Big data

‘Big Data’ is similar to ‘small data’, but bigger

…but having data bigger it requires different approaches: Techniques, tools and architecture

…with an aim to solve new problems …or old problems in a better way

WHAT IS BIG DATA?

BIG DATA CONFUSION

BIG DATA SURVEY

Survey conducted by IBM in mid-2013 with 1144 professionals from 95 countries across 26 industry. Respondents represent a mix of disciplines including both business professionals and IT professionals.

3 V‘s of Big Data

THREE PILLARS

Data Analytics Services/Aggregators/Tools

Technology Providers (Services, Storage, Data Warehouses)

Service Providers (Clubbing best of tools and technology with services)

IBM Google Wipro

SAS Institute SAP TCS

Microsoft Microsoft IBM

Oracle Amazon Infosys

Dell IBM Cognizant

Hitachi Oracle Oracle

Crayon Hewlett Packard

Tech Mahindra

THE BARRIERS

Nothing hinders use of Big Data

No by-as from management

Lack of willingness to share data

Overly complicated reports

Lack of communication between departments

Departmental Divisions

Other

Lack of analysis yeilding usable insights

Lack of in-house skills

Lack of suitable software

9

4

18

22

31

32

36

36

40

42

Australia

China

Hong Kong

India

Singapore

58

58.1

43.7

46.3

74.5

BIG IS STILL SMALLThe adoption of data strategies by businesses in Asia-

Pacific region has been relatively poor

INDIA-BIG DATA

Gaining attraction

Huge market opportunities for IT services (82.9% of revenues) and analytics firms (17.1 % )

Current market size is $200 million. By 2015 $1 billion

The opportunity for Indian service providers lies in offering services around Big Data implementation and analytics for global multinationals

COMPANIES RECENTLY USING BIG DATA

Future Enhancement

The phone in your pocket has more programmable memory, more storage and more capability than several large IBM computers.

It takes dozens of microprocessors running 100 million lines of code to get a premium car out of the driveway, and this software is only going to get more complex. In fact, the cost of software and electronics accounts for 30-40% of the price.

CONCLUSION Big Data and Big Data Analytics – Not Just for Large

Organizations It Is Not Just About Building Bigger Databases Moving Processing to the Data Source Yields Big Dividends Choose the Most Appropriate Big Data Scenario

Complete data scenario whereby entire data sets can be properly managed and factored into analytical processing, complete with in-database or in-memory processing and grid technologies.

Targeted data scenarios that use analytics and data management tools to determine the right data to feed into analytic models, for situations where using data set isn’t technically feasible or adds little value.

CLOSING THOUGHT Big data is not just about helping an organization be more

successful – to market more effectively or improve business operations.

High-performance analytics from designed to support big data initiatives, with in-memory, in-database and grid computing options.

Those organizations can benefit from cloud computing, where big data analytics is delivered as a service and IT resources can be quickly adjusted to meet changing business demands.

On Demand provides customers with the option to push big data analytics to greatly eliminating the time, capital expense and maintenance associated with on-premises deployments.

Thank you