The Fast Path to Big Data

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The Fast Path

to Big Data

Industry Outlook 2012


Leveraging Big Data

Template Architectures to

Drive Business Outcomes

HIGHLIGHTS

Big Data is more than just a buzzword. It is a

proven model for leveraging existing

information sources to make smarter,

more immediate decisions that result in

better business outcomes.

Big Data is already being used today by

companies across vertical market segments to

improve top- and bottom-line performance.


Big Data Drivers & Hurdles

Lack of in-house

experience and expertise

in Big Data technologies

and their implementation

can greatly delay time-to-

benefit and add

unacceptable risk to the

IT project portfolio

Insufficient In-House

Expertise

A Confusing

Technology

Landscape

Uncertainty About

ROI

In the rush to cash in on

Big Data fever, developers

and vendors have

introduced a confusing

array of tools and

technologies that are often

longer on hype than they

are on clarity

Many IT organizations

find it difficult to prioritize

use cases, project the

economic benefits for

those use cases, and

right size their

investments accordingly


A Faster, Surer Path to Big Data Results

A Proven, Configurable Multitier Technology Stack

A Flexible, Modular Partner Engagement Model

Vertical Market Expertise across the Use-case Life Cycle

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2

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IT can enhance the speed, certainty and ROI of Big Data initiatives by

availing itself of three types of partner resources:


Configurable Multitier Technology Stack

Big Data implementations essentially require four tiers of technology:

1. Compute

Infrastructure

2. Data

Management

3. Analytics

4. Applications

The idea is to standardize the first three of these technology

tiers into a platform set that can be leveraged to deliver on

any given use case.

This brings predictability to cost and performance outcomes,

while also providing economies of scale that make each use

case successively less expensive

Big Data use cases, however, can vary significantly in their

functional attributes.

So, rather than utilizing a single, monolithic stack for every

use case, it makes much more sense to define a set of

templates and/or configuration parameters for each tier in the

stack to accurately and efficiently fulfill varying Big Data

requirements

This kind of highly configurable technology stack enables companies to avoid the

serious problems associated with either treating every use case as a “one-off”

project or force-fitting every use case into a “one size fits all” platform.


Modular Partner Engagement Model

Companies need the

flexibility to adopt

whatever elements

of their partner’s

services catalog offer

real advantages in

terms of ROI, while

still leveraging their

existing internal and/or

cloud resources

wherever it makes

sense to do so

There is no one-

size-fits-all

engagement model

for optimizing Big

Data ROI

Each partner

engagement must be

tightly tailored to

whatever specific

shortfalls in internal

resources stand between

a company and its

technical requirements,

as well as to the

magnitude of the

projected business

impact of that particular

Big Data initiative

Companies should

seek out a Big Data

partner with a history

of engagement with

industry leaders in its

core vertical market

The right Big Data partner will be able to accommodate all of these approaches with a

modular engagement model that empowers companies to choose the right mix of

solutions for their immediate and long-term objectives.

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Customer Engagement Models

A flexible engagement model allows companies to leverage partner, off-

the-shelf and vendor capabilities as appropriate, while utilizing their own

in-house resources wherever it makes sense to do so.


Critical Outcomes for a Big Data World

• Big Data has been clearly proven to help companies improve marketing, deliver an enhanced customer experience, drive operational efficiencies and achieve other outcomes that directly affect top- and bottom-line business performance

1. Rapid, Reliable Discovery of New, High-Impact Business Insights

• The right partner can help companies accomplish this investment reduction on several fronts: by sparing them the ramp-up costs; by rightsizing and/or hosting compute infrastructure; and by ensuring that the end-to-end solution stack is properly architected

2. Reduced Technology Implementation & Ownership Costs

• Engagement with the right partner brings consistency and repeatability to successive Big Data deliverables — enabling companies to gain economies of scale, continuously accelerate time-to-benefit and propagate shared Big Data services across the organization

3. Repeatable Success


Concluding Thoughts

The effective use of Big Data can mean the

difference between market leadership and ‘also-ran’

status for many companies

Big Data will continue to play a more strategic role in

enterprise IT. Companies that recognize this reality

— and that act on it in a technologically,

operationally and economically optimized way — will

gain sustainable competitive advantages over those

that don’t

Any company pursuing those advantages will

substantially benefit by engaging the right Big Data

partner


For more details please visit the link below:

http://www.wipro.com/Documents/The_Fast_Path_to_Big_D

ata.pdf

http://www.wipro.com/Documents/The_Fast_Path_to_Big_Data.pdf

http://www.wipro.com/Documents/The_Fast_Path_to_Big_Data.pdf

http://www.wipro.com/Documents/insights/assessing-the-bounties-and-boundaries-in-big-data-analytics.pdf


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customers. It specifically surveys innovative strategies that will help

customers gain competitive advantage in the market. The Council, in

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studies market trends to help equip organizations with insights to

facilitate their IT and business strategies.

For more information on the Research Council visit

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