Performance, Scalability, and Economic Benefit of Open Analytics

About Us

Core Competencies include: Search (Apache Lucene, Elastic Search), Big Data Analytics (MongoDB, Apache Hadoop), Natural Language Processing (Apache

OpenNLP), Web Crawling (Apache Nutch)

Big Data Unstructured Data

Structured Data Open AnalyticsAgile Intelligence

Business Value

Agenda

• Why a need in the market• Market trends and patterns• What is open analytics• Deriving economic value

Why the need

Data is becoming the new raw material of business: An economic input almost on par with

capital and labor.

“Every day I wake up and ask, ‘how can I flow data better, manage data better, analyze data better?”

Rollin Ford, the CIO of Wal-Mart

Source: Data, Data Everywhere, The Economist, February 25, 2010

Source: Mike Driscoll, CTO Metamarkets: The Three Sexy Skills of Data Scientists (& Data Driven Startups)

Source: Mike Driscoll, CTO Metamarkets: The Three Sexy Skills of Data Scientists (& Data Driven Startups)

Market growth (BI)

2005 2006 2006 2008 2009 2010 2011 20120

5

10

15

20

25

30

35

40

$17.5B$19.4B

$22.1B$24.3B $24.9B

$28.1B$30.4B

$33.9B

$ of growth by year“After three decades, the business analytics market is finally reaching the mainstream”

“There are few growth inhibitors in the foreseeable future”

Source: IDC Worldwide Business Analytics Software - $billions – 2011 and 2012 estimates

Top 5 CIO Business and Technology Priorities (2012)

R Top 5 Technology Priorities

1 Analytics and business intelligence

2 Mobile Technologies

3 Cloud Computing (SaaS, IaaS, PaaS)

4 Collaboration technologies

5 Legacy modernization

R Top 5 Business Priorities

1 Increasing enterprise growth

2 Attracting and retaining new customers

3 Reducing Enterprise Costs

4 Creating new products and services (innovation)

5 Delivering operational results

Source: Gartner Top 10 Business and Technology Priorities in 2012

Open Analytics

• Process to design and implement analytical solutions

• Joins open tools and agile engineering techniques

• Goal is to enable organizations to deliver analysis products smarter, faster and more efficient which enables top line growth

How does this relate to open analytics

R Top 5 Technology Priorities

1 Analytics and business intelligence

2 Mobile Technologies

3 Cloud Computing (SaaS, IaaS, PaaS)

4 Collaboration technologies

5 Legacy modernization

R Top 5 Business Priorities

1 Increasing enterprise growth

2 Attracting and retaining new customers

3 Reducing Enterprise Costs

4 Creating new products and services (innovation)

5 Delivering operational results

R Open Analytics

1 Open innovation

2 Mission agility

3 Open source software

4 Easily extensible algorithms

5 Analysis teamed with technology

Open Architecture + Open Source = Open Analytics

Solutions for analysis• Processing needs• Search and Aggregation• Harvesting and Enrichment• Data and Document Storage• Machine learning• Visualization

Business Value enabled analysis• Require the ability to quickly change• Require the ability to quickly scale• Require the ability to visualize uniquely• Require the ability to be domain specific

Deriving economic value

• What problem will I truly be solving?• How is my big data solution to derive

analytical meaning?• Can I apply a $ value to the solution?

If I said no any of these do I really have a problem today and is status quo okay?

Start with a simple question you are trying to solve and get specific really fast!

Question for the audience

How are you using open source big data analytics today to drive topline business

growth?

a) Unstructured and structured data fusion

b) Machine learning and prediction

c) Dashboarding, mashups and data visualization

d) Other?

Thank You!!!

Christopher Morgan

www.ikanow.com

cmorgan@ikanow.com