ivan o dwyer ibm vc group 15 th december 2009 l.
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Ivan O’Dwyer IBM VC Group 15 th December 2009. “The New Intelligentsia” A look at the Landscape in Analytics . Agenda. 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

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slide2

Agenda

  • 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
advanced analytics focuses on the prescriptive predictive

Stochastic Optimization

Optimization

Predictive modeling

What will happen next if ?

Forecasting

What if these trends continue?

Competitive Advantage

Simulation

What could happen…. ?

Alerts

What actions are needed?

Query/drill down

What exactly is the problem?

Ad hoc reporting

How many, how often, where?

Standard Reporting

What happened?

Degree of Complexity

Advanced Analytics Focuses on the Prescriptive & Predictive

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

Prescriptive

How can we achieve the best outcome?

Predictive

Descriptive

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

it s all about competition
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 s motivating vc investment new business models
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
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-levelinsights 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
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
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 *

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

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

horizontal applications
Horizontal Applications

Security / Surveillance (Video Analytics)

CRM Analytics

Energy Analytics & Optimization for Enterprise

Risk & Fraud Analytics & Compliance

Call Miner

E-Glue

Enkata

HubSpot

KXEN

Lattice Engines

Xtract

Austin Logistics

Clickfox

Agent Video Intelligence

AxonX

Cernium

Intellio

Mate Intelligent Video

OmniPerception

VideoIQ

Vidient Systems

Clear Standards

Optimal Technologies Intl

Planetmetrics

Prenova

Integral Analytics

Tendril

GreenBox

Energy Hub

41st Parameter

E-Glue

eBureau

Guardian Analytics

ID Analytics

Texert

vertical applications
Vertical Applications

Financial Services & Insurance Analytics

Media & Entertainment Advertising & Other Analytics

Retail Analytics

Agilence

Alpha Bay

Dacps Software

IntelliQ

RivalWatch

Searchandise Commerce

Austin Logistics

Derivix

DFA Capital Management

Eagle Eye Analytics

FinAnalytica

Firm58

Mantara

Razorsight

Reval

Valen Technologies

33Across

Anvato

Clickable

Crowd Science

Digitalsmiths

MediaBank

Meteor Solutions

Teracent

TubeMogul

Visible Measures

E-Commerce Analytics

7 Billion People

Bazaarvoice

Infopia

Marketlive

Healthcare / Pharma Analytics

Casenet

DecisionView

HealthDataInsights

Health Monitoring Systems

Logical Images

MedeFinance

Medical Insight

Supply Chain Optimization

Axxom Software

Delfoi

RockBlocks Group

RollStream

ShipLogix

slide14

Agenda

  • 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
a yottabyte
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.
slide16
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

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

Enterprises need to leverage the broader internet for all relevant content

  • Cross division
  • Ecosystem
  • User generated
  • (News) Feeds
  • mySpace
  • Facebook
  • Twitter
  • Audio/Video
  • Wikis
  • ...
what is stream processing
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

Fastest

Sensemaking

First

Domains for Competitive Advantage

Human

Capital

Tools

Data

trend organizations are getting dumber

All Digital Data

Growing Dumber

Sensemaking Algorithms

Trend: Organizations are Getting Dumber

Computing Power Growth

Time

the way forward

All Digital Data

Context

Engines

The Way Forward

Computing Power Growth

Sensemaking Algorithms

Time

sensemaking

Observations

Structured

Unstructured

Audio/Video

Geospatial

Biometrics

Etc.

CONSUMERS

Operational Systems

Business Intelligence

Data Marts

Data Mining

Pattern Discovery

Predictive Modeling

Case Management

Visualization

Etc.

Feature

Extraction

& Classification

Context

Analysis

Relevance

Detection

Publish

Persistent Context

Questions

Search, Discovery,

Context Requests

Etc.

Answers to questions

Respond

Notice

Sensemaking
in the future everybody will have privacy for 15 minutes
“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
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!
slide27

IBM VCGroup

VF Ventures

?

IBM Research

Entity Analytics

VF Research

A Suggestion…..

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

Service Innovation

Service Creation

ISV’s?

ISV’s?

Service Integration

VCC CoE

thank you

?

?

?

Thank You !

Ivan O’Dwyer IBM VCG

ivan.odwyer@ie.ibm.com