Real-Time Analytics on Data in Motion

Analyze More, Speed Actions, Store Less

1

Anand Ladda

Technical Sales Specialist – Streams/BigInsights - Mid-Atlantic Region

For questions about this presentation contact Anand Ladda aladda@us.ibm.com

Agenda

Welcome

Opening Comments / Goals for this presentation

Value drivers for Big Data

Streaming data is the new normal

InfoSphere Streams Overview

Demo

Summary

– Questions, Resources, and Next Steps

2 © 2014 IBM Corporation

Data: To Have and To Hold? Or to Analyze and Act!

Data in

Data at

4

Value Drivers for Big Data

5 5

Data in many forms Variety

Data at speed Velocity

Data at scale Volume

Data as trustworthy Veracity

4 Vs of big data

Scalable / extensible

infrastructure

Scalable storage

infrastructures enable larger

workloads

High-capacity warehouses

support the variety of data

Data integration topped the

data priorities of most

organizations

Agile and flexible infrastructure

Big data landing platform

expands the structured and

unstructured data available for

usage

Real-time analysis processing

enables ‘in the moment’ actions

Trustworthiness is now the top

data priority across majority of

organizations

Source "Analytics: The real-world use of big data. How innovative organizations are extracting value from uncertain data." IBM Institute for Business Value in

collaboration with the Saïd Business School, University of Oxford. October 2012.

6 © 2014 IBM Corporation

Information Management Zones

Actionable Insight

Reporting, Analysis

Data Types

Landing, Exploration,

Archive

Reporting, Interactive Analysis

Deep Analytics, Modeling

Transaction and Application Data

Machine and Sensor Data

Enterprise Content

Social Data

Image and Video

Third-Party Data

Trusted Data, Warehousing

Discovery, Exploration

Decision

Management

Predictive

Analytics, Modeling

Operational Systems

Document Storage

Real-Time Analytical Processing

Governance and Lifecycle Management Fabric Integration | Matching | Masking | Lineage | Security | Privacy | Glossary

Mainframe, Power8, Intel, Cloud (Managed/Hosted), Bluemix Services

Transactional DB

NoSQL Doc Store Hadoop Mixed Workload

RDBMS

Analytic Appliance

Data Mart

Landed

Raw Data

Discovery

Sandbox

Staging

Transformation

© 2014 IBM Corporation 7

No Storage Required

Continuous

In Memory Analytics

Analytics Delivered TO

Streaming Data

Shift from queries to real-time insight in context

Ask

Query

Ask a question

Find the data

Analyze

Store the data

Is the analysis helpful? ???

Traditional Analytics Real-Time Analytics

Fast

8

Streaming data is challenging

2xsSometimes 1 minute is too late. How to quickly process, analyze and act on data? What opportunity are you missing?

Data volumes double every year. Too much to store and then analyze. How to analyze now before insight is lost or forgotten?

Dashboard overload. Too much history and not enough forward thinking. How to get ahead, plan and predict vs react?

Soon there will be 1 trillion connect things. Are you restricting your analytics?

Too much noise. Too much low value data. How to pre-process all data on the fly. Keep only what is valuable.

Minute 1Trillion

Business Need

Connect the right data to the right people in the right context for the right decisions at the right time

9

Operational

Databases

Reporting and

human analysis on

historical data

Analysis of current data

to improve business

transactions

Real Time Analytic

Processing (RTAP) to

improve business

response

Data

Warehousing

Stream

Computing

Data at

rest

1968

Hierarchical

1970

Relational

“System R”

1983

DB2 v1

2009 InfoSphere

Streams

OLTP OLAP

RTAP

More than a Decade Old, InfoSphere Streams Enables Real Time Analytic

Processing (RTAP)

2003

“System S”

10

IBM InfoSphere Streams for Context-Aware Stream Computing

Experience the power of now: secure, continuous, dynamic

Real-Time Action

Context-Aware Analytics

Data

Feedback

& Learning

11

Three core components of InfoSphere Streams

Integrated Development

Environment Scale-Out Runtime Analytic Toolkits

Development and Management Functional and Optimized Flexibility and Scalability

Cloud and on premise available for flexible deployment

Achieve scale:

By partitioning applications into software components

Infrastructure provides services for

Scheduling analytics across hardware hosts,

Establishing streaming connectivity

Where appropriate:

Elements can be fused together

for lower communication latency

Continuous ingestion Continuous analysis

How does InfoSphere Streams work?

© 2013 IBM Corporation 12

13 13

InfoSphere Streams Deployment Options

Your choice of infrastructure and deployment model

IBM Power Intel Servers On Cloud

14

Market leading development environment

Intelligent optimization and centralized

management

Speed time to market.

45% faster delivery

Reduce operational

cost and complexity.

1.5 people manage large

government application

Faster results with a smaller hardware

footprint

InfoSphere Streams delivers superior performance and lowers TCO

Performance advantage increases as scale increases

Run the benchmark to see for yourself https://github.com/IBMStreams/benchmarks

Read Benchmark Results

Read TCO Analysis

Do more with less.

14.2x less hardware resources

12.3x more throughput

Streaming Realtime SmartPhone data with InfoSphere Streams Demo

© 2013 IBM Corporation 15

https://developer.ibm.com/streamsdev/docs/streaming-realtime-smartphone-data-infosphere-streams/

QUESTIONS, AND NEXT

STEPS

Wrap-up slides and helpful links

16 © 2014 IBM Corporation

Get the PDF:

https://www14.software.ibm.com/webapp/iwm/web/signup.do?source=sw-

infomgt&S_PKG=ov28404

Chapter 1: Big Data at Rest and in Motion

Chapter 2: In-Motion Use Cases

Chapter 3: Program, Framework, or Platform

Chapter 4: InfoSphere Streams

Chapter 5: The InfoSphere Streams Ecosystem

Chapter 6: Getting Started

Appendix: Resources and References

What is Streams Quick Start?

• No charge, downloadable edition to allow you to

experiment with stream computing

• No time or data limitations for use on your unique use

cases in non-production systems

• Sophisticated analytics for large data sets - quickly

ingest, analyze and correlate data

• Comprehensive development tools and scale-out

architecture to get up and running quickly, support

available through forums & communities**

Download

Now! ibm.co/streamsqs

Video

Tutorial

InfoSphere Streams Quick Start Edition

Real-time analytic processing at your fingertips

** no formal IBM support is available

VM Ware image & regular install available!!

http://ibmurl.hursley.ibm.com/476B

More than 200 downloads

EVERY WEEK!!

Thousands of downloads

since released in August 2013

18

What is StreamsDev?

Your direct channel to the Streams development team

• Engage across 5 key areas

• Documentation - getting started info, coding

articles and snippets, how to videos and more

• Downloads – links to the latest downloads

• Get help – links to online information and articles,

post questions and get answers

• Blogs - from the Streams’ architects discussing

the latest features and discussions about feature

usage and improvements, we want your input!

• Events- complete calendar

Discuss. Share. Learn.

Join

Now! https://www.ibmdw.net/streamsdev/

InfoSphere Streams Developer Community For Developers, By Developers

19

3500 unique visitors

88+ countries

44 states

Additional resources

InfoSphere Streams website

InfoSphere Streams developerWorks community

InfoSphere Streams Developer Community

InfoSphere Streams data sheet

InfoSphere Streams for industry alignment

InfoSphere Streams youtube channel

20

Thank You

Merci

Grazie

Gracias Obrigado

Danke

Japanese

French

German

Italian

Spanish

Portuguese

Traditional Chinese

Simplified Chinese

Romanian

Multumesc

Turkish

Teşekkür ederim

English

24 © 2014 IBM Corporation