[307 Pages Report] The global predictive analytics market size to grow from USD 7.2 billion in 2020 to USD 21.5 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 24.5% during the forecast period. Various factors such as the growing focus on digital transformation, rise adoption of big data and AI and ML technologies, increasing focus on remote monitoring in support of the COVID-19 pandemic, and the need to forecast possible future financial scenarios to answer specific business questions are expected to drive the adoption of the predictive analytics market.
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The spread of COVID-19 has generated a huge disruption in daily activities. It has forced people to follow social distancing policies, temporarily suspend many business activities, and limit travel. Under such circumstances, the healthcare vertical has emerged as the biggest user of big data and predictive analytics to understand the virus and its spread. The pandemic situation has also disrupted demand and supply cycles. To be on the top of demand, manufacturers need real-time insights on demand and inventory status to make informed decisions. Predictive analytics has enabled manufacturers to determine how much quantity of products they should produce, and it has also helped determine what should be the priority of production line according to demand trends to ensure that production is never halted.
Technologies have helped drive businesses to the next level by providing the fuel for analytics tools to forecast, predict, and plan for issues before they actually occur. Companies with transportation fleets that leverage the predictive modeling technology would be able to increase their bottom line efficiencies even further and amplify their competitive advantage post the pandemic using predictive analytics solutions and services.
Today, data is recognized as a new resource. It requires efficient and effective utilization to ensure a competitive market edge. Businesses are interested in deriving insights from collected data for making better, real-time, and fact-based decisions. This demand for in-depth knowledge has accelerated the adoption of big data and related technologies. The exponential growth in data volume is due to the expansion of businesses worldwide, driving the rise in data volumes and sources. The accumulation of big data in a single location has rapidly developed data science experts' evaluation capabilities in every organization. Companies prefer to provide standalone solutions, rather than combined solutions. This is eventually increasing the number of big data analytics startups, which are driving noteworthy innovations.
Big data has captured the attention of businesses and consumers. It has not only become a major subject in technology and media, but also made its way into many compliances, internal audit, and fraud risk management-related discussions. An integral part of business operations in every industry, big data has influenced the adoption of predictive analytics worldwide. Leveraging the opportunities and challenges of big data predictive analytics, enterprises can optimize vital business processes, functions, and objectives. Predictive analytics enables organizations to meet stakeholder demands, manage data volumes, manage risks, improve process controls, and boost administrative performance by turning information into intelligence. Advanced predictive analytics solutions play a vital role in enabling an effective Intelligent Enterprise (IE) approach, which helps in creating a single view across the entire organization through the combination of standard reporting and data visualization.
Predictive analytics delivers a decisive data interpretation and provides a larger picture to decision-makers for boosting the overall business performance. The modification of predictive models permits integration with both software and services, depending on the level and nature of the analysis. Professional services are necessary for customizing existing analytics solutions, which cater to particular data sets. As the predictive analytics concept is still in the nascent phase, the availability of skilled labor is also limited. This is another important factor in restraining market growth. Moreover, changing regulations are considered as the major factor slowing down the adoption of predictive analytics among organizations. For instance, data regulations may vary from region to region and country to country. General Data Protection Regulation (GDPR) enables the European Union (EU) to monitor and ensure the safety of the EU citizens.
As compared to conventional solutions, the initial costs and time incurred for deploying predictive analytics solutions are higher due to the involvement of BI and data analytics expertise. Though the deployment of predictive analytics solutions would reduce operating costs in later stages, the time consumed for managing and updating regulations is tedious. Therefore, the adoption of predictive analytics solutions is expected to witness a slower pace in small enterprises.
During the uncertain situation of the COVID-19 pandemic, the healthcare vertical has sought to use big data and predictive analytics tools to better understand the virus and its spread. Predictive analytics has helped researchers around the world to build predictive analytics models that can track COVID-19 surges in different countries. Researchers from Binghamton University and State University of New York have developed several predictive analytics models to examine COVID-19 trends and patterns around the world. Hospitals and health systems have leveraged predictive models to gain insights into COVID-19 risks, disease outcomes, and the virus potential impact on resources. Communities across countries have started relaxing social distancing orders; hence, it has become crucial for health systems to plan for changes in healthcare demands and surges in COVID-19 cases. The team at CommonSpirit Health has built predictive models using de-identified cell phone data, public health information, and data from the CommonSpirit Health systems own care sites. Using these models, organizations can gain insights into the surges and dips of COVID-19 infection rates, allowing hospitals to plan better and work toward resuming their full spectrum of necessary services. Recently, a team from Florida Atlantic University (FAU) has utilized the ML technology to build a COVID-19 knowledge base and risk assessment dashboard, which aims at addressing the discrepancies that exist in the context of the pandemic. Hence, using these predictive models, researchers can help organizations in staying ahead of possible increases in COVID-19 patients by continuing to collect data from around the world to make predictive analytics models more accurate.
These days, organizations analyze and generate insights from various data formats. These data formats include text, video, speech, and image for their businesses. There is a variety of data models for different business needs. These data models are tightly integrated with specific analytics solutions. For example, machine-generated data is modeled differently from the data coming from web and social media. The use of these data types is different for different business needs. Machine-generated data can be analyzed using supply chain analytics or operational analytics, while web and social network data can be analyzed using social media analytics. Organizations need to define different business rules for managing different data models and integrated analytics solutions.
The deployment modes in the predictive analytics market include on-premises and cloud. Predictive analytics solutions are deployed in various enterprises. Enterprises adopt cloud models due to inadequate resources. These models enable organizations to leverage the benefits of real-time predictive analytics.
Several organizations have started emphasizing on the importance of having the right cloud-based collaboration tools, enabling employees to work remotely to limit the pandemic impact on productivity as the COVID-19 outbreak has forced numerous companies to review their IT strategies as a top priority.
The predictive analytics market is segmented based on organization size, which includes SMEs and large enterprises. The market size of the large enterprise segment is estimated to be higher in 2020. Enhanced business productivity and timely delivery of products and services are important aspects for the success of any organization. Organizations have been gradually recognizing the importance of predictive analytics solutions and services and have started deploying them as per their needs and available resources. Large enterprises face the need to analyze large volumes of data generated from business functions and customers to enable data-driven decisions, driving the adoption of predictive analytics solutions and services.
North America is expected to hold the largest market size in the global predictive analytics market. In contrast, Asia Pacific (APAC) is expected to grow at the highest CAGR during the forecast period due to the commercialization of IoT technology and the increasing adoption of advanced technologies across countries, such as China, Japan, and ANZ. The improved internet penetration in the region provides enormous opportunities for organizations to gather insights about customer preferences, thus leading to the adoption of predictive analytics solutions in APAC.
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The predictive analytics vendors have implemented various types of organic and inorganic growth strategies, such as new product launches, product upgradations, partnerships and agreements, business expansions, and mergers and acquisitions to strengthen their offerings in the market. The major vendors in the global predictive analytics market include Microsoft (US), IBM (US), SAS Institute (US), SAP SE (Germany), Oracle (US), Google (US), Salesforce (US), Amazon Web Services (US), Hewlett Packard Enterprise (US), Teradata (US), Alteryx (US), Altair (US), FICO (US), Domo (US), Cloudera (US), Board International (Switzerland), TIBCO Software (US), Hitachi Vantara (US), Happiest Minds (India), Dataiku (US), Qlik (US), RapidMiner (US), ibi (US), Infor (US), Biofourmis (US), In-Med Prognostics (US), Aito.ai (Finland), Symend (US), Onward Health (India), Unioncrate (US), CyberLabs (Brazil), Actify Data Labs (India), Amlgo Labs (India), Verimos (US). The study includes an in-depth competitive analysis of these key players in the Predictive analytics market with their company profiles, recent developments, and key market strategies.
Report Metric |
Details |
Market size available for years |
20142025 |
Base year considered |
2019 |
Forecast period |
20202025 |
Forecast units |
USD Billion |
Segments covered |
Component, deployment mode, organization size, vertical, and region |
Geographies covered |
North America, Europe, APAC, Latin America, and MEA |
Companies covered |
Microsoft (US), IBM (US), SAS Institute (US), SAP SE (Germany), Oracle (US), Google (US), Salesforce (US), Amazon Web Services (US), Hewlett Packard Enterprise (US), Teradata Corporation (US), Alteryx (US), Altair (US), FICO (US), Domo (US), Cloudera (US), Board International (Switzerland), TIBCO Software (US), Hitachi Vantara (US), Happiest Minds (India), Dataiku (US), Qlik (US), RapidMiner (US), ibi (US), Infor (US), Biofourmis (US), In-Med Prognostics (US), Aito.ai (Finland), Symend (US), Onward Health (India), Unioncrate (US), CyberLabs (Brazil), Actify Data Labs (India), Amlgo Labs (India), Verimos (US) |
This research report categorizes the predictive analytics market based on components, deployment modes, organization size, verticals, and regions.
What is predictive analytics?
Predictive analytics is a statistical and data mining solution that consists of numerous algorithms and methodologies. These algorithms and methodologies are used for both structured as well as unstructured data to extract business insights. Predictive analytics offers flexible, scalable, and advanced solutions to help users make better-informed business decisions. It allows industries in understanding customer perceptions by providing a competitive market edge and the ability to rapidly orchestrate business decisions.
Which countries are considered in the European region?
The report includes an analysis of the UK, Germany, and France in the European region.
Which are key verticals adopting predictive analytics solutions and services?
Key verticals adopting Predictive analytics solutions and services include into BFSI, retail and eCommerce, manufacturing, government and defense, healthcare and life sciences, energy and utilities, transportation and logistics, and telecommunications and IT, and others, which include media and entertainment, travel and hospitality, and education.
Which are the key drivers supporting the growth of the predictive analytics market?
The key drivers supporting the growth of the predictive market include rising adoption of big data and other related technologies, the advent of ML and AL, and cost benefits of cloud-based predictive analytics solutions
Who are the key vendors in the predictive analytics market?
The key vendors operating in the Predictive Analytics market include Microsoft, IBM, SAS Institute, SAP, Oracle, Google, Salesforce, AWS, HPE, Alteryx, Altair, FICO, and Board International. These vendors have adopted different types of organic and inorganic growth strategies such as new product launches, product enhancements, partnerships, and mergers and acquisitions. .
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TABLE OF CONTENTS
1 INTRODUCTION (Page No. - 36)
1.1 INTRODUCTION TO COVID-19
1.2 COVID-19 HEALTH ASSESSMENT
FIGURE 1 COVID-19: THE GLOBAL PROPAGATION
FIGURE 2 COVID-19 PROPAGATION: SELECT COUNTRIES
1.3 COVID-19 ECONOMIC ASSESSMENT
FIGURE 3 REVISED GROSS DOMESTIC PRODUCT FORECASTS FOR SELECT G20 COUNTRIES IN 2020
1.3.1 COVID-19 ECONOMIC IMPACTSCENARIO ASSESSMENT
FIGURE 4 CRITERIA IMPACTING THE GLOBAL ECONOMY
FIGURE 5 SCENARIOS IN TERMS OF RECOVERY OF THE GLOBAL ECONOMY
1.4 OBJECTIVES OF THE STUDY
1.5 MARKET DEFINITION
1.5.1 INCLUSIONS AND EXCLUSIONS
1.6 MARKET SCOPE
1.6.1 MARKET SEGMENTATION
1.6.2 REGIONS COVERED
1.6.3 YEARS CONSIDERED FOR THE STUDY
1.7 CURRENCY CONSIDERED
TABLE 1 UNITED STATES DOLLAR EXCHANGE RATE, 20172019
1.8 STAKEHOLDERS
1.9 SUMMARY OF CHANGES
2 RESEARCH METHODOLOGY (Page No. - 46)
2.1 RESEARCH DATA
FIGURE 6 PREDICTIVE ANALYTICS MARKET: RESEARCH DESIGN
2.1.1 SECONDARY DATA
2.2 MARKET BREAKUP AND DATA TRIANGULATION
FIGURE 7 DATA TRIANGULATION
2.2.1 PRIMARY DATA
2.2.1.1 Key industry insights
TABLE 2 PRIMARY INTERVIEWS
2.2.1.2 Breakup of primary profiles
2.3 MARKET SIZE ESTIMATION
FIGURE 8 MARKET SIZE ESTIMATION METHODOLOGY -APPROACH 1 (SUPPLY SIDE): REVENUE OF SOLUTIONS/SERVICES OF PREDICTIVE ANALYTICS MARKET
FIGURE 9 MARKET SIZE ESTIMATION METHODOLOGY -APPROACH 2 - BOTTOM-UP (SUPPLY SIDE): COLLECTIVE REVENUE OF ALL SOLUTIONS/SERVICES OF MARKET
FIGURE 10 MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES
2.3.1 TOP-DOWN APPROACH
2.3.2 BOTTOM-UP APPROACH
2.4 MARKET FORECAST
TABLE 3 FACTOR ANALYSIS
TABLE 4 IMPACT OF COVID-19
2.5 COMPANY EVALUATION MATRIX
FIGURE 11 COMPETITIVE EVALUATION MATRIX: CRITERIA WEIGHTAGE
2.6 ASSUMPTIONS FOR THE STUDY
2.7 LIMITATIONS OF THE STUDY
3 EXECUTIVE SUMMARY (Page No. - 56)
TABLE 5 GLOBAL PREDICTIVE ANALYTICS MARKET SIZE AND GROWTH RATE, 20142019 (USD MILLION, Y-O-Y%)
TABLE 6 GLOBAL MARKET SIZE AND GROWTH RATE, 20192025 (USD MILLION, Y-O-Y%)
FIGURE 12 SOLUTIONS SEGMENT TO HOLD LARGER MARKET SIZE IN 2020
FIGURE 13 RISK ANALYTICS SEGMENT TO HOLD LARGEST MARKET SIZE IN 2020
FIGURE 14 PROFESSIONAL SERVICES SEGMENT TO HOLD HIGHER MARKET SHARE IN 2020
FIGURE 15 DEPLOYMENT AND INTEGRATION SEGMENT TO HOLD HIGHER MARKET SHARE IN 2020
FIGURE 16 ON-PREMISES SEGMENT TO HOLD LARGER MARKET SIZE IN 2020
FIGURE 17 LARGE ENTERPRISES SEGMENT TO HOLD HIGHER MARKET SHARE IN 2020
FIGURE 18 BANKING, FINANCIAL SERVICES, AND INSURANCE VERTICAL TO HOLD LARGEST MARKET SIZE IN 2020
FIGURE 19 NORTH AMERICA TO HOLD HIGHEST MARKET SHARE IN 2020
4 PREMIUM INSIGHTS (Page No. - 62)
4.1 ATTRACTIVE OPPORTUNITIES IN PREDICTIVE ANALYTICS MARKET
FIGURE 20 INCREASING ADOPTION OF AI AND ML TECHNOLOGIES TO BOOST MARKET GROWTH
4.2 MARKET, BY SOLUTION
FIGURE 21 RISK ANALYTICS SEGMENT TO HOLD LARGEST MARKET SIZE FROM 2020 TO 2025
4.3 MARKET, BY REGION
FIGURE 22 NORTH AMERICA TO HOLD HIGHEST MARKET SHARE IN 2020
4.4 MARKET, BY SOLUTION AND VERTICAL
FIGURE 23 RISK ANALYTICS SEGMENT AND BANKING, FINANCIAL SERVICES, AND INSURANCE VERTICAL TO HOLD HIGHEST MARKET SHARES IN 2020
5 MARKET OVERVIEW AND INDUSTRY TRENDS (Page No. - 64)
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
FIGURE 24 DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES: PREDICTIVE ANALYTICS MARKET
5.2.1 DRIVERS
5.2.1.1 Rising adoption of big data and other related technologies
5.2.1.2 Advent of machine learning and artificial intelligence
5.2.1.3 Cost benefits of cloud-based predictive analytics solutions
5.2.2 RESTRAINTS
5.2.2.1 Changing regional data regulations leading to the time-consuming restructuring of predictive models
5.2.3 OPPORTUNITIES
5.2.3.1 Rising internet proliferation and growing usage of connected and integrated technologies
5.2.3.2 Increasing demand for real-time streaming analytics solutions to track and monitor the COVID-19 spread
5.2.4 CHALLENGES
5.2.4.1 Growing demand for diversified data models based on business needs
5.2.4.2 Ownership and privacy of collected data
5.2.5 CUMULATIVE GROWTH ANALYSIS
5.3 IMPACT OF COVID-19 ON THE PREDICTIVE ANALYTICS MARKET
FIGURE 25 MARKET TO WITNESS DECLINE IN GROWTH IN 2020
5.4 PREDICTIVE ANALYTICS: EVOLUTION
FIGURE 26 EVOLUTION OF PREDICTIVE ANALYTICS
5.5 PREDICTIVE ANALYTICS: ECOSYSTEM
FIGURE 27 PREDICTIVE ANALYTICS: ECOSYSTEM
5.6 CASE STUDY ANALYSIS
5.6.1 BANKING, FINANCIAL SERVICES, AND INSURANCE
5.6.1.1 Case study 1: Streamlining the mortgage appraisal process
5.6.2 TELECOMMUNICATIONS AND IT
5.6.2.1 Case study 1: Segmenting customers to deliver accurate and timely decisions
5.6.3 RETAIL AND ECOMMERCE
5.6.3.1 Case study 1: Using weather data to predict sales
5.6.4 HEALTHCARE AND LIFE SCIENCES
5.6.4.1 Case study 1: Improve healthcare operations with data analysis
5.6.5 MANUFACTURING
5.6.5.1 Case study 1: Improving customer support in electronic manufacturing
5.6.6 ENERGY AND UTILITIES
5.6.6.1 Case study 1: Increasing debt collection
5.6.7 TRANSPORTATION AND LOGISTICS
5.6.7.1 Case study 1: Visualizing and predicting the status of the fleet
5.7 PATENT ANALYSIS
5.7.1 PATENTS FILED: PREDICTIVE ANALYTICS MARKET, BY SOLUTION, 20192020
5.8 VALUE CHAIN ANALYSIS
FIGURE 28 VALUE CHAIN ANALYSIS
5.9 TECHNOLOGY ANALYSIS
5.9.1 AI AND PREDICTIVE ANALYTICS
5.9.2 BLOCKCHAIN AND PREDICTIVE ANALYTICS
5.9.3 ML AND PREDICTIVE ANALYTICS
5.9.4 IOT AND PREDICTIVE ANALYTICS
5.9.5 5G AND PREDICTIVE ANALYTICS
5.10 PRICING ANALYSIS
5.11 REGULATORY IMPLICATIONS
5.11.1 INTRODUCTION
5.11.2 SARBANES-OXLEY ACT OF 2002
5.11.3 GENERAL DATA PROTECTION REGULATION
5.11.4 BASEL
6 PREDICTIVE ANALYTICS MARKET, BY COMPONENT (Page No. - 80)
6.1 INTRODUCTION
6.1.1 COMPONENTS: MARKET DRIVERS
6.1.2 COMPONENTS: COVID-19 IMPACT
FIGURE 29 SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
TABLE 7 MARKET SIZE, BY COMPONENT, 20142019 (USD MILLION)
TABLE 8 MARKET SIZE, BY COMPONENT, 20192025 (USD MILLION)
6.2 SOLUTIONS
FIGURE 30 CUSTOMER ANALYTICS SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
TABLE 9 MARKET SIZE, BY SOLUTION, 20142019 (USD MILLION)
TABLE 10 PREDICTIVE ANALYTICS MARKET SIZE, BY SOLUTION, 20192025 (USD MILLION)
6.2.1 FINANCIAL ANALYTICS
TABLE 11 FINANCIAL ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 12 FINANCIAL ANALYTICS MARKET SIZE, BY REGION, 20192025 (USD MILLION)
TABLE 13 FINANCIAL ANALYTICS MARKET SIZE, BY APPLICATION, 20142019 (USD MILLION)
TABLE 14 FINANCIAL ANALYTICS MARKET SIZE, BY APPLICATION, 20192025 (USD MILLION)
6.2.1.1 Fraud detection
6.2.1.2 Profitability management
6.2.1.3 Governance, risk, and compliance management
6.2.1.4 Others
6.2.2 RISK ANALYTICS
TABLE 15 RISK ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 16 RISK ANALYTICS MARKET SIZE, BY REGION, 20192025 (USD MILLION)
TABLE 17 RISK ANALYTICS MARKET SIZE, BY APPLICATION, 20142019 (USD MILLION)
TABLE 18 RISK ANALYTICS MARKET SIZE, BY APPLICATION, 20192025 (USD MILLION)
6.2.2.1 Cyber risk management
6.2.2.2 Operational risk management
6.2.2.3 Credit and market risk management
6.2.2.4 Others
6.2.3 MARKETING ANALYTICS
TABLE 19 MARKETING ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 20 MARKETING ANALYTICS MARKET SIZE, BY REGION, 20192025 (USD MILLION)
TABLE 21 MARKETING ANALYTICS MARKET SIZE, BY APPLICATION, 20142019 (USD MILLION)
TABLE 22 MARKETING ANALYTICS MARKET SIZE, BY APPLICATION, 20192025 (USD MILLION)
6.2.3.1 Predictive modelling
6.2.3.2 Yield management
6.2.3.3 Product and service development strategies
6.2.3.4 Others
6.2.4 SALES ANALYTICS
TABLE 23 SALES ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 24 SALES ANALYTICS MARKET SIZE, BY REGION, 20192025 (USD MILLION)
TABLE 25 SALES ANALYTICS MARKET SIZE, BY APPLICATION, 20142019 (USD MILLION)
TABLE 26 SALES ANALYTICS MARKET SIZE, BY APPLICATION, 20192025 (USD MILLION)
6.2.4.1 Sales life cycle management
6.2.4.2 Sales rep efficiency management
6.2.4.3 Others
6.2.5 CUSTOMER ANALYTICS
TABLE 27 CUSTOMER ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 28 CUSTOMER ANALYTICS MARKET SIZE, BY REGION, 20192025 (USD MILLION)
TABLE 29 CUSTOMER ANALYTICS MARKET SIZE, BY APPLICATION, 20142019 (USD MILLION)
TABLE 30 CUSTOMER ANALYTICS MARKET SIZE, BY APPLICATION, 20192025 (USD MILLION)
6.2.5.1 Customer segmentation and clustering
6.2.5.2 Customer behavior analysis
6.2.5.3 Monitoring customer loyalty and satisfaction
6.2.5.4 Others
6.2.6 WEB AND SOCIAL MEDIA ANALYTICS
TABLE 31 WEB AND SOCIAL MEDIA ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 32 WEB AND SOCIAL MEDIA ANALYTICS MARKET SIZE, BY REGION, 20192025 (USD MILLION)
TABLE 33 WEB AND SOCIAL MEDIA ANALYTICS MARKET SIZE, BY APPLICATION, 20142019 (USD MILLION)
TABLE 34 WEB AND SOCIAL MEDIA ANALYTICS MARKET SIZE, BY APPLICATION, 20192025 (USD MILLION)
6.2.6.1 Social media management
6.2.6.2 Search engine optimization
6.2.6.3 Performance monitoring
6.2.6.4 Competitor benchmarking
6.2.7 SUPPLY CHAIN ANALYTICS
TABLE 35 SUPPLY CHAIN ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 36 SUPPLY CHAIN ANALYTICS MARKET SIZE, BY REGION, 20192025 (USD MILLION)
TABLE 37 SUPPLY CHAIN ANALYTICS MARKET SIZE, BY APPLICATION, 20142019 (USD MILLION)
TABLE 38 SUPPLY CHAIN ANALYTICS MARKET SIZE, BY APPLICATION, 20192025 (USD MILLION)
6.2.7.1 Distribution and logistics optimization
6.2.7.2 Inventory management
6.2.7.3 Manufacturing analysis
6.2.7.4 Others
6.2.8 NETWORK ANALYTICS
TABLE 39 NETWORK ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 40 NETWORK ANALYTICS MARKET SIZE, BY REGION, 20192025 (USD MILLION)
TABLE 41 NETWORK ANALYTICS MARKET SIZE, BY APPLICATION, 20142019 (USD MILLION)
TABLE 42 NETWORK ANALYTICS MARKET SIZE, BY APPLICATION, 20192025 (USD MILLION)
6.2.8.1 Intelligent network optimization
6.2.8.2 Traffic management
6.2.8.3 Others
6.2.9 OTHERS
TABLE 43 OTHERS: PREDICTIVE ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 44 OTHERS: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
6.3 SERVICES
FIGURE 31 MANAGED SERVICES SEGMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
TABLE 45 MARKET SIZE, BY SERVICE, 20142019 (USD MILLION)
TABLE 46 MARKET SIZE, BY SERVICE, 20192025 (USD MILLION)
6.3.1 MANAGED SERVICES
TABLE 47 MANAGED SERVICES: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 48 MANAGED SERVICES: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
6.3.2 PROFESSIONAL SERVICES
FIGURE 32 CONSULTING SEGMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
TABLE 49 PROFESSIONAL SERVICES: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 50 PROFESSIONAL SERVICES: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
TABLE 51 PROFESSIONAL SERVICE: MARKET SIZE, BY COMPONENT, 20142019 (USD MILLION)
TABLE 52 PROFESSIONAL SERVICES: MARKET SIZE, BY COMPONENT , 20192025 (USD MILLION)
6.3.2.1 Consulting
TABLE 53 CONSULTING MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 54 CONSULTING MARKET SIZE, BY REGION, 20192025 (USD MILLION)
6.3.2.2 Deployment and integration
TABLE 55 DEPLOYMENT AND INTEGRATION: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 56 DEPLOYMENT AND INTEGRATION: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
7 PREDICTIVE ANALYTICS MARKET, BY DEPLOYMENT MODE (Page No. - 112)
7.1 INTRODUCTION
7.1.1 DEPLOYMENT MODE: MARKET DRIVERS
7.1.2 DEPLOYMENT MODE: COVID-19 IMPACT
FIGURE 33 CLOUD SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
TABLE 57 MARKET SIZE, BY DEPLOYMENT MODE, 20142019 (USD MILLION)
TABLE 58 MARKET SIZE, BY DEPLOYMENT MODE, 20192025 (USD MILLION)
7.2 CLOUD
TABLE 59 CLOUD: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 60 CLOUD: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
7.3 ON-PREMISES
TABLE 61 ON-PREMISES: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 62 ON-PREMISES: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
8 PREDICTIVE ANALYTICS MARKET, BY ORGANIZATION SIZE (Page No. - 118)
8.1 INTRODUCTION
8.1.1 ORGANIZATION SIZE: MARKET DRIVERS
8.1.2 ORGANIZATION SIZE: COVID-19 IMPACT
FIGURE 34 SMALL AND MEDIUM-SIZED ENTERPRISES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
TABLE 63 MARKET SIZE, BY ORGANIZATION SIZE, 20142019 (USD MILLION)
TABLE 64 MARKET SIZE, BY ORGANIZATION SIZE, 20192025 (USD MILLION)
8.2 LARGE ENTERPRISES
TABLE 65 LARGE ENTERPRISES: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 66 LARGE ENTERPRISES: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
8.3 SMALL AND MEDIUM-SIZED ENTERPRISES
TABLE 67 SMALL AND MEDIUM-SIZED ENTERPRISES: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 68 SMALL AND MEDIUM-SIZED ENTERPRISES: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
9 PREDICTIVE ANALYTICS MARKET, BY VERTICAL (Page No. - 124)
9.1 INTRODUCTION
9.1.1 VERTICAL: MARKET DRIVERS
9.1.2 VERTICAL: COVID-19 IMPACT
9.2 PREDICTIVE ANALYTICS: ENTERPRISE USE CASES
FIGURE 35 BANKING, FINANCIAL SERVICES, AND INSURANCE VERTICAL TO HOLD LARGEST MARKET SIZE DURING FORECAST PERIOD
TABLE 69 MARKET SIZE, BY VERTICAL, 20142019 (USD MILLION)
TABLE 70 MARKET SIZE, BY VERTICAL, 20192025 (USD MILLION)
9.3 BANKING, FINANCIAL SERVICES, AND INSURANCE
TABLE 71 BANKING, FINANCIAL SERVICES, AND INSURANCE: USE CASES
TABLE 72 BANKING, FINANCIAL SERVICES, AND INSURANCE: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 73 BANKING, FINANCIAL SERVICES, AND INSURANCE: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
9.4 TELECOMMUNICATIONS AND IT
TABLE 74 TELECOMMUNICATIONS AND INFORMATION TECHNOLOGY: USE CASES
TABLE 75 TELECOMMUNICATIONS AND IT: PREDICTIVE ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 76 TELECOMMUNICATIONS AND IT: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
9.5 RETAIL AND ECOMMERCE
TABLE 77 RETAIL AND ECOMMERCE: USE CASES
TABLE 78 RETAIL AND ECOMMERCE: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 79 RETAIL AND ECOMMERCE: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
9.6 HEALTHCARE AND LIFE SCIENCES
TABLE 80 HEALTHCARE AND LIFE SCIENCES: USE CASES
TABLE 81 HEALTHCARE AND LIFE SCIENCES: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 82 HEALTHCARE AND LIFE SCIENCES: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
9.7 MANUFACTURING
TABLE 83 MANUFACTURING: USE CASES
TABLE 84 MANUFACTURING: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 85 MANUFACTURING: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
9.8 GOVERNMENT AND DEFENSE
TABLE 86 GOVERNMENT AND DEFENSE: USE CASES
TABLE 87 GOVERNMENT AND DEFENSE: PREDICTIVE ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 88 GOVERNMENT AND DEFENSE: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
9.9 ENERGY AND UTILITIES
TABLE 89 ENERGY AND UTILITIES: USE CASES
TABLE 90 ENERGY AND UTILITIES: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 91 ENERGY AND UTILITIES: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
9.10 TRANSPORTATION AND LOGISTICS
TABLE 92 TRANSPORTATION AND LOGISTICS: USE CASES
TABLE 93 TRANSPORTATION AND LOGISTICS: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 94 TRANSPORTATION AND LOGISTICS: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
9.11 OTHERS
TABLE 95 OTHERS: USE CASES
TABLE 96 OTHERS: MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 97 OTHERS: MARKET SIZE, BY REGION, 20192025 (USD MILLION)
10 PREDICTIVE ANALYTICS MARKET, BY REGION (Page No. - 145)
10.1 INTRODUCTION
FIGURE 36 JAPAN AND AUSTRALIA AND NEW ZEALAND TO ACCOUNT FOR HIGHEST CAGRS DURING FORECAST PERIOD
FIGURE 37 ASIA PACIFIC TO ACCOUNT FOR HIGHEST CAGR DURING FORECAST PERIOD
TABLE 98 MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 99 MARKET SIZE, BY REGION, 20192025 (USD MILLION)
10.2 NORTH AMERICA
10.2.1 NORTH AMERICA: MARKET DRIVERS
10.2.2 NORTH AMERICA: COVID-19 IMPACT
10.2.3 NORTH AMERICA: REGULATIONS
10.2.3.1 Health Insurance Portability and Accountability Act of 1996
10.2.3.2 California Consumer Privacy Act
10.2.3.3 GrammLeachBliley Act
10.2.3.4 Institute of Electrical and Electronics Engineers Standards Association
FIGURE 38 NORTH AMERICA: MARKET SNAPSHOT
TABLE 100 NORTH AMERICA: PREDICTIVE ANALYTICS MARKET SIZE, BY COMPONENT, 20142019 (USD MILLION)
TABLE 101 NORTH AMERICA: MARKET SIZE, BY COMPONENT, 20192025 (USD MILLION)
TABLE 102 NORTH AMERICA: MARKET SIZE, BY SOLUTION, 20142019 (USD MILLION)
TABLE 103 NORTH AMERICA: MARKET SIZE, BY SOLUTION, 20192025 (USD MILLION)
TABLE 104 NORTH AMERICA: MARKET SIZE, BY SERVICE, 20142019 (USD MILLION)
TABLE 105 NORTH AMERICA: MARKET SIZE, BY SERVICE, 20192025 (USD MILLION)
TABLE 106 NORTH AMERICA: MARKET SIZE, BY PROFESSIONAL SERVICE, 20142019 (USD MILLION)
TABLE 107 NORTH AMERICA: MARKET SIZE, BY PROFESSIONAL SERVICE, 20192025 (USD MILLION)
TABLE 108 NORTH AMERICA: MARKET SIZE, BY DEPLOYMENT MODE, 20142019 (USD MILLION)
TABLE 109 NORTH AMERICA: MARKET SIZE, BY DEPLOYMENT MODE, 20192025 (USD MILLION)
TABLE 110 NORTH AMERICA: MARKET SIZE, BY ORGANIZATION SIZE, 20142019 (USD MILLION)
TABLE 111 NORTH AMERICA: MARKET SIZE, BY ORGANIZATION SIZE, 20192025 (USD MILLION)
TABLE 112 NORTH AMERICA: MARKET SIZE, BY VERTICAL, 20142019 (USD MILLION)
TABLE 113 NORTH AMERICA: MARKET SIZE, BY VERTICAL, 20192025 (USD MILLION)
TABLE 114 NORTH AMERICA: MARKET SIZE, BY COUNTRY, 20142019 (USD MILLION)
TABLE 115 NORTH AMERICA: MARKET SIZE, BY COUNTRY, 20192025 (USD MILLION)
10.2.4 UNITED STATES
10.2.5 CANADA
10.3 EUROPE
10.3.1 EUROPE: MARKET DRIVERS
10.3.2 EUROPE: COVID-19 IMPACT
10.3.3 EUROPE: REGULATIONS
10.3.3.1 General Data Protection Regulation
10.3.3.2 European Committee for Standardization
10.3.3.3 European Technical Standards Institute
TABLE 116 EUROPE: PREDICTIVE ANALYTICS MARKET SIZE, BY COMPONENT, 20142019 (USD MILLION)
TABLE 117 EUROPE: MARKET SIZE, BY COMPONENT, 20192025 (USD MILLION)
TABLE 118 EUROPE: MARKET SIZE, BY SOLUTION, 20142019 (USD MILLION)
TABLE 119 EUROPE: MARKET SIZE, BY SOLUTION, 20192025 (USD MILLION)
TABLE 120 EUROPE: MARKET SIZE, BY SERVICE, 20142019 (USD MILLION)
TABLE 121 EUROPE: MARKET SIZE, BY SERVICE, 20192025 (USD MILLION)
TABLE 122 EUROPE: MARKET SIZE, BY PROFESSIONAL SERVICE, 20142019 (USD MILLION)
TABLE 123 EUROPE: MARKET SIZE, BY PROFESSIONAL SERVICE, 20192025 (USD MILLION)
TABLE 124 EUROPE: MARKET SIZE, BY DEPLOYMENT MODE, 20142019 (USD MILLION)
TABLE 125 EUROPE: MARKET SIZE, BY DEPLOYMENT MODE, 20192025 (USD MILLION)
TABLE 126 EUROPE: MARKET SIZE, BY ORGANIZATION SIZE, 20142019 (USD MILLION)
TABLE 127 EUROPE: MARKET SIZE, BY ORGANIZATION SIZE, 20192025 (USD MILLION)
TABLE 128 EUROPE: MARKET SIZE, BY VERTICAL, 20142019 (USD MILLION)
TABLE 129 EUROPE: MARKET SIZE, BY VERTICAL, 20192025 (USD MILLION)
TABLE 130 EUROPE: MARKET SIZE, BY COUNTRY, 20142019 (USD MILLION)
TABLE 131 EUROPE: MARKET SIZE, BY COUNTRY, 20192025 (USD MILLION)
10.3.4 UNITED KINGDOM
10.3.5 GERMANY
10.3.6 FRANCE
10.3.7 REST OF EUROPE
10.4 ASIA PACIFIC
10.4.1 ASIA PACIFIC: MARKET DRIVERS
10.4.2 ASIA PACIFIC: COVID-19 IMPACT
10.4.3 ASIA PACIFIC: REGULATIONS
10.4.3.1 International Organization for Standardization 27001
10.4.3.2 Personal Data Protection Act
FIGURE 39 ASIA PACIFIC: MARKET SNAPSHOT
TABLE 132 ASIA PACIFIC: PREDICTIVE ANALYTICS MARKET SIZE, BY COMPONENT, 20142019 (USD MILLION)
TABLE 133 ASIA PACIFIC: MARKET SIZE, BY COMPONENT, 20192025 (USD MILLION)
TABLE 134 ASIA PACIFIC: MARKET SIZE, BY SOLUTION, 20142019 (USD MILLION)
TABLE 135 ASIA PACIFIC: MARKET SIZE, BY SOLUTION, 20192025 (USD MILLION)
TABLE 136 ASIA PACIFIC: MARKET SIZE, BY SERVICE, 20142019 (USD MILLION)
TABLE 137 ASIA PACIFIC: MARKET SIZE, BY SERVICE, 20192025 (USD MILLION)
TABLE 138 ASIA PACIFIC: MARKET SIZE, BY PROFESSIONAL SERVICE, 20142019 (USD MILLION)
TABLE 139 ASIA PACIFIC: MARKET SIZE, BY PROFESSIONAL SERVICE, 20192025 (USD MILLION)
TABLE 140 ASIA PACIFIC: MARKET SIZE, BY DEPLOYMENT MODE, 20142019 (USD MILLION)
TABLE 141 ASIA PACIFIC: MARKET SIZE, BY DEPLOYMENT MODE, 20192025 (USD MILLION)
TABLE 142 ASIA PACIFIC: MARKET SIZE, BY ORGANIZATION SIZE, 20142019 (USD MILLION)
TABLE 143 ASIA PACIFIC: MARKET SIZE, BY ORGANIZATION SIZE, 20192025 (USD MILLION)
TABLE 144 ASIA PACIFIC: MARKET SIZE, BY VERTICAL, 20142019 (USD MILLION)
TABLE 145 ASIA PACIFIC: MARKET SIZE, BY VERTICAL, 20192025 (USD MILLION)
TABLE 146 ASIA PACIFIC: MARKET SIZE, BY COUNTRY, 20142019 (USD MILLION)
TABLE 147 ASIA PACIFIC: MARKET SIZE, BY COUNTRY, 20192025 (USD MILLION)
10.4.4 CHINA
10.4.5 JAPAN
10.4.6 AUSTRALIA AND NEW ZEALAND
10.4.7 REST OF ASIA PACIFIC
10.5 MIDDLE EAST AND AFRICA
10.5.1 MIDDLE EAST AND AFRICA: MARKET DRIVERS
10.5.2 MIDDLE EAST AND AFRICA: COVID-19 IMPACT
10.5.3 MIDDLE EAST AND AFRICA: REGULATIONS
10.5.3.1 Israeli Privacy Protection Regulations (Data Security), 5777-2017
10.5.3.2 Cloud Computing Framework
10.5.3.3 GDPR Applicability in KSA
10.5.3.4 Protection of Personal Information Act
10.5.3.5 TRAs IoT Regulatory Policy
TABLE 148 MIDDLE EAST AND AFRICA: PREDICTIVE ANALYTICS MARKET SIZE, BY COMPONENT, 20142019 (USD MILLION)
TABLE 149 MIDDLE EAST AND AFRICA: MARKET SIZE, BY COMPONENT, 20202025 (USD MILLION)
TABLE 150 MIDDLE EAST AND AFRICA: MARKET SIZE, BY SOLUTION, 20142019 (USD MILLION)
TABLE 151 MIDDLE EAST AND AFRICA: MARKET SIZE, BY SOLUTION, 20192025 (USD MILLION)
TABLE 152 MIDDLE EAST AND AFRICA: MARKET SIZE, BY SERVICE, 20142019 (USD MILLION)
TABLE 153 MIDDLE EAST AND AFRICA: MARKET SIZE, BY SERVICE, 20202025 (USD MILLION)
TABLE 154 MIDDLE EAST AND AFRICA: MARKET SIZE, BY PROFESSIONAL SERVICE, 20142019 (USD MILLION)
TABLE 155 MIDDLE EAST AND AFRICA: MARKET SIZE, BY PROFESSIONAL SERVICE, 20202025 (USD MILLION)
TABLE 156 MIDDLE EAST AND AFRICA: MARKET SIZE, BY DEPLOYMENT MODE, 20142019 (USD MILLION)
TABLE 157 MIDDLE EAST AND AFRICA: MARKET SIZE, BY DEPLOYMENT MODE, 20202025 (USD MILLION)
TABLE 158 MIDDLE EAST AND AFRICA: MARKET SIZE, BY ORGANIZATION SIZE, 20142019 (USD MILLION)
TABLE 159 MIDDLE EAST AND AFRICA: MARKET SIZE, BY ORGANIZATION SIZE, 20202025 (USD MILLION)
TABLE 160 MIDDLE EAST AND AFRICA: MARKET SIZE, BY VERTICAL, 20142019 (USD MILLION)
TABLE 161 MIDDLE EAST AND AFRICA: MARKET SIZE, BY VERTICAL, 20202025 (USD MILLION)
TABLE 162 MIDDLE EAST AND AFRICA: MARKET SIZE, BY COUNTRY, 20142019 (USD MILLION)
TABLE 163 MIDDLE EAST AND AFRICA: MARKET SIZE, BY COUNTRY, 20202025 (USD MILLION)
10.5.4 MIDDLE EAST
10.5.5 AFRICA
10.6 LATIN AMERICA
10.6.1 LATIN AMERICA: MARKET DRIVERS
10.6.2 LATIN AMERICA: COVID-19 IMPACT
10.6.3 LATIN AMERICA: REGULATIONS
10.6.3.1 Brazil Data Protection Law
10.6.3.2 Argentina Personal Data Protection Law No. 25.326
TABLE 164 LATIN AMERICA: PREDICTIVE ANALYTICS MARKET SIZE, BY COMPONENT, 20142019 (USD MILLION)
TABLE 165 LATIN AMERICA: MARKET SIZE, BY COMPONENT, 20202025 (USD MILLION)
TABLE 166 LATIN AMERICA: MARKET SIZE, BY SOLUTION, 20142019 (USD MILLION)
TABLE 167 LATIN AMERICA: MARKET SIZE, BY SOLUTION, 20192025 (USD MILLION)
TABLE 168 LATIN AMERICA: MARKET SIZE, BY SERVICE, 20142019 (USD MILLION)
TABLE 169 LATIN AMERICA: MARKET SIZE, BY SERVICE, 20202025 (USD MILLION)
TABLE 170 LATIN AMERICA: MARKET SIZE, BY PROFESSIONAL SERVICE, 20142019 (USD MILLION)
TABLE 171 LATIN AMERICA: MARKET SIZE, BY PROFESSIONAL SERVICE, 20202025 (USD MILLION)
TABLE 172 LATIN AMERICA: MARKET SIZE, BY DEPLOYMENT MODE, 20142019 (USD MILLION)
TABLE 173 LATIN AMERICA: MARKET SIZE, BY DEPLOYMENT MODE, 20202025 (USD MILLION)
TABLE 174 LATIN AMERICA: MARKET SIZE, BY ORGANIZATION SIZE, 20142019 (USD MILLION)
TABLE 175 LATIN AMERICA: MARKET SIZE, BY ORGANIZATION SIZE, 20202025 (USD MILLION)
TABLE 176 LATIN AMERICA: MARKET SIZE, BY VERTICAL, 20142019 (USD MILLION)
TABLE 177 LATIN AMERICA: MARKET SIZE, BY VERTICAL, 20202025 (USD MILLION)
TABLE 178 LATIN AMERICA: MARKET SIZE, BY COUNTRY, 20142019 (USD MILLION)
TABLE 179 LATIN AMERICA: MARKET SIZE, BY COUNTRY, 20202025 (USD MILLION)
10.6.4 BRAZIL
10.6.5 MEXICO
10.6.6 REST OF LATIN AMERICA
11 COMPETITIVE LANDSCAPE (Page No. - 199)
11.1 OVERVIEW
11.2 MARKET EVALUATION FRAMEWORK
FIGURE 40 MARKET EVALUATION FRAMEWORK
11.3 MARKET SHARE, 2020
FIGURE 41 MICROSOFT LEADS PREDICTIVE ANALYTICS MARKET IN 2020
11.4 HISTORIC REVENUE ANALYSIS OF KEY MARKET PLAYERS
FIGURE 42 REVENUE ANALYSIS OF KEY MARKET PLAYERS
11.5 KEY MARKET DEVELOPMENTS
11.5.1 NEW PRODUCT LAUNCHES AND PRODUCT ENHANCEMENTS
TABLE 180 NEW PRODUCT LAUNCHES AND PRODUCT ENHANCEMENTS, 20182020
11.5.2 BUSINESS EXPANSIONS
TABLE 181 BUSINESS EXPANSIONS, 20192020
11.5.3 MERGERS AND ACQUISITIONS
TABLE 182 MERGERS AND ACQUISITIONS, 20192020
11.5.4 PARTNERSHIPS, AGREEMENTS, CONTRACTS, AND COLLABORATIONS
TABLE 183 PARTNERSHIPS, AGREEMENTS, CONTRACTS, AND COLLABORATIONS, 20192020
12 COMPANY EVALUATION MATRIX AND COMPANY PROFILES (Page No. - 207)
12.1 OVERVIEW
12.2 COMPANY EVALUATION MATRIX DEFINITIONS AND METHODOLOGY
12.2.1 MARKET RANKING ANALYSIS, BY COMPANY
FIGURE 43 RANKING OF KEY PLAYERS, 2020
12.3 COMPANY EVALUATION MATRIX, 2020
12.3.1 STAR
12.3.2 EMERGING LEADERS
12.3.3 PERVASIVE
12.3.4 PARTICIPANT
FIGURE 44 PREDICTIVE ANALYTICS MARKET (GLOBAL), COMPANY EVALUATION MATRIX, 2020
12.4 COMPANY PROFILES
12.4.1 INTRODUCTION
(Business and financial overview, Solutions and services offered, Recent developments, MNM VIEW, Key strengths/right to win, Strategic choices made, and Weaknesses and competitive threats)*
12.4.2 MICROSOFT
FIGURE 45 MICROSOFT: COMPANY SNAPSHOT
12.4.3 IBM
FIGURE 46 IBM: COMPANY SNAPSHOT
12.4.4 ORACLE
FIGURE 47 ORACLE: COMPANY SNAPSHOT
12.4.5 SAP
FIGURE 48 SAP: COMPANY SNAPSHOT
12.4.6 SAS INSTITUTE
FIGURE 49 SAS INSTITUTE: COMPANY SNAPSHOT
12.4.7 GOOGLE
FIGURE 50 GOOGLE: COMPANY SNAPSHOT
12.4.8 SALESFORCE
FIGURE 51 SALESFORCE: COMPANY SNAPSHOT
12.4.9 AWS
FIGURE 52 AWS: COMPANY SNAPSHOT
12.4.10 HPE
FIGURE 53 HPE: COMPANY SNAPSHOT
12.4.11 TERADATA
FIGURE 54 TERADATA: COMPANY SNAPSHOT
12.4.12 ALTERYX
FIGURE 55 ALTERYX: COMPANY SNAPSHOT
12.4.13 FAIR ISSAC CORPORATION
FIGURE 56 FICO: COMPANY SNAPSHOT
12.4.14 ALTAIR
FIGURE 57 ALTAIR: COMPANY SNAPSHOT
12.4.15 DOMO
FIGURE 58 DOMO: COMPANY SNAPSHOT
12.4.16 CLOUDERA
FIGURE 59 CLOUDERA: COMPANY SNAPSHOT
12.4.17 BOARD INTERNATIONAL
12.4.18 TIBCO SOFTWARE
12.4.19 HITACHI VANTARA
12.4.20 HAPPIEST MINDS
12.4.21 DATAIKU
12.4.22 RAPIDMINER
12.4.23 QLIK
12.4.24 IBI
12.4.25 INFOR
12.5 STARTUP/SME EVALUATION MATRIX, 2020
12.5.1 PROGRESSIVE COMPANIES
12.5.2 RESPONSIVE COMPANIES
12.5.3 DYNAMIC COMPANIES
12.5.4 STARTING BLOCKS
FIGURE 60 PREDICTIVE ANALYTICS MARKET (GLOBAL), STARTUP/SME EVALUATION MATRIX, 2020
12.6 STARTUP/SME PROFILES
12.6.1 BIOFOURMIS
12.6.2 IN-MED PROGNOSTICS
12.6.3 AITO.AI
12.6.4 SYMEND
12.6.5 ONWARD HEALTH
12.6.6 UNIONCRATE
12.6.7 CYBERLABS
12.6.8 ACTIFY DATA LABS
12.6.9 AMLGO LABS
12.6.10 VERIMOS
*Details on Business and financial overview, Solutions and services offered, Recent developments, MNM VIEW, Key strengths/right to win, Strategic choices made, and Weaknesses and competitive threats might not be captured in case of unlisted companies.
13 APPENDIX (Page No. - 286)
13.1 ADJACENT AND RELATED MARKETS
13.1.1 INTRODUCTION
13.1.2 HADOOP BIG DATA ANALYTICS MARKETGLOBAL FORECAST TO 2025
13.1.2.1 Market definition
13.1.2.2 Market overview
TABLE 184 GLOBAL HADOOP BIG DATA ANALYTICS MARKET SIZE AND GROWTH RATE, 20142019 (USD MILLION, Y-O-Y%)
TABLE 185 GLOBAL HADOOP BIG DATA ANALYTICS MARKET SIZE AND GROWTH RATE, 20192025 (USD MILLION, Y-O-Y%)
13.1.2.2.1 Hadoop big data analytics market, by component
TABLE 186 HADOOP BIG DATA ANALYTICS MARKET SIZE, BY COMPONENT, 20142019 (USD MILLION)
TABLE 187 HADOOP BIG DATA ANALYTICS MARKET SIZE, BY COMPONENT, 20192025 (USD MILLION)
13.1.2.2.2 Hadoop big data analytics market, by deployment mode
TABLE 188 HADOOP BIG DATA ANALYTICS MARKET SIZE, BY DEPLOYMENT MODE, 20142019 (USD MILLION)
TABLE 189 HADOOP BIG DATA ANALYTICS MARKET SIZE, BY DEPLOYMENT MODE, 20192025 (USD MILLION)
13.1.2.2.3 Hadoop big data analytics market, by organization size
TABLE 190 HADOOP BIG DATA ANALYTICS MARKET SIZE, BY ORGANIZATION SIZE, 20142019 (USD MILLION)
TABLE 191 HADOOP BIG DATA ANALYTICS MARKET SIZE, BY ORGANIZATION SIZE, 20192025 (USD MILLION)
13.1.2.2.4 Hadoop big data analytics market, by vertical
TABLE 192 HADOOP BIG DATA ANALYTICS MARKET SIZE, BY VERTICAL, 20142019 (USD MILLION)
TABLE 193 HADOOP BIG DATA ANALYTICS MARKET SIZE, BY VERTICAL, 20192025 (USD MILLION)
13.1.2.2.5 Hadoop big data analytics market, by region
TABLE 194 HADOOP BIG DATA ANALYTICS MARKET SIZE, BY REGION, 20142019 (USD MILLION)
TABLE 195 HADOOP BIG DATA ANALYTICS MARKET SIZE, BY REGION, 20192025 (USD MILLION)
13.1.3 ANALYTICS AS A SERVICE MARKET GLOBAL FORECAST TO 2024
13.1.3.1 Market definition
13.1.3.2 Market overview
TABLE 196 GLOBAL ANALYTICS AS A SERVICE MARKET SIZE AND GROWTH RATE, 20172024 (USD MILLION AND Y-O-Y %)
13.1.3.2.1 Analytics as a service market, by component
TABLE 197 ANALYTICS AS A SERVICE MARKET SIZE, BY COMPONENT, 20172024 (USD MILLION)
TABLE 198 SOLUTIONS: ANALYTICS AS A SERVICE MARKET SIZE, BY TYPE , 20172024 (USD MILLION)
TABLE 199 SERVICES: ANALYTICS AS A SERVICE MARKET SIZE, BY TYPE, 20172024 (USD MILLION)
TABLE 200 PROFESSIONAL SERVICES: ANALYTICS AS A SERVICE MARKET SIZE, BY TYPE , 20172024 (USD MILLION)
13.1.3.2.2 Analytics as a service market, by deployment mode
TABLE 201 ANALYTICS AS A SERVICE MARKET SIZE, BY DEPLOYMENT MODE, 20172024 (USD MILLION)
13.1.3.2.3 Analytics as a service market, by organization size
TABLE 202 ANALYTICS AS A SERVICE MARKET SIZE, BY ORGANIZATION SIZE, 20172024 (USD MILLION)
13.1.3.2.4 Analytics as a service market, by industry vertical
TABLE 203 ANALYTICS AS A SERVICE MARKET SIZE, BY INDUSTRY VERTICAL, 20172024 (USD MILLION)
13.1.3.2.5 Analytics as a service market, by region
TABLE 204 ANALYTICS AS A SERVICE MARKET SIZE, BY REGION, 20172024 (USD MILLION)
13.1.4 PRESCRIPTIVE ANALYTICS MARKET GLOBAL FORECAST TO 2021
13.1.4.1 Market definition
13.1.4.2 Market overview
TABLE 205 GLOBAL PRESCRIPTIVE ANALYTICS MARKET SIZE AND GROWTH RATE, 20162021 (USD MILLION AND Y-O-Y %)
13.1.4.2.1 Prescriptive analytics market, by component
TABLE 206 PRESCRIPTIVE ANALYTICS MARKET SIZE, BY COMPONENT, 20162021 (USD MILLION)
TABLE 207 SERVICES: PRESCRIPTIVE ANALYTICS MARKET SIZE, BY TYPE, 20162021 (USD MILLION)
13.1.4.2.2 Prescriptive analytics market, by deployment mode
TABLE 208 PRESCRIPTIVE ANALYTICS MARKET SIZE, BY DEPLOYMENT MODE, 20162021 (USD MILLION)
13.1.4.2.3 Prescriptive analytics market, by business function
TABLE 209 PRESCRIPTIVE ANALYTICS MARKET SIZE, BY BUSINESS FUNCTION, 20162021 (USD MILLION)
13.1.4.2.4 Prescriptive analytics market, by vertical
TABLE 210 PRESCRIPTIVE ANALYTICS MARKET SIZE, BY VERTICAL, 20162021 (USD MILLION)
13.1.4.2.5 Prescriptive analytics market, by region
TABLE 211 PRESCRIPTIVE ANALYTICS MARKET SIZE, BY REGION, 20162021 (USD MILLION)
13.2 INDUSTRY EXPERTS
13.3 DISCUSSION GUIDE
13.4 KNOWLEDGE STORE: MARKETSANDMARKETS SUBSCRIPTION PORTAL
13.5 AVAILABLE CUSTOMIZATIONS
13.6 RELATED REPORTS
13.7 AUTHOR DETAILS
The study involved four major activities in estimating the current market size of the predictive analytics market. Extensive secondary research was done to collect information on the market, peer market, and parent market. The next step was to validate these findings, assumptions, and sizing with industry experts across the value chain through primary research. Both top-down and bottom-up approaches were used to estimate the total market size. After that, the market breakup and data triangulation procedures were used to estimate the market size of the segments and subsegments of the predictive analytics market.
In the secondary research process, various secondary sources, such as Analytics Insight, Data Science and Artificial Intelligence for Communications, and related magazines, have been referred to for identifying and collecting information for this study. Secondary sources included annual reports; press releases & investor presentations of companies; whitepapers, certified publications, and articles by recognized authors; gold standard and silver standard websites; Research and Development (R&D) organizations; regulatory bodies; and databases.
Various primary sources from both supply and demand sides were interviewed to obtain qualitative and quantitative information on the market. The primary sources from the supply side included various industry experts, including Chief X Officers (CXOs); Vice Presidents (VPs); directors from business development, marketing, and product development/innovation teams; related key executives from Predictive analytics solution vendors, system integrators, professional service providers, industry associations, and consultants; and key opinion leaders. All possible parameters that affect the market covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
The following is the breakup of primary profiles:
To know about the assumptions considered for the study, download the pdf brochure
Both top-down and bottom-up approaches were used to estimate and validate the total size of the Predictive analytics market. The top-down approach was used to derive the revenue contribution of top vendors and their offerings in the market. The bottom-up approach was used to arrive at the overall market size of the global predictive analytics market using key companies revenue and their offerings in the market. The research methodology used to estimate the market size includes the following:
After arriving at the overall market size using the market size estimation processes as explained above, the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation, and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.
With the given market data, MarketsandMarkets offers customizations as per the companys specific needs. The following customization options are available for the report:
Benchmarking the rapid strategy shifts of the Top 100 companies in the Predictive Analytics Market
Request For Special Pricing
Growth opportunities and latent adjacency in Predictive Analytics Market
According to us, implementing predictive analytics would be a good strategy for an organization: With the increasing volume and variety of business data, due to increasing adoption of emerging technologies such as Artificial Intelligence, Machine Learning, Internet of Things and Mobility, organizations require real-time insights from those datasets for faster and better decision making. Predictive analytics helps industries in understanding the customer perception by providing competitive market edge and an ability to orchestrate business decisions rapidly. It also provides operational excellence by improving productivity and profitability across organizations, and help the organization for achieving financial efficiency, informed decision making, and better data visualization for both structured as well as unstructured data sets. Organizations across industry verticals (including BFSI, Retail, Healthcare, Government, Telecom, and so on) are implementing predictive analytics for multiple business applications to get these benefits and most of them are achieving better results. For example, HSBC recently partnered with an AI start-up Ayasdi to automate anti-money laundering investigations using predictive modelling and they saw the number of investigations by 20% without reducing the number of cases referred for more scrutiny. Vodafone is using CleverTaps customer analytics solution to engage their users and drive conversions. Using the predictive analytics tool, Vodafone could successfully scale personalized campaigns to double the conversions. Hence, predictive analytics is considered as a new mantra for businesses across industries because it helps organizations achieving varied range of business outcomes, higher customer satisfaction, and efficient operations. It is now widely being used by marketing, sales and finance teams to achieve desirable business performance.
Do you think implementing predictive analysts will be a good strategy? Would it be good with an automation platform?