How does Big Data disrupt the technology ecosystem of the public cloud?

Transcription

1 How does Big Data disrupt the technology ecosystem of the public cloud? Copyright 2012 IDC. Reproduction is forbidden unless authorized. All rights reserved.

2 Agenda Market trends 2020 Vision Introduce panel members and theme Source:/Notes: 2

3 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

4 Next Era of Computing-Intelligent Systems 2020 Vision 4 BILLION Connected People 4 Trillion Revenue Opportunity MILLION Apps 25 BILLION Embedded and Intelligent Systems TRILLION GBs of Data Source: IDC, Intel, McAfee 2012

5 The Greater Cloud Opportunity Includes Cloud Services Cloud Services Deployment Models Customer site Managed Private Cloud Service provider site 2016 Hosted Private Cloud $26.0B (50%+ CAGRe) Dedicated Private Cloud Virtual Private Cloud 2016 $98.4B (26.4% CAGR) Public Cloud Dedicated/Single-tenant delivery platform Shared/Multi-tenant delivery platform Source: Worldwide and Regional Public IT Cloud Services Forecast, IDC # Aug 2012)

6 The Greater Cloud Opportunity and ICT products and services that enable Cloud Services IT Services (e.g., Consulting, Integration) 2016 $19.9B (29.2% CAGR) Servers Storage IT for the Cloud System Infrastructure Software Network Services Converged Systems Network Equipment 2016 $34.8B (19.2% CAGR) Source: Worldwide and U.S. Cloud Professional Services Forecast, IDC # Jun 2012) 6

7 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 Data Organization & Management Refers to software that processes and prepares all types of data for analysis. This layer extracts, cleanses, normalizes, tags, and integrates data Infrastructure 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

8 Big Data is Not All About Technology Q: What are the top IT challenges to delivering a successful business analytics solution? Q: What are the top business challenges to delivering a successful BI and analytics solution in your organization? Data integration Managing data quality Cost of technology Lack of sufficiently skilled IT staff Data governance Defining business requirements Lack of sufficient number of staff with analytics skills Securing budget Evaluating appropriate technology Keeping up with system performance requirements High ongoing technology maintenance costs Agreeing on KPIs, metrics Finding executive sponsors Source: IDC and Computerworld BI and Analytics Survey Research Group IT Survey, 2012, N = 111

9 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 intelligence question & answer systems in place across consumer industries, operating within call centers, in retail stores, etc. Real time monitoring of streaming data will become pervasive by 2020 (today a combination of off line and real time)