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Predictive Analytics Market 2013-2019 Global Industry Analysis, Size, Share, Growth, Trends, and Forecast to 2019 Research Report Available Online By ResearchMoz.us

NEW YORK, January 6, 2014 /PRNewswire/ --

ResearchMoz.us includes new market research report "Predictive Analytics Market 2013-2019" to its huge collection of research reports.

Researchmoz presents this most up-to-date research on Predictive Analytics Market 2013-2019(http://www.researchmoz.us/predictive-analytics-market-customer-intelligence-decision-support-systems-data-mining-and-management-performance-management-fraud-and-security-intelligence-risk-management-financial-intelligence-operations-and-campaign-management-glob-report.html). This report analyzes the predictive analytics market on a global basis, with further breakdown into various sub-segments. It provides cross-sectional analysis of the market based on parameters such as geography, end-use industry, software solutions type, applications, and mode of delivery. The analysis provides market estimates in terms of revenue, and forecast for the period 2013 - 2019. 

The market is going through a growth phase marked with complexity of solutions and low awareness. There are variations in growth patterns across different end-use industries and type of software solutions. These variations exist in terms of technologies used and applications preferred. This report is thereby produced to give a detailed overview of the ongoing trends in the market. It includes review of market dynamics with focus on market drivers, growth challenges (restraints), and opportunities. The value chain analysis and Porter's five forces analysis included in the report further help in assessing the market situation and competitiveness. Market attractiveness analysis highlights key industry segments and their comparative attractiveness against other segments. 

Apart from the detailed sub-segment analysis as illustrated below, this report also provides company profiles of the key market players. The competitive profiling of these players includes company and financial overview, business strategies adopted by them, and their recent developments which can help in assessing competition in the market. Some of the major companies included in this report include International Business Machines Corporation (IBM), SAS Institute Inc, Microsoft Corporation, SAP AG, Tableau Software Inc., Information Builders, Fair Isaac Corporation (FICO), Teradata Corporation, Acxiom Corporation, and TIBCO Software Inc. among others.

This research report presents a comprehensive assessment of the global predictive analytics market, by segmenting it as shown below.

Global Predictive Analytics Market, By End-Use Industry 
Banking and financial services
Insurance
Government, public administration, & utilities
Pharmaceutical 
Telecom and IT
Retail 
Transportation and logistics
Healthcare
Manufacturing
Media and entertainment
Energy (oil, gas, and electricity)
Engineering and construction
Tourism
Sports
Others
 
Global Predictive Analytics Market, By Software Solutions Type 
Customer intelligence
Decision support systems
Performance management
Data mining and management
Fraud and security intelligence
Sustainability intelligence
Financial intelligence
Operations management
Campaign management
Others 

Global Predictive Analytics Market, By Application 
Sales and marketing
Customer and channel
Operations and workforce
Finance and risk

Global Predictive Analytics Market, By Mode of Delivery
On-premises installation
Hosted or Cloud based

Global Predictive Analytics Market, By Geography
North America
Europe
Asia Pacific
RoW

Related & Recently Added Reports by Researchmoz.us to its store.

Wearable Technology in Industry Verticals 2013-2018 (http://www.researchmoz.us/wearable-technology-in-industry-verticals-2013-2018-report.html) We see several factors converging to facilitate wearable technology integration including expanded wireless capacity due to pervasive wireless (WiFi, WiMAX, and LTE), cellular market saturation and the need for wireless companies to establish new revenue streams, continuously decreasing cost of data, and the significant backing from huge companies including Google, Apple, and others.  We also see developments in key technologies such as Augmented Reality, Body Area Networks, Ambient Awareness, and Peer-to-Peer Communications as drivers for evolution in consumer perception of value and willingness to engage in new forms of communications, content, applications, and commerce.

Google in Broadband and Applications (http://www.researchmoz.us/google-in-broadband-and-applications-report.html )Google's core business has been to provide a platform for users to search and access information on the Internet. Against the backdrop of vibrant developments in technology, Google has set the pace in many areas by expanding its business influence and creating new revenue generation options. Google has strengthened presence across the technology value chain by developing capacity to set-up fiber-optic communications networks, web-based applications for consumers and enterprises, and android-based mobile applications.The first two capabilities strengthen Google's main revenue generation activity - online advertising. And two of the three have created new revenue streams.

Big Data in Financial Services Industry (http://www.researchmoz.us/big-data-in-financial-services-industry-market-trends-challenges-and-prospects-2013-2018-report.html) Big Data is making a big impact already in certain industries such as the healthcare, industrial, and retail sectors. With the exception of the government sector, no other industry has more to gain from leveraging Big Data than the financial services sector. Big Data technology will help financial institutions maximize the value of data and gain competitive advantage, minimize costs, convert challenges to opportunities, and minimize risk in real-time.Big Data technologies provide financial services firms with the capability to capture and analyze data, build predictive models, back-test and simulate scenarios. Through iteration, firms will determine the most important variables and also key predictive models.There is a huge opportunity for financial services firms to apply new data sets and new algorithms to optimize capital allocation, cash management, and currency processing. The financial implications are manifest in improved capital flows and profitability for many firms within the ecosystem.

Cloud Application Marketplace 2013 - 2018 (http://www.researchmoz.us/cloud-application-marketplace-2013-2018-report.html) There are thousands of cloud applications in the market that are offered by hundreds of vendors. To gain a competitive advantage in the cloud applications market, companies are collaborating in the development and/or delivery of solutions that solve enterprise problems, optimize operations, improve customer relations and services delivery.  Many of these solutions rely upon open APIs for access to hybrid enterprise/telephony cloud-based applications.  This trend is expected to accelerate as the lower cost of cloud application operations is a significant deployment factor.At the consumer user level, the global cloud applications marketplace is driven largely by the increasing adoption of a variety of mobile devices including smartphones, tablets, and wearable wireless devices.

Table of Contents

1.0 EXECUTIVE SUMMARY 6
2.0 UNDERSTANDING CLOUD COMPUTING  8
2.1 CLOUD FOUNDATIONS 9
2.1.1 GRID COMPUTING 11
2.2 CLOUD TECHNOLOGIES AND ARCHITECTURE  12
2.2.1 SOFTWARE DEFINED NETWORKING (SDN)  15
2.2.2 VIRTUALIZATION 16
2.3 CLOUD COMPUTING V/S VIRTUALIZATION 18
2.4 MOVING BEYOND CLOUD COMPUTING  19

3.0 CLOUD SERVICE ENABLERS 21
3.1 GENERAL ENABLERS  21
3.1.1 WIRELESS BROADBAND CONNECTIVITY 21
3.1.2 SECURITY SOLUTIONS  21
3.1.3 PRESENCE AND LOCATION  22
3.2 PERSONAL CLOUD SERVICE ENABLERS  22
3.2.1 IDENTITY MANAGEMENT 22
3.2.2 PREFERENCE MANAGEMENT 23

4.0 CLOUD SERVICE ANALYSIS  24
4.1 CLOUD SERVICE SEGMENTATION 24
4.1.1 BUSINESS TO BUSINESS (B2B)  24
4.1.2 BUSINESS TO CONSUMER (B2C)  25
4.2 THE BIG THREE CLOUD SERVICES  26
4.2.1 INFRASTRUCTURE AS A SERVICE (IAAS) 27
4.2.2 PLATFORM AS A SERVICE ( PAAS) 29
4.2.3 SOFTWARE AS A SERVICE (SAAS) 31
4.2.4 DIFFERENCES BETWEEN IAAS, SAAS, AND PAAS 33
4.3 BUSINESS PROCESS AS A SERVICE 34
4.3.1 ENTERPRISE RESOURCE PLANNING IN THE CLOUD  35
4.3.2 SUPPLY CHAIN MANAGEMENT IN THE CLOUD  38
4.4 INDUSTRY VERTICALS IN THE CLOUD  40
4.4.1 FINANCE AND BANKING IN THE CLOUD 41
4.4.2 RETAIL IN THE CLOUD 43
4.4.3 HEALTHCARE IN THE CLOUD  45
4.4.4 TELECOMMUNICATIONS IN THE CLOUD  47
4.4.5 GOVERNMENT AND DEFENSE IN THE CLOUD  49
4.5 WORKFORCE IN THE CLOUD  50
4.5.1 HUMAN CAPITAL MANAGEMENT IN THE CLOUD  50
4.5.2 TRAINING AND EDUCATION IN THE CLOUD 52
4.5.3 COLLABORATION IN THE CLOUD  52
4.5.4 OFFICE AUTOMATION IN THE CLOUD 54
4.6 CUSTOMERS IN THE CLOUD 56
4.6.1 CUSTOMER RELATIONSHIP IN THE CLOUD  56
4.6.2 COMMERCE AND PAYMENTS IN THE CLOUD  58
4.7 EMERGING CLOUD BASED APPLICATIONS  59
4.7.1 B2B APPLICATIONS 59
4.7.2 B2C APPLICATIONS 62
4.8 THE FUTURE OF CLOUD SERVICES 64
4.8.1 EVERYTHING AS A SERVICE 66

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