The cognitive computing market is expected to expand its roots at a strong CAGR of 26.3% during the forecast period. The market is likely to hold a revenue of US$ 18.03 billion in 2023 while it is anticipated to cross a value of US$ 188.2 billion by 2033.
The rise in concern among all the leading business organizations to analyze a large volume of data to estimate the risk associated with any strategic initiative is expected to accelerate market growth.
Factors such as the rise in big data analytics, developments of machine-to-machine technologies, and an increase in demand for a better customer experience led the market growth.
The human-like interface, advanced processing, better decision-making results, and technological advancements in corporate spaces are expected to garner growth. Furthermore, the challenges faced by the industry are anticipated to be solved through cognitive systems. A wide range of applications involving healthcare, government, IT & telecom, and manufacturing. The expanding application of smart technologies like artificial intelligence, machine learning, and big data are also projected to enrich the cognitive computing system experience.
The end-user brands are looking forward to adopting systems that increase and enhanced the adaptiveness of operations. The interactive, Iterative, contextual, and stateful capabilities of these systems inflict higher productivity and efficiency in any operation.
FMI explains how cognitive computing systems benefit different vertical operations. For example, the healthcare sector untangles complex and unstructured healthcare data. This data involves information regarding diagnoses, conditions, and patient history. For the retail sector, the system works on consumer data and delivers personalized suggestions. In the banking and finance industry, the system diversifies the data dimensions and gathers information through multiple sources to provide an idea about ant project.
Lastly, cognitive computing has properties that help these many applications. Some noticeable properties that the systems deliver are analytical accuracy, business process efficiency, customer interaction and experience, and service quality & employee productivity.
Attributes | Details |
---|---|
Cognitive Computing Market CAGR (2023 to 2033) | 26.3% |
Cognitive Computing Market Size (2023) | US$ 18.03 billion |
Cognitive Computing Market Size (2033) | US$ 188.2 billion |
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There is an increase in the demand for cognitive systems in large organizations and this is expected to increase in SMBs owing to cloud-based services. As cloud-based deployment decreases the cost of deploying cognitive computing in the organization, there is a subsequent rise in the overall demand for cloud-based services.
The rise in big data analytics, developments of machine-to-machine technologies, and an increase in demand for a better customer experience. In addition, industries such as BFSI, social websites, healthcare, and e-commerce have witnessed a rapid increase in transaction information and customer data.
To develop cognitive solutions, a high upfront investment is required to set up maintenance architecture and infrastructure which leads to high operational costs.
Issues relating to government standards and uncertain regulatory compliance are also expected to limit the growth of the cognitive computing market. In addition, the market is anticipated to experience several challenges owing to the lack of awareness among SMEs.
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One of the significant market key trends is the rising demand for big data analytics across various industries such as IT and telecom, healthcare, aerospace & defense. The rising volume of data and the adoption of big data tools are likely to drive the demand for big data analytics.
NLP technology helps in analyzing unstructured data for improving customer needs, expectations, and better customer experience. Hence, with the help of NLP, organizations get better insights into the optimization of business processes, reduction in operational cost, and customer perception.
Cognitive Computing Market:
Attributes | Cognitive Computing Market |
---|---|
CAGR (2023 to 2033) | 26.3% |
Market Value (2033) | US$ 188.2 billion |
Growth Factor | An increase in the development of machine-to-machine technologies. |
Opportunity | Technological proliferation is leading to the adoption of innovative techniques, such as machine learning & automated reasoning, in dispensing systems. |
Key Trends | The necessity for industries, such as healthcare, retail, and financial institutions, to analyze large volumes of data optimally on a real-time basis, is presumed to impact the industry favorably. |
Calibration Services Market:
Attributes | Calibration Services Market |
---|---|
CAGR (2023 to 2033) | 39.6% |
Market Value (2033) | US$ 402.5 billion |
Growth Factor | The need to achieve robotic autonomy to stay competitive in a global market. |
Opportunity | AI is being used not only to automate tasks but also to diagnose equipment malfunctions or detect product anomalies. |
Key Trends | Businesses have started considering fully autonomous robots that can perceive, interact, and conceptualize the world around them. |
Electronic Test Equipment Market:
Attributes | Electronic Test Equipment Market |
---|---|
CAGR (2023 to 2033) | 38.7% |
Market Value (2033) | US$ 212.5 billion |
Growth Factor | Technological advancement and proliferation in data generation. |
Opportunity | The advancements in deep learning algorithms |
Key Trends | Machine learning-enabled solutions are being significantly adopted by organizations worldwide to enhance customer experience, and ROI, and to gain a competitive edge in business operations. |
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Countries | Revenue Share % (2023) |
---|---|
United States | 27.3% |
Germany | 7.2% |
Japan | 5.4% |
Australia | 2.1% |
Countries | CAGR % (2023 to 2033) |
---|---|
China | 29.3% |
India | 23.1% |
United Kingdom | 25.1% |
The global cognitive computing market is divided into North America, South America, Europe, Asia Pacific, the Middle East, and Africa based on geography. The North American region is expected to hold a substantial share of the global cognitive computing market. While the Asia Pacific (APAC) region is expected to grow at a significant rate during the forecast period.
North America is a significant revenue contributor in the global market. The region is witnessing significant developments in the market, owing to the increasing usage of the internet and startups adopting cognitive computing solutions.
In addition, organizations, especially in the United States, have started using cognitive computing solutions to analyze huge volumes of data to provide better solutions. New technological advancements, such as 5G and IoT have also aided in the boost of cognitive solutions in this region.
Cognitive computing demand in the United States has held a market share of 27.3% in 2022. Moreover, the United Kingdom and China are expected to thrive at growth forecasts of 25.1% and 29.3% respectively, throughout the forecast period.
The growth is attributed to the expanding manufacturing space in China while India’s forecast for the IT and telecom industry is rich and is projected to gain more traction for the market. China and India both emerging superpowers are anticipated to expand their market space as both build new healthcare, government-based infrastructure.
Category | By Deployment Type |
---|---|
Leading Segment | On-Premises |
Market Share (2022) | 57.6% |
Category | By Industry Type |
---|---|
Leading Segment | IT and telecom |
Market Share (2022) | 17.5% |
The cognitive computing market can be segmented on the basis of deployment, application, industry, end user, and region. Based on the deployment, the market can be segmented into the following: on-premise, and cloud.
By deployment, the on-premise category of the cognitive computing market is expected to dominate the market as it held a market share of 57.6% in 2022. The growth is attributed to its capabilities such as data mining, pattern recognition, and natural language processing, which in turn is expected to accelerate the market growth over the analysis period.
According to FMI, on the basis of application, the market can be segmented into the following: diagnostic APIs, robots, cyber security, farm mechanization, social media monitoring, self-driving cars, gaming, video surveillance, eLearning, IT infrastructure management, supply chain management, and others. By application, the diagnostic APIs category is expected to dominate the market and is predicted to reach a CAGR of 27.9%, during the forecast period.
Based on Industry, the market can be segmented into the following: healthcare, BFSI, IT and telecom, manufacturing, energy & utility, retail, aerospace & defense, government, transportation, agriculture, media & entertainment, education, and. Based on end-user, the market can be segmented into the following: large enterprises, small and medium enterprises (SMEs), and public sector. The IT and telecom segment leads the market space as the IT industries are on the rise in emerging Asian economies. The demand for effective communication, data tracking, and evaluation techniques is likely to flourish in the segment during the forecast period.
3M, Google LLC, Hewlett Packard Enterprise Development LP, International Business Machines Corporation, Microsoft Corporation, Nuance Communications Inc., Oracle Corporation, SAP SE, SAS Institute Inc., and Tibco Software Inc., among others, are the top companies in the global cognitive computing market.
With a sizable cognitive computing market share, these main firms are concentrating on growing their consumer base in new countries. These businesses are making use of strategic collaboration initiatives to grow their market share and profits.
Mid-size and smaller businesses, on the other hand, are expanding their market presence by gaining new contracts and entering new markets, thanks to technical developments and product innovations.
Market Developments
The market is anticipated to be valued US$ 18.03 billion in 2023.
The market is estimated to evolve at a CAGR of 26.3% till 2033.
The China market is expected to develop at a CAGR of 29.3%.
By 2033, the market is estimated to be worth US$ 188.2 billion.
In the United States, the market share to stand at 27.3%.
1. Executive Summary 1.1. Global Market Outlook 1.2. Demand-side Trends 1.3. Supply-side Trends 1.4. Technology Roadmap Analysis 1.5. Analysis and Recommendations 2. Market Overview 2.1. Market Coverage / Taxonomy 2.2. Market Definition / Scope / Limitations 3. Market Background 3.1. Market Dynamics 3.1.1. Drivers 3.1.2. Restraints 3.1.3. Opportunity 3.1.4. Trends 3.2. Scenario Forecast 3.2.1. Demand in Optimistic Scenario 3.2.2. Demand in Likely Scenario 3.2.3. Demand in Conservative Scenario 3.3. Opportunity Map Analysis 3.4. Investment Feasibility Matrix 3.5. PESTLE and Porter’s Analysis 3.6. Regulatory Landscape 3.6.1. By Key Regions 3.6.2. By Key Countries 3.7. Regional Parent Market Outlook 4. Global Market Analysis 2018 to 2022 and Forecast, 2023 to 2033 4.1. Historical Market Size Value (US$ Million) Analysis, 2018 to 2022 4.2. Current and Future Market Size Value (US$ Million) Projections, 2023 to 2033 4.2.1. Y-o-Y Growth Trend Analysis 4.2.2. Absolute $ Opportunity Analysis 5. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Deployment 5.1. Introduction / Key Findings 5.2. Historical Market Size Value (US$ Million) Analysis By Deployment, 2018 to 2022 5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Deployment, 2023 to 2033 5.3.1. On-Premise 5.3.2. Cloud 5.4. Y-o-Y Growth Trend Analysis By Deployment, 2018 to 2022 5.5. Absolute $ Opportunity Analysis By Deployment, 2023 to 2033 6. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Application 6.1. Introduction / Key Findings 6.2. Historical Market Size Value (US$ Million) Analysis By Application, 2018 to 2022 6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Application, 2023 to 2033 6.3.1. Diagnostic APIs 6.3.2. Robots 6.3.3. Cyber Security 6.3.4. Farm Mechanization 6.3.5. Social Media Monitoring 6.3.6. Self-Driving Cars 6.3.7. Gaming 6.3.8. Video Surveillance 6.3.9. e-Learning 6.3.10. IT Infrastructure Management 6.3.11. Supply Chain Management 6.3.12. Others 6.4. Y-o-Y Growth Trend Analysis By Application, 2018 to 2022 6.5. Absolute $ Opportunity Analysis By Application, 2023 to 2033 7. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Industry 7.1. Introduction / Key Findings 7.2. Historical Market Size Value (US$ Million) Analysis By Industry, 2018 to 2022 7.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Industry, 2023 to 2033 7.3.1. Healthcare 7.3.2. BFSI 7.3.3. IT and Telecom 7.3.4. Manufacturing 7.3.5. Energy & Utility 7.3.6. Retail 7.3.7. Aerospace & Defense 7.3.8. Government 7.3.9. Transportation 7.3.10. Agriculture 7.3.11. Media & Entertainment 7.3.12. Others 7.4. Y-o-Y Growth Trend Analysis By Industry, 2018 to 2022 7.5. Absolute $ Opportunity Analysis By Industry, 2023 to 2033 8. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By End User 8.1. Introduction / Key Findings 8.2. Historical Market Size Value (US$ Million) Analysis By End User, 2018 to 2022 8.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By End User, 2023 to 2033 8.3.1. Large Enterprises 8.3.2. Small and Medium Enterprises (SMEs) 8.3.3. Public Sector 8.4. Y-o-Y Growth Trend Analysis By End User, 2018 to 2022 8.5. Absolute $ Opportunity Analysis By End User, 2023 to 2033 9. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Region 9.1. Introduction 9.2. Historical Market Size Value (US$ Million) Analysis By Region, 2018 to 2022 9.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2023 to 2033 9.3.1. North America 9.3.2. Latin America 9.3.3. Europe 9.3.4. South Asia 9.3.5. East Asia 9.3.6. Oceania 9.3.7. MEA 9.4. Market Attractiveness Analysis By Region 10. North America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 10.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 10.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 10.2.1. By Country 10.2.1.1. USA 10.2.1.2. Canada 10.2.2. By Deployment 10.2.3. By Application 10.2.4. By Industry 10.2.5. By End User 10.3. Market Attractiveness Analysis 10.3.1. By Country 10.3.2. By Deployment 10.3.3. By Application 10.3.4. By Industry 10.3.5. By End User 10.4. Key Takeaways 11. Latin America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 11.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 11.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 11.2.1. By Country 11.2.1.1. Brazil 11.2.1.2. Mexico 11.2.1.3. Rest of Latin America 11.2.2. By Deployment 11.2.3. By Application 11.2.4. By Industry 11.2.5. By End User 11.3. Market Attractiveness Analysis 11.3.1. By Country 11.3.2. By Deployment 11.3.3. By Application 11.3.4. By Industry 11.3.5. By End User 11.4. Key Takeaways 12. Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 12.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 12.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 12.2.1. By Country 12.2.1.1. Germany 12.2.1.2. UK 12.2.1.3. France 12.2.1.4. Spain 12.2.1.5. Italy 12.2.1.6. Rest of Europe 12.2.2. By Deployment 12.2.3. By Application 12.2.4. By Industry 12.2.5. By End User 12.3. Market Attractiveness Analysis 12.3.1. By Country 12.3.2. By Deployment 12.3.3. By Application 12.3.4. By Industry 12.3.5. By End User 12.4. Key Takeaways 13. South Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 13.2.1. By Country 13.2.1.1. India 13.2.1.2. Malaysia 13.2.1.3. Singapore 13.2.1.4. Thailand 13.2.1.5. Rest of South Asia 13.2.2. By Deployment 13.2.3. By Application 13.2.4. By Industry 13.2.5. By End User 13.3. Market Attractiveness Analysis 13.3.1. By Country 13.3.2. By Deployment 13.3.3. By Application 13.3.4. By Industry 13.3.5. By End User 13.4. Key Takeaways 14. East Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 14.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 14.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 14.2.1. By Country 14.2.1.1. China 14.2.1.2. Japan 14.2.1.3. South Korea 14.2.2. By Deployment 14.2.3. By Application 14.2.4. By Industry 14.2.5. By End User 14.3. Market Attractiveness Analysis 14.3.1. By Country 14.3.2. By Deployment 14.3.3. By Application 14.3.4. By Industry 14.3.5. By End User 14.4. Key Takeaways 15. Oceania Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 15.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 15.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 15.2.1. By Country 15.2.1.1. Australia 15.2.1.2. New Zealand 15.2.2. By Deployment 15.2.3. By Application 15.2.4. By Industry 15.2.5. By End User 15.3. Market Attractiveness Analysis 15.3.1. By Country 15.3.2. By Deployment 15.3.3. By Application 15.3.4. By Industry 15.3.5. By End User 15.4. Key Takeaways 16. MEA Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 16.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 16.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 16.2.1. By Country 16.2.1.1. GCC Countries 16.2.1.2. South Africa 16.2.1.3. Israel 16.2.1.4. Rest of MEA 16.2.2. By Deployment 16.2.3. By Application 16.2.4. By Industry 16.2.5. By End User 16.3. Market Attractiveness Analysis 16.3.1. By Country 16.3.2. By Deployment 16.3.3. By Application 16.3.4. By Industry 16.3.5. By End User 16.4. Key Takeaways 17. Key Countries Market Analysis 17.1. USA 17.1.1. Pricing Analysis 17.1.2. Market Share Analysis, 2022 17.1.2.1. By Deployment 17.1.2.2. By Application 17.1.2.3. By Industry 17.1.2.4. By End User 17.2. Canada 17.2.1. Pricing Analysis 17.2.2. Market Share Analysis, 2022 17.2.2.1. By Deployment 17.2.2.2. By Application 17.2.2.3. By Industry 17.2.2.4. By End User 17.3. Brazil 17.3.1. Pricing Analysis 17.3.2. Market Share Analysis, 2022 17.3.2.1. By Deployment 17.3.2.2. By Application 17.3.2.3. By Industry 17.3.2.4. By End User 17.4. Mexico 17.4.1. Pricing Analysis 17.4.2. Market Share Analysis, 2022 17.4.2.1. By Deployment 17.4.2.2. By Application 17.4.2.3. By Industry 17.4.2.4. By End User 17.5. Germany 17.5.1. Pricing Analysis 17.5.2. Market Share Analysis, 2022 17.5.2.1. By Deployment 17.5.2.2. By Application 17.5.2.3. By Industry 17.5.2.4. By End User 17.6. UK 17.6.1. Pricing Analysis 17.6.2. Market Share Analysis, 2022 17.6.2.1. By Deployment 17.6.2.2. By Application 17.6.2.3. By Industry 17.6.2.4. By End User 17.7. France 17.7.1. Pricing Analysis 17.7.2. Market Share Analysis, 2022 17.7.2.1. By Deployment 17.7.2.2. By Application 17.7.2.3. By Industry 17.7.2.4. By End User 17.8. Spain 17.8.1. Pricing Analysis 17.8.2. Market Share Analysis, 2022 17.8.2.1. By Deployment 17.8.2.2. By Application 17.8.2.3. By Industry 17.8.2.4. By End User 17.9. Italy 17.9.1. Pricing Analysis 17.9.2. Market Share Analysis, 2022 17.9.2.1. By Deployment 17.9.2.2. By Application 17.9.2.3. By Industry 17.9.2.4. By End User 17.10. India 17.10.1. Pricing Analysis 17.10.2. Market Share Analysis, 2022 17.10.2.1. By Deployment 17.10.2.2. By Application 17.10.2.3. By Industry 17.10.2.4. By End User 17.11. Malaysia 17.11.1. Pricing Analysis 17.11.2. Market Share Analysis, 2022 17.11.2.1. By Deployment 17.11.2.2. By Application 17.11.2.3. By Industry 17.11.2.4. By End User 17.12. Singapore 17.12.1. Pricing Analysis 17.12.2. Market Share Analysis, 2022 17.12.2.1. By Deployment 17.12.2.2. By Application 17.12.2.3. By Industry 17.12.2.4. By End User 17.13. Thailand 17.13.1. Pricing Analysis 17.13.2. Market Share Analysis, 2022 17.13.2.1. By Deployment 17.13.2.2. By Application 17.13.2.3. By Industry 17.13.2.4. By End User 17.14. China 17.14.1. Pricing Analysis 17.14.2. Market Share Analysis, 2022 17.14.2.1. By Deployment 17.14.2.2. By Application 17.14.2.3. By Industry 17.14.2.4. By End User 17.15. Japan 17.15.1. Pricing Analysis 17.15.2. Market Share Analysis, 2022 17.15.2.1. By Deployment 17.15.2.2. By Application 17.15.2.3. By Industry 17.15.2.4. By End User 17.16. South Korea 17.16.1. Pricing Analysis 17.16.2. Market Share Analysis, 2022 17.16.2.1. By Deployment 17.16.2.2. By Application 17.16.2.3. By Industry 17.16.2.4. By End User 17.17. Australia 17.17.1. Pricing Analysis 17.17.2. Market Share Analysis, 2022 17.17.2.1. By Deployment 17.17.2.2. By Application 17.17.2.3. By Industry 17.17.2.4. By End User 17.18. New Zealand 17.18.1. Pricing Analysis 17.18.2. Market Share Analysis, 2022 17.18.2.1. By Deployment 17.18.2.2. By Application 17.18.2.3. By Industry 17.18.2.4. By End User 17.19. GCC Countries 17.19.1. Pricing Analysis 17.19.2. Market Share Analysis, 2022 17.19.2.1. By Deployment 17.19.2.2. By Application 17.19.2.3. By Industry 17.19.2.4. By End User 17.20. South Africa 17.20.1. Pricing Analysis 17.20.2. Market Share Analysis, 2022 17.20.2.1. By Deployment 17.20.2.2. By Application 17.20.2.3. By Industry 17.20.2.4. By End User 17.21. Israel 17.21.1. Pricing Analysis 17.21.2. Market Share Analysis, 2022 17.21.2.1. By Deployment 17.21.2.2. By Application 17.21.2.3. By Industry 17.21.2.4. By End User 18. Market Structure Analysis 18.1. Competition Dashboard 18.2. Competition Benchmarking 18.3. Market Share Analysis of Top Players 18.3.1. By Regional 18.3.2. By Deployment 18.3.3. By Application 18.3.4. By Industry 18.3.5. By End User 19. Competition Analysis 19.1. Competition Deep Dive 19.1.1. 3M 19.1.1.1. Overview 19.1.1.2. Product Portfolio 19.1.1.3. Profitability by Market Segments 19.1.1.4. Sales Footprint 19.1.1.5. Strategy Overview 19.1.1.5.1. Marketing Strategy 19.1.2. Google LLC 19.1.2.1. Overview 19.1.2.2. Product Portfolio 19.1.2.3. Profitability by Market Segments 19.1.2.4. Sales Footprint 19.1.2.5. Strategy Overview 19.1.2.5.1. Marketing Strategy 19.1.3. Hewlett Packard Enterprise Development LP 19.1.3.1. Overview 19.1.3.2. Product Portfolio 19.1.3.3. Profitability by Market Segments 19.1.3.4. Sales Footprint 19.1.3.5. Strategy Overview 19.1.3.5.1. Marketing Strategy 19.1.4. International Business Machines Corporation 19.1.4.1. Overview 19.1.4.2. Product Portfolio 19.1.4.3. Profitability by Market Segments 19.1.4.4. Sales Footprint 19.1.4.5. Strategy Overview 19.1.4.5.1. Marketing Strategy 19.1.5. Microsoft Corporation 19.1.5.1. Overview 19.1.5.2. Product Portfolio 19.1.5.3. Profitability by Market Segments 19.1.5.4. Sales Footprint 19.1.5.5. Strategy Overview 19.1.5.5.1. Marketing Strategy 19.1.6. Nuance Communications, Inc. 19.1.6.1. Overview 19.1.6.2. Product Portfolio 19.1.6.3. Profitability by Market Segments 19.1.6.4. Sales Footprint 19.1.6.5. Strategy Overview 19.1.6.5.1. Marketing Strategy 19.1.7. Oracle Corporation 19.1.7.1. Overview 19.1.7.2. Product Portfolio 19.1.7.3. Profitability by Market Segments 19.1.7.4. Sales Footprint 19.1.7.5. Strategy Overview 19.1.7.5.1. Marketing Strategy 19.1.8. SAP SE 19.1.8.1. Overview 19.1.8.2. Product Portfolio 19.1.8.3. Profitability by Market Segments 19.1.8.4. Sales Footprint 19.1.8.5. Strategy Overview 19.1.8.5.1. Marketing Strategy 19.1.9. SAS Institute Inc. 19.1.9.1. Overview 19.1.9.2. Product Portfolio 19.1.9.3. Profitability by Market Segments 19.1.9.4. Sales Footprint 19.1.9.5. Strategy Overview 19.1.9.5.1. Marketing Strategy 19.1.10. Tibco Software Inc. 19.1.10.1. Overview 19.1.10.2. Product Portfolio 19.1.10.3. Profitability by Market Segments 19.1.10.4. Sales Footprint 19.1.10.5. Strategy Overview 19.1.10.5.1. Marketing Strategy 20. Assumptions & Acronyms Used 21. Research Methodology
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