engineers track sensor data to find leading

indicators• Temperature, vibration, etc.

• Engineers usually use ad hoc rules on leading indicators

– R/TERR used to develop predictive models for preventative maintenance

– Deployed in real-time systems, alert when maintenance recommended

Predictive Maintenance for Oil & Gas

• Port Congestion Detection– Real time system triggers TERR– Analyzes port congestion– Recommends reduction of speed if

no berths available

• Maritime Abnormality Detection– Based on Automatic Identification

System info, TERR calculates likelihood of deviation from normal sailing routes

– Alerts carrier & operator

Transportation and Logistics Optimization

Use TERR in your familiar tools

RStudio IDE– Free, open source IDE widely used by the

R Community– Fully compatible with TERR Developer

Edition

KNIME– Free, open source workflow tool for data

management and analysis– TERR fully compatible with KNIME

Interactive R Statistics Integration nodes

TERR is R for the Enterprise

• Develop code in open source R, deploy on commercially-supported, and robust platforms– Without recoding, without compromises– Save time & money, quickly respond to new threats and opportunities

• Tightly & efficiently embed R language functionality

• Extend the power of R to a wider audience, more applications

• TERR Community at community.tibco.com– Resources, Documentation, R compatibility, FAQs, Forums– Predictive Analytics overview and resources

• Free TERR Developer Edition– Full version of TERR engine for testing code prior to deployment– Supported through TIBCO Community, download via tap.tibco.com

• Spotfire Free Trial: http://spotfire.tibco.com/trial

• R Consortium Founding Member  www.r-consortium.org

Learn more and Try it yourself