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Analytics at Scale: What you

need to know

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Webinar overview

According to a 2014 Forrester survey, you’ve probably found a way to successfully retain and organize your big data, but you’re only analyzing about 12% of it. Imagine all the business value you’re missing in that other 88%.

to discover new ways to effectively analyze all your data, and learn how you can profit from all the actionable business insights you’ll gain.

Fern Halper, TDWI Director of Research, Advanced Analytics Jane M. Hendricks, IBM Portfolio Marketing Manager, IBM Analytics, IBM Predictive Analytics Platform

Available on demand:

Wh

at

Wh

o

Wh

en

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What is analytics at scale?

Organizations need to be able to accommodate

the ever increasing amount of data.

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Coping with the data deluge Data is coming from many sources and is many formats.

Structured Unstructured

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Majority use their data warehouse on structured data

Many use dashboards, visualizations and some

predictive analytics

Big data analysis is not that advanced…

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…but interest in predictive analytics is strong

Analytics poised for growth

49%39% 39%

30% 30%20%

27% 46%35%

39%31%

40%

Time series Predictive Optimization Geospatial Simulation Stream analysis

Now 3 years from now

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What’s the difference between big data and

big data analytics?

Challenge: There can be so much data that performance degrades in traditional modeling environments.

Solution: Organizations need analytics that alter the internal structure of the data without changing its external behavior.

Big Data

Big Data

analytics

Big Data

algorithms

Real time

From untrusted sources

Sometimes dirty

Signal to noise can be low

Programmatic

Data driven

Lots of attributes

Iterative

Refactored algorithms

New algorithms

Analytics closer to the data

Open source: R, Python

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Addressing the Analytical Needs of the Business User

Exploiting Value From the Relevant New Mix of Data

Making Decisions At Point of Impact

Pervasive Analytics for All Problems

Breakthrough Analytics for All Data

Engaging Analytics for Everyone

Three themes are driving the IBM analytics strategy

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Collaboration and Deployment Services

Differentiated Analytic Solutions

IBM SPSS Predictive Analytics Portfolio

Predictive

Maintenance and

Quality (PMQ)

Predictive Customer

Intelligence

(PCI)

Counter Fraud

Management

(CFM)

Custom Applications

Data Collection Statistics Modeler and

ADM

Decision Optimization

Analytic

Server

Watson Analytics

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99%

Acceleration In Uncovering New

Images of

the Universe

1 Exabyte of Data Analyzed Every Day,

Twice the Amount Generated By

Global Daily Internet Traffic

>3,000

Dishes Integrated to Form

the World’s Largest

Radio Telescope

Research institute ASTRON will use streaming analytics to deliver

insight from world’s largest radio telescope

Case study: ASTRON

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View the complete webinar