|By PR Newswire||
|January 6, 2014 06:30 AM EST||
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
Government, public administration, & utilities
Telecom and IT
Transportation and logistics
Media and entertainment
Energy (oil, gas, and electricity)
Engineering and construction
Global Predictive Analytics Market, By Software Solutions Type
Decision support systems
Data mining and management
Fraud and security intelligence
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
Hosted or Cloud based
Global Predictive Analytics Market, By Geography
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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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