© 2009 IBM Corporation “The New Intelligentsia” A look at the Landscape in Analytics Ivan O’Dwyer IBM VC Group 15 th December 2009.

© 2009 IBM Corporation

“The New Intelligentsia” A look at the Landscape in Analytics

Ivan O’Dwyer IBM VC Group

15th December 2009

© 2009 IBM Corporation2

Why the spotlight on analytics?

What are the VC’s are telling us? A selection of players

What are the macro technology Trends in Analytics and “Sensemaking” Research

Privacy and Data Protection

Summary

Suggestion

Agenda


Advanced Analytics Focuses on the Prescriptive & Predictive

Degree of Complexity

Com

petit

ive

Adv

anta

ge

Standard Reporting

Ad hoc reporting

Query/drill down

Alerts

Simulation

Forecasting

Predictive modeling

Optimization

What exactly is the problem?

What will happen next if ?

What if these trends continue?

What could happen…. ?

What actions are needed?

How many, how often, where?

What happened?

Stochastic Optimization

Based on: Competing on Analytics, Davenport and Harris, 2007

Descriptive

Prescriptive

Predictive

How can we achieve the best outcome?

How can we achieve the best outcome including the effects of variability?


It’s all about competition!

“Every millisecond gained in our program trading applications is worth $100 million a year.”

Goldman Sachs, 2007 * Source Automated Trader Magazine 2007


What the VC’s are telling us ….


What’s Motivating VC Investment & New Business Models ?

On premise BI is complex, expensive – requires expensive consulting; long implementation cycles; inflexible; limited to large clients who can afford

SMBs / Mid-market have same need for analytics especially in tight economy

Increasing need for non-IT experts to implement simple analytics – easy to build, easy to use

First generation of startup innovation was data warehouse and management appliances – Netezza, Teradata, Greenplum

Second generation of startup innovation is delivering analytics – as-a-service (Saas BI, On Demand BI) -- PivotLink, Birst, Oco, etc.


VC Trends - What are we seeing?

Analytics-as-a-service emerging as a clear and compelling model– Companies across the capability spectrum (including professional services)– Ecosystems – Cloud integrators embracing cloud BI platforms (e.g., Appirio with

PivotLink, Host Analytics)– New kinds of data aggregation and self-service models emerging (public or private cloud

concepts). – AaaS infrastructures can drive/enable more coherent, uniform data models.

Opportunities seen in producing industry-level insights and benchmarks

Many start-ups focusing on on-line business analytics, especially e-commerce-related.

– Combination of traditional analytics capability with SaaS-type delivery models (e.g., RichRelevance working with enterprise-class e-commerce sites like Sears.com, Walmart.com)

Open source tools growing in importance– e.g., Talend, Pentaho, Cloudera (Hadoop-based)– Across the capability spectrum– Often with cloud-type infrastructure, leveraging services-focused models

Unstructured and independent of data warehousing (80% of all NEW Data is Unstructured)

– Potential for a whole new range of applications on the “right” engine– Patient drug interaction and efficacy of trials over time– Every time you skip a track on a CD or Mp3 album


What VC’s are telling us (continued)

Edge device analytics as enabler for new applications. – Enable distributed devices to capture and send data to central analytics engines,

and/or to perform analytics at the edge to send higher-level or highly-enriched information back to central location.

– Examples – SW on mobile devices (CarrierIQ), security systems (many video systems), smart building/home management (Tendril, etc.).

Advanced text analytics poised to bear fruit– Strong area of continued investment. – Companies structured as enabling components with which broader solutions can be

constructed (sentiment, certain kinds of patterns, etc.)

Analytics-based capabilities being targeted to create “Smarter Networks” via centralized and edge-assisted analytics.

– Current mobile networks lack intelligence or consistent data sets to properly monitor, correct, and improve them over time.

– Investment targeted to produce new sources of data, data integration, and analytics that will allow for improvement of telecom network performance and greater end-user satisfaction.


Analytics-As-A-Service Startups

New class of BI startups emerging that are providing end to end analytics as a service: data integration and loading, analytics platform and application

Software is fundamentally simpler and easier to deploy for SMB

Initially targeting the gap between enterprise analytics and end-user (desktop) analytics primarily implemented on Excel; Converting Excel users first.

Initial sweet spot: analytics applications for sales and marketing

For SMBs, rapid time to value – weeks / months vs. years; potentially reduces up to 70% of overall cost of BI *

* “On Demand Business Intelligence Takes Off,” Information Management, Brad Peters, July 7, 2009” (refers to startups implementing integrated Saas BI deployments)

Diagram “Birst Brings Big BI to Business”, Richard Hackathorn, July 10, 2009, Boulder BI Brain Trust Blog


Horizontal Applications

Security / Surveillance (Video

Analytics)Agent Video Intelligence

AxonX

Cernium

Intellio

Mate Intelligent Video

OmniPerception

VideoIQ

Vidient Systems

Energy Analytics & Optimization for

Enterprise

Clear Standards

Optimal Technologies Intl

Planetmetrics

Prenova

Integral Analytics

Tendril

GreenBox

Energy Hub

Risk & Fraud Analytics & Compliance

41st Parameter

E-Glue

eBureau

Guardian Analytics

ID Analytics

Texert

Call Miner

E-Glue

Enkata

HubSpot

KXEN

Lattice Engines

Xtract

Austin Logistics

Clickfox

CRM Analytics


Vertical Applications

Austin Logistics

Derivix

DFA Capital Management

Eagle Eye Analytics

FinAnalytica

Firm58

Mantara

Razorsight

Reval

Valen Technologies

Financial Services & Insurance Analytics

Media & Entertainment

Advertising & Other Analytics33Across

Anvato

Clickable

Crowd Science

Digitalsmiths

MediaBank

Meteor Solutions

Teracent

TubeMogul

Visible Measures

Agilence

Alpha Bay

Dacps Software

IntelliQ

RivalWatch

Searchandise Commerce

Retail Analytics

E-Commerce Analytics

7 Billion People

Bazaarvoice

Infopia

Marketlive

Supply Chain Optimization

Axxom Software

Delfoi

RockBlocks Group

RollStream

ShipLogix

Healthcare / Pharma Analytics

Casenet

DecisionView

HealthDataInsights

Health Monitoring Systems

Logical Images

MedeFinance

Medical Insight


Examples of VC backed emerging companies


Macro Trends in Data andSensemaking Analytics


Next wave content-centric web Apps---Massive Mashups

Semantic Web

Text Analytics, Sentiment Analysis,

Stream Processing Engines

Space Time Travel Data – The SuperFood of Analytics

Context Engines

Sensemaking Infrastructure

Data finding Data …..Relevance finding the User

Agenda


A Yottabyte?

What is a Yottabyte?

1000 GB = 1 Terabyte (TB)1000 TB = 1 Petabyte (PB)1000 PB = 1 Exabyte (EB)1000 EB = 1 Zettabyte (ZB)1000 ZB = 1 Yottabyte (YB)In other words, a Yottabyte = 1,000,000,000,000,000 GB.


Volume of data in enterprises is doubling approximately every three years (Forrester Research)

– Includes structured and unstructured data, excludes rich media

This content is an untapped value for business insights & intelligence

Databases are great when you know what you’re looking for - not so if you’re attempting to discover business opportunities

Frequency of Change Increasing - an enterprise’s ability to capture, warehouse and collect insights from massive amounts of data - quickly & easily - will be disruptive

Success will be measured by enterprises that can slice & dice data into consumable, remixable content for their business ecosystem

Enterprises need to

leverage the broader internet for all relevant

content

• Cross division

• Ecosystem

• User generated

• (News) Feeds

• mySpace

• Facebook

• Twitter

• Audio/Video

• Wikis

• ...

New Class of Analytic Applications to unlock new insight by leveraging Unstructured Information


Macro Trends


What is Stream Processing?

Stream is all about……

– Very complex analytics… on

– Incredible volumes and variety of streaming data.. With

– Sub-millisecond latency and response time.. While

– Data is still in motion… and

– Runs on a wide variety of Hardware Platforms… to

– Provide organizations with a very flexible yet extremely powerful solution to remain highly competitive and productive

InfoSphere Streams is a result of an ongoing software research project at IBM Research known as System S. The System S research is ongoing and will result in additional enhancements to the Streams Platform


Domains for Competitive Advantage

Human Capital

ToolsData

First

FastestSensemaking


Time

Com

pu

tin

g P

ow

er

Gro

wth

Trend: Organizations are Getting Dumber

Sensemaking Algorithms

All Digital Data

Growing Dumber


The Way Forward

Sensemaking Algorithms

All Digital Data

ContextEngines

Time

Com

pu

tin

g P

ow

er

Gro

wth


Introducing … Persistent Context

“Remembering in a database (persistent) how things relate to each other (context).”


Sensemaking

Persistent Context

ContextAnalysis

Relevance Detection

FeatureExtraction & Classification

Publish

Notice Respond


Privacy


“In the Future Everybody will have Privacy for 15 minutes”

Privacy and Space with respect to Space-Time-Travel Data and your mobile

Privacy by Design – The 7 Principles

UK Data Protection Act is nearly 10 yrs old-

To Anonymize or not to Anonymize that is the question.

If we get Privacy right huge benefit accrues

If we don’t get it right …….

“Privacy A Manifesto- Wolfgang Sofsky

Diagram “Birst Brings Big BI to Business”, Richard Hackathorn, July 10, 2009, Boulder BI Brain Trust Blog


A Summary

The convergence of business imperatives, the coming of age of technologies like in line Stream, Semantic Web, massive mahsups, and elastic , price optimized cloud delivery all point to a very exciting few years ahead in analytics. Context accumulation technology is particularly exciting.

Investment dollars are beginning to flow to Analytics-as–a-Service model Startups. We are watching developments here very closely. Better Data models may result from these new types of business models and the effect of social collaboration around them

In Telco Industry analytics around CVM, CEM, SNA , segmentation are beginning to really prove their value but analytics can also be put to good use to operationally optimize many different aspects of Telco Networks and internal processes.

And they said the internet meant location wouldn’t matter anymore! Space- Time –Travel Data is when mashed up with tertiary data will enable a whole range of optimization applications

Privacy remains a concern , but clearly not for everyone. More progress needs to be(and is being) made on the anonymization of analytics. If a company can achieve same results with anonymization than why wouldn’t it make anonomize all of its analytics, and potentially gain a brand/ competitive advantage in doing so…

Data is the only resource mankind has where the act of consumption creates more of the resource.

In the future the data will find that data and the relevance will find the user!


IBM ResearchEntity Analytics

?

IBM VCGroupVF Ventures

VF Research

Service Innovation

Service Creation

Service Integration

ISV’s?

VCC CoE

A Suggestion…..

ISV’s?

Organise a Research Symposium to examine in detail research areas of mutual interest and benefit in Smart Analytics ……aim for Q1 event…Output of event would be collaboration projects to be run by the VCC / SPTC/ CoE’s


Thank You !

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Ivan O’Dwyer IBM VCG [email protected]

© 2009 IBM Corporation “The New Intelligentsia” A look at the Landscape in Analytics Ivan O’Dwyer IBM VC Group 15 th December 2009.

Documents

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simple analytics easy

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