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Topics: Cloud computing, Data management, Decision theory Pages: 5 (603 words) Published: January 17, 2013
How does Big Data disrupt the technology ecosystem of the public cloud?

Copyright 2012 IDC. Reproduction is forbidden unless authorized. All rights reserved.

Market trends

2020 Vision

Introduce panel members and theme

© 2012 IDC



Market Drivers of Big Data
Billions of devices, millions of apps, drives data explosion Heterogeneous systems and architectures Real time computing and decision making-analytics Cloud bridges consumer and enterprise markets  Convergence of compute, storage, and networking solutions  Workloads are changes-more parallelization  Big data needs big storage  Density and power are still the key parameters © 2012 IDC

Next Era of Computing-Intelligent Systems 2020 Vision

Connected People

Revenue Opportunity

GBs of Data

© 2012 IDC

Embedded and Intelligent Systems
Source: IDC, Intel, McAfee 2012

The “Greater Cloud” Opportunity
Includes Cloud Services…
Cloud Services Deployment Models
Customer site

2016 Hosted $26.0B Private Cloud
(50%+ CAGRe)

Service provider site


(26.4% CAGR)

Managed Private Cloud

Dedicated Private Cloud

Virtual Private Cloud

Public Cloud

Dedicated/Single-tenant delivery platform

Shared/Multi-tenant delivery platform

Source: Worldwide and Regional Public IT Cloud Services 2012–2016 Forecast, IDC #236552 Aug 2012) © 2012 IDC

The “Greater Cloud” Opportunity
… and ICT products and services that enable Cloud Services IT Services
(e.g., Consulting, Integration)


(29.2% CAGR)

Servers Storage

“IT for the Cloud” Converged Systems
System Infrastructure Software Network Equipment


(19.2% CAGR)

Network Services
Source: Worldwide and U.S. Cloud Professional Services 2012–2016 Forecast , IDC #235054 Jun 2012) © 2012 IDC 6

Big Data Technology Segments
Decision Support & Automation Interface
Applications with functionality required to support collaboration, scenario evaluation, risk management, and decision capture and retention

Analytics & Discovery

This layer includes software for ad-hoc discovery, and deep analytics and software that supports realtime analysis and automated, rules-based transactional decision making Refers to software that processes and prepares all types of data for analysis. This layer extracts, cleanses, normalizes, tags, and integrates data

Data Organization & Management


The foundation of the stack includes the use of industry standard servers, networks, storage, and clustering software used for scale out deployment of Big Data technology

© 2012 IDC

Big Data is Not All About Technology
Q: What are the top IT challenges to delivering a successful business analytics solution? Data integration Managing data quality Cost of technology Lack of sufficiently skilled IT staff Data governance Evaluating appropriate technology Keeping up with system performance requirements High ongoing technology maintenance costs Q: What are the top business challenges to delivering a successful BI and analytics solution in your organization?

51.4 47.7 46.8 46.8

Defining business requirements Lack of sufficient number of staff with analytics skills



Securing budget


34.2 27.9 24.3 20.7
Finding executive sponsors Agreeing on KPIs, metrics



Source: IDC and Computerworld BI and Analytics Survey Research Group IT Survey, 2012, N = 111 © 2012 IDC

Big Data/Analytics: Milestones
In 2013, vendors increasingly provide not only technology but also analytic services and content (data as a service) Distinction between technology and services firms will increasingly blur (Deloitte acquires OCO) Business process consulting accelerates in importance Big Data technology and services market will reach $16 Billion by 2016 By 2017, 25% of F500 companies will have artificial...
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