[250 Pages Report] Newly released Predictive Analytics Market analysis report by Future Market Insights shows that global sales of Predictive Analytics Market in 2021 was held at US$ 10.5 Billion. With 15.8% CAGR during 2022 to 2032, the market is likely to reach a valuation of US$ 55.5 Bn by 2032. Revenue through BFSI is projected to register the highest CAGR of 15.7% during 2022 to 2032.
| Attributes | Details |
|---|---|
| Global Predictive Analytics Market CAGR (2022 to 2032) | 15.8% |
| Global Predictive Analytics Market Size (2022) | US$ 12.8 Billion |
| Global Predictive Analytics Market Size (2032) | US$ 55.5 Billion |
| North America Predictive Analytics Market Size (2022) | US$ 5.1 Billion |
| U.S. Predictive Analytics Market CAGR (2022 to 2032) | 15.7% |
| Key Companies Covered |
|
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As per the Predictive Analytics Market research by Future Market Insights - a market research and competitive intelligence provider, historically, from 2015 to 2021, market value of the Predictive Analytics Market increased at around 27.9% CAGR.
The market is expanding due to an increase in awareness among companies about the huge volume of data created to anticipate future events utilizing predictive analytic solutions. Furthermore, the increased use of the internet, along with the availability of several ways to access the internet, has resulted in a rise in data creation.
As a result, exploiting this data to generate precise business plans and decisions improves revenue, creating demand for predictive analytics solutions.
The e-commerce sector has enhanced customers' usual purchase experiences. The most important aspects for increasing business sales are dedicated social media marketing and consumer perception analysis. Since linked gadgets are becoming more popular, businesses are focusing on real-time analysis of consumer purchasing behavior. Real-time analytics information may also be utilized to build personalized offers to boost client retention.
As big data becomes more prevalent, predictive analysis is projected to be applied in Finance and Human Resources. Factors such as a scarcity of experienced IT personnel and hefty implementation costs may constrict industry expansion.
Furthermore, data integrity provides a greater barrier in the application of predictive analytics technology in many end-user verticals, which is expected to increase slowly throughout the projected period. High time consumption, the demand for constant trial, and testing of the sophisticated algorithm are possible limitations impeding worldwide market expansion.
The increased use of smartphones has directly led to a tremendous rise in the volume of data generated. This figure is expected to rise further as high-speed internet services become more available and inexpensive in both urban and rural locations. Globalization, economic progress, and the availability of low-cost, easy-to-use smartphones are all factors promoting increased data output in countries.
The generation of data by corporate enterprises is likely to witness an exponential increase, owing to the ease of data capture. Companies these days have in-house teams of scientists and analysts that record and analyze both internal and external data obtained through surveys and other data gathering methods.
Venture finance businesses have also been extremely supportive of big data projects throughout the world. Another element driving the rise of business data is the digitization of transactions.
The increasing efficiency of data processing technology and solutions is a fundamental driver of predictive business analytics growth. Because of the rapid development of artificial intelligence and deep-learning algorithms, activities that formerly required extensive knowledge and expertise may now be accomplished with ease.
Analytical software is already widely available, ranging from simple statistical tools in spreadsheets to statistical software suites. As data volumes and analytical complexity grow at an exponential rate, in-database analytics solutions are becoming increasingly prevalent.
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The rising need to store, process, and analyze massive amounts of structured and unstructured data has pushed many businesses and individuals to adopt advanced and big data analytics, which is projected to drive market growth.
Many firms, like Alphabet and Meta, leverage big data to generate advertisement income by serving customized adverts to social media and web users. Furthermore, as a consequence of the vast amount of data created in numerous company verticals, big data investment will increase, supporting the growth of the predictive analytics market.
Because of the growth of the Internet of Things (IoT) trend, multimedia, which has produced a massive flow of data, the amount of data obtained by organizations is constantly increasing.
North America is the most lucrative region with a double-digit projected growth and predictive analytics market share of approximately 47%. Because of the region's strong investment in big data analytics and early deployment of current technologies such as IoT and AI in predictive analytics.
The need to study client behavior and purchase patterns, estimate budget requirements, and develop efficient marketing campaigns by examining historical trends are the primary driving drivers in the North American predictive analytics industry. Increased digitization will boost the adoption of Predictive Analytics software and services in North America over the projected period.
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The market in the US is expected to account for the largest revenue of US$ 19.3 Bn by 2032. This is due to the growing technology improvements as well as the strong foothold of key firms such as Microsoft and Oracle across the United States.
For instance, the Orlando Magic of the NBA uses SAS predictive analytics to increase revenue and establish starting line-ups. The Orlando Magic organization's business users get fast access to information. The Magic can now visually examine the most recent statistics, down to the game and seat level. Furthermore, increased awareness of the value of predictive analytics solutions in corporate operations is likely to boost market expansion in this area.
Revenue through BFSI segment is forecasted to grow at the highest CAGR of over 15.7% during 2022-2032. The variables that may be associated with higher adoption of advanced financial analytics solutions by large BFSI organizations because of enhanced regulatory compliance processes.
As the global regulatory environment has become more complex, demand for predictive analytics solutions in the BFSI business has increased. As a result of regulatory requirements, credit risk management, capital planning, and insurance risk management, among other things, are becoming increasingly important.
Using predictive analytics solutions allows BFSI organizations to embark on a digital transformation journey. It improves the customer experience and helps businesses deal with changing customer behavior.
From the perspective of a financial institution, when a loan is made, there is always a high level of risk involved. As a result, a bank's ability to accurately predict the risk of default is critical. Predictive analytics models are being used by banks to enhance loan approval and collection procedures. This enables companies to assess applicants' repayment ability, analyze patterns in earlier loans, and do other things.
With digital payment systems, wallets, cryptocurrencies, mobile banking, and other possibilities, the frequency of financial scams and counterfeit transactions has increased along with customer delight and ease of banking. To be more specific, between 2020 and 2021, India recorded 229 financial frauds (worth up to US$ 18 Bn). The more concerning fact is that less than 1% of the total has only been retrieved.
The Solutions segment is forecasted to grow at the highest CAGR of over 15.4% during 2022-2032. The factors that can be linked to the widespread usage of numerous risk analytics systems for forecasting future dangers and devising risk mitigation strategies.
Since they focus on risk management and what-if scenarios, predictive analytics solutions are a reliable form of forecasting. Furthermore, it allows businesses to adapt to industry trends and grow on the run.
In business, predictive analytics solutions assess previous and current data to better understand items, customers, and partners, as well as identify potential opportunities and risks. As a result, purchasing patterns are analyzed and relevant insights are supplied, supporting businesses in adding more value to their offerings and assuring a better buying experience for customers.
Among the leading players in the global Predictive Analytics market are Microsoft, IBM, SAP, Oracle, SAS Institute. To gain a competitive advantage in the industry, these market players are investing in product launches, partnerships, mergers and acquisitions, and expansions.
Due to the growing demand for the product around the world, many new companies are expected to enter the market. This is expected to increase competition on a worldwide scale. Additionally, global predictive analytics market growth is expected to be fuelled by collaborations among current players to improve quality throughout the research period.
Over the projection period, established market players are expected to diversify their portfolios and offer one-stop solutions to combat fierce competition.
Similarly, recent developments related to companies in Predictive Analytics services have been tracked by the team at Future Market Insights, which are available in the full report.
| Attributes | Details |
|---|---|
| Forecast Period | 2022 to 2032 |
| Historical Data Available for | 2015 to 2021 |
| Market Analysis | US$ Million for Value |
| Key Regions Covered | North America, Europe, Asia Pacific, Middle East & Africa, Latin America |
| Key Countries Covered | United States, Canada, Brazil, Mexico, Germany, France, UK, Spain, Italy, China, South Korea, Japan, Saudi Arabia, South Africa |
| Key Market Segments Covered | Component, Deployment Mode, Organization Size, Vertical, Region |
| Key Companies Profiled |
|
| Pricing | Available upon Request |
The global Predictive Analytics Market is worth more than US$ 10.5 Bn at present.
Value of Predictive Analytics Market are projected to increase at a CAGR of around 15.8% during 2022 – 2032.
Value of Predictive Analytics Market increased at a CAGR of around 27.9% during 2015 – 2021.
The rise in artificial intelligence, data analytics, data fabrication, big data, data democratization, edge computing, etc. are driving the growth of the Predictive Analytics Market.
The market for Predictive Analytics Market in US is projected to expand at a CAGR of around 15.7% during 2022 – 2032.
1. Executive Summary
1.1. Global Market Outlook
1.2. Summary of Statistics
1.3. Key Market Characteristics & Attributes
1.4. Analysis and Recommendations
2. Market Overview
2.1. Market Coverage
2.2. Market Definition
3. Market Risks and Trends Assessment
3.1. Risk Assessment
3.1.1. COVID-19 Crisis and Impact on Demand
3.1.2. COVID-19 Impact Benchmark with Previous Crisis
3.1.3. Impact on Market Value (US$ Mn)
3.1.4. Assessment by Key Countries
3.1.5. Assessment by Key Market Segments
3.1.6. Action Points and Recommendation for Suppliers
3.2. Key Trends Impacting the Market
3.3. Formulation and Product Development Trends
4. Market Background
4.1. Market, by Key Countries
4.2. Market Opportunity Assessment (US$ Mn)
4.2.1. Total Available Market
4.2.2. Serviceable Addressable Market
4.2.3. Serviceable Obtainable Market
4.3. Market Scenario Forecast
4.3.1. Demand in optimistic Scenario
4.3.2. Demand in Likely Scenario
4.3.3. Demand in Conservative Scenario
4.4. Investment Feasibility Analysis
4.4.1. Investment in Established Markets
4.4.1.1. In Short Term
4.4.1.2. In Long Term
4.4.2. Investment in Emerging Markets
4.4.2.1. In Short Term
4.4.2.2. In Long Term
4.5. Forecast Factors - Relevance & Impact
4.5.1. Top Companies Historical Growth
4.5.2. Growth in Automation, By Country
4.5.3. Adoption Rate, By Country
4.6. Market Dynamics
4.6.1. Market Driving Factors and Impact Assessment
4.6.2. Prominent Market Challenges and Impact Assessment
4.6.3. Market Opportunities
4.6.4. Prominent Trends in the Global Market & Their Impact Assessment
5. Key Success Factors
5.1. Manufacturers’ Focus on Low Penetration High Growth Markets
5.2. Banking on with Segments High Incremental Opportunity
5.3. Peer Benchmarking
6. Global Market Demand Analysis 2015-2021 and Forecast, 2022-2032
6.1. Historical Market Analysis, 2015-2021
6.2. Current and Future Market Projections, 2022-2032
6.3. Y-o-Y Growth Trend Analysis
7. Global Market Value Analysis 2015-2021 and Forecast, 2022-2032
7.1. Historical Market Value (US$ Mn) Analysis, 2015-2021
7.2. Current and Future Market Value (US$ Mn) Projections, 2022-2032
7.2.1. Y-o-Y Growth Trend Analysis
7.2.2. Absolute $ Opportunity Analysis
8. Global Market Analysis 2015-2021 and Forecast 2022-2032, By Component
8.1. Introduction / Key Findings
8.2. Historical Market Size (US$ Mn) Analysis By Component, 2015-2021
8.3. Current and Future Market Size (US$ Mn) Analysis and Forecast By Component, 2022-2032
8.3.1. Solutions
8.3.1.1. Financial Analytics
8.3.1.2. Risk Analytics
8.3.1.3. Marketing Analytics
8.3.1.4. Sales Analytics
8.3.1.5. Customer Analytics
8.3.1.6. Web and Social Media Analytics
8.3.1.7. Supply Chain Analytics
8.3.1.8. Network Analytics
8.3.2. Services
8.3.2.1. Professional Services
8.3.2.1.1. Consulting
8.3.2.1.2. Deployment and Integration
8.3.2.1.3. Support and Maintenance
8.3.2.2. Support and Maintenance
8.4. Market Attractiveness Analysis By Component
9. Global Market Analysis 2015-2021 and Forecast 2022-2032, By Vertical
9.1. Introduction / Key Findings
9.2. Historical Market Size (US$ Mn) Analysis By Vertical, 2015-2021
9.3. Current and Future Market Size (US$ Mn) Analysis and Forecast By Vertical, 2022-2032
9.3.1. BFSI
9.3.2. Manufacturing
9.3.3. Retail and eCommerce
9.3.4. Government and Defense
9.3.5. Healthcare and Life Sciences
9.3.6. Energy and Utilities
9.3.7. Telecommunications and IT
9.3.8. Transportation and Logistics
9.3.9. Media and Entertainment
9.3.10. Travel and Hospitality
9.3.11. Others
9.4. Market Attractiveness Analysis By Vertical
10. Global Market Analysis 2015-2021 and Forecast 2022-2032, By Deployment Mode
10.1. Introduction / Key Findings
10.2. Historical Market Size (US$ Mn) Analysis By Deployment Mode, 2015-2021
10.3. Current and Future Market Size (US$ Mn) Analysis and Forecast By Deployment Mode, 2022-2032
10.3.1. Cloud
10.3.2. On-premises
10.4. Market Attractiveness Analysis By Deployment Mode
11. Global Market Analysis 2015-2021 and Forecast 2022-2032, By Organization Size
11.1. Introduction / Key Findings
11.2. Historical Market Size (US$ Mn) Analysis By Organization Size, 2015-2021
11.3. Current and Future Market Size (US$ Mn) Analysis and Forecast By Organization Size, 2022-2032
11.3.1. Large Enterprises
11.3.2. Small and Medium-sized Enterprises (SMEs)
11.4. Market Attractiveness Analysis By Organization Size
12. Global Market Analysis 2015-2021 and Forecast 2022-2032, By Region
12.1. Introduction
12.2. Historical Market Size (US$ Mn) Analysis By Region, 2015-2021
12.3. Current Market Size (US$ Mn) & Analysis and Forecast By Region, 2022-2032
12.3.1. North America
12.3.2. Latin America
12.3.3. Europe
12.3.4. Asia Pacific
12.3.5. Middle East and Africa (MEA)
12.4. Market Attractiveness Analysis By Region
13. North America Market Analysis 2015-2021 and Forecast 2022-2032
13.1. Introduction
13.2. Pricing Analysis
13.3. Historical Market Value (US$ Mn) Trend Analysis By Market Taxonomy, 2015-2021
13.4. Market Value (US$ Mn) & Forecast By Market Taxonomy, 2022-2032
13.4.1. By Country
13.4.1.1. U.S.
13.4.1.2. Canada
13.4.1.3. Rest of North America
13.4.2. By Component
13.4.3. By Vertical
13.4.4. By Organization Size
13.4.5. By Deployment Mode
13.5. Market Attractiveness Analysis
13.5.1. By Country
13.5.2. By Component
13.5.3. By Vertical
13.5.4. By Organization Size
13.5.5. By Deployment Mode
14. Latin America Market Analysis 2015-2021 and Forecast 2022-2032
14.1. Introduction
14.2. Pricing Analysis
14.3. Historical Market Value (US$ Mn) Trend Analysis By Market Taxonomy, 2015-2021
14.4. Market Value (US$ Mn) & Forecast By Market Taxonomy, 2022-2032
14.4.1. By Country
14.4.1.1. Brazil
14.4.1.2. Mexico
14.4.1.3. Rest of Latin America
14.4.2. By Component
14.4.3. By Vertical
14.4.4. By Organization Size
14.4.5. By Deployment Mode
14.5. Market Attractiveness Analysis
14.5.1. By Country
14.5.2. By Component
14.5.3. By Vertical
14.5.4. By Organization Size
14.5.5. By Deployment Mode
15. Europe Market Analysis 2015-2021 and Forecast 2022-2032
15.1. Introduction
15.2. Pricing Analysis
15.3. Historical Market Value (US$ Mn) Trend Analysis By Market Taxonomy, 2015-2021
15.4. Market Value (US$ Mn) & Forecast By Market Taxonomy, 2022-2032
15.4.1. By Country
15.4.1.1. Germany
15.4.1.2. France
15.4.1.3. U.K.
15.4.1.4. Italy
15.4.1.5. Benelux
15.4.1.6. Nordic Countries
15.4.1.7. Rest of Europe
15.4.2. By Component
15.4.3. By Vertical
15.4.4. By Organization Size
15.4.5. By Deployment Mode
15.5. Market Attractiveness Analysis
15.5.1. By Country
15.5.2. By Component
15.5.3. By Vertical
15.5.4. By Organization Size
15.5.5. By Deployment Mode
16. Asia Pacific Market Analysis 2015-2021 and Forecast 2022-2032
16.1. Introduction
16.2. Pricing Analysis
16.3. Historical Market Value (US$ Mn) Trend Analysis By Market Taxonomy, 2015-2021
16.4. Market Value (US$ Mn) & Forecast By Market Taxonomy, 2022-2032
16.4.1. By Country
16.4.1.1. China
16.4.1.2. Japan
16.4.1.3. South Korea
16.4.1.4. Rest of Asia Pacific
16.4.2. By Component
16.4.3. By Vertical
16.4.4. By Organization Size
16.4.5. By Deployment Mode
16.5. Market Attractiveness Analysis
16.5.1. By Country
16.5.2. By Component
16.5.3. By Vertical
16.5.4. By Organization Size
16.5.5. By Deployment Mode
17. Middle East and Africa Market Analysis 2015-2021 and Forecast 2022-2032
17.1. Introduction
17.2. Pricing Analysis
17.3. Historical Market Value (US$ Mn) Trend Analysis By Market Taxonomy, 2015-2021
17.4. Market Value (US$ Mn) & Forecast By Market Taxonomy, 2022-2032
17.4.1. By Country
17.4.1.1. GCC Countries
17.4.1.2. South Africa
17.4.1.3. Turkey
17.4.1.4. Rest of Middle East and Africa
17.4.2. By Component
17.4.3. By Vertical
17.4.4. By Organization Size
17.4.5. By Deployment Mode
17.5. Market Attractiveness Analysis
17.5.1. By Country
17.5.2. By Component
17.5.3. By Vertical
17.5.4. By Organization Size
17.5.5. By Deployment Mode
18. Key Countries Market Analysis 2015-2021 and Forecast 2022-2032
18.1. Introduction
18.1.1. Market Value Proportion Analysis, By Key Countries
18.1.2. Global Vs. Country Growth Comparison
18.2. US Market Analysis
18.2.1. Value Proportion Analysis by Market Taxonomy
18.2.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.2.2.1. By Component
18.2.2.2. By Vertical
18.2.2.3. By Organization Size
18.2.2.4. By Deployment Mode
18.3. Canada Market Analysis
18.3.1. Value Proportion Analysis by Market Taxonomy
18.3.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.3.2.1. By Component
18.3.2.2. By Vertical
18.3.2.3. By Organization Size
18.3.2.4. By Deployment Mode
18.4. Mexico Market Analysis
18.4.1. Value Proportion Analysis by Market Taxonomy
18.4.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.4.2.1. By Component
18.4.2.2. By Vertical
18.4.2.3. By Organization Size
18.4.2.4. By Deployment Mode
18.5. Brazil Market Analysis
18.5.1. Value Proportion Analysis by Market Taxonomy
18.5.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.5.2.1. By Component
18.5.2.2. By Vertical
18.5.2.3. By Organization Size
18.5.2.4. By Deployment Mode
18.6. Germany Market Analysis
18.6.1. Value Proportion Analysis by Market Taxonomy
18.6.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.6.2.1. By Component
18.6.2.2. By Vertical
18.6.2.3. By Organization Size
18.6.2.4. By Deployment Mode
18.7. France Market Analysis
18.7.1. Value Proportion Analysis by Market Taxonomy
18.7.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.7.2.1. By Component
18.7.2.2. By Vertical
18.7.2.3. By Organization Size
18.7.2.4. By Deployment Mode
18.8. Italy Market Analysis
18.8.1. Value Proportion Analysis by Market Taxonomy
18.8.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.8.2.1. By Component
18.8.2.2. By Vertical
18.8.2.3. By Organization Size
18.8.2.4. By Deployment Mode
18.9. BENELUX Market Analysis
18.9.1. Value Proportion Analysis by Market Taxonomy
18.9.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.9.2.1. By Component
18.9.2.2. By Vertical
18.9.2.3. By Organization Size
18.9.2.4. By Deployment Mode
18.10. UK Market Analysis
18.10.1. Value Proportion Analysis by Market Taxonomy
18.10.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.10.2.1. By Component
18.10.2.2. By Vertical
18.10.2.3. By Organization Size
18.10.2.4. By Deployment Mode
18.11. Nordic Countries Market Analysis
18.11.1. Value Proportion Analysis by Market Taxonomy
18.11.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.11.2.1. By Component
18.11.2.2. By Vertical
18.11.2.3. By Organization Size
18.11.2.4. By Deployment Mode
18.12. China Market Analysis
18.12.1. Value Proportion Analysis by Market Taxonomy
18.12.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.12.2.1. By Component
18.12.2.2. By Vertical
18.12.2.3. By Organization Size
18.12.2.4. By Deployment Mode
18.13. Japan Market Analysis
18.13.1. Value Proportion Analysis by Market Taxonomy
18.13.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.13.2.1. By Component
18.13.2.2. By Vertical
18.13.2.3. By Organization Size
18.13.2.4. By Deployment Mode
18.14. South Korea Market Analysis
18.14.1. Value Proportion Analysis by Market Taxonomy
18.14.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.14.2.1. By Component
18.14.2.2. By Vertical
18.14.2.3. By Organization Size
18.14.2.4. By Deployment Mode
18.15. GCC Countries Market Analysis
18.15.1. Value Proportion Analysis by Market Taxonomy
18.15.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.15.2.1. By Component
18.15.2.2. By Vertical
18.15.2.3. By Organization Size
18.15.2.4. By Deployment Mode
18.16. South Africa Market Analysis
18.16.1. Value Proportion Analysis by Market Taxonomy
18.16.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.16.2.1. By Component
18.16.2.2. By Vertical
18.16.2.3. By Organization Size
18.16.2.4. By Deployment Mode
18.17. Turkey Market Analysis
18.17.1. Value Proportion Analysis by Market Taxonomy
18.17.2. Value Analysis and Forecast by Market Taxonomy, 2015-2032
18.17.2.1. By Component
18.17.2.2. By Vertical
18.17.2.3. By Organization Size
18.17.2.4. By Deployment Mode
18.17.3. Competition Landscape and Player Concentration in the Country
19. Market Structure Analysis
19.1. Market Analysis by Tier of Companies
19.2. Market Concentration
19.3. Market Share Analysis of Top Players
19.4. Market Presence Analysis
19.4.1. By Regional footprint of Players
19.4.2. Product footprint by Players
20. Competition Analysis
20.1. Competition Dashboard
20.2. Competition Benchmarking
20.3. Competition Deep Dive
20.3.1. Microsoft
20.3.1.1. Overview
20.3.1.2. Product Portfolio
20.3.1.3. Sales Footprint
20.3.1.4. Strategy Overview
20.3.2. IBM
20.3.2.1. Overview
20.3.2.2. Product Portfolio
20.3.2.3. Sales Footprint
20.3.2.4. Strategy Overview
20.3.3. SAP
20.3.3.1. Overview
20.3.3.2. Product Portfolio
20.3.3.3. Sales Footprint
20.3.3.4. Strategy Overview
20.3.4. Oracle
20.3.4.1. Overview
20.3.4.2. Product Portfolio
20.3.4.3. Sales Footprint
20.3.4.4. Strategy Overview
20.3.5. SAS Institute
20.3.5.1. Overview
20.3.5.2. Product Portfolio
20.3.5.3. Sales Footprint
20.3.5.4. Strategy Overview
20.3.6. Google
20.3.6.1. Overview
20.3.6.2. Product Portfolio
20.3.6.3. Sales Footprint
20.3.6.4. Strategy Overview
20.3.7. Salesforce
20.3.7.1. Overview
20.3.7.2. Product Portfolio
20.3.7.3. Sales Footprint
20.3.7.4. Strategy Overview
20.3.8. AWS
20.3.8.1. Overview
20.3.8.2. Product Portfolio
20.3.8.3. Sales Footprint
20.3.8.4. Strategy Overview
20.3.9. HPE
20.3.9.1. Overview
20.3.9.2. Product Portfolio
20.3.9.3. Sales Footprint
20.3.9.4. Strategy Overview
20.3.10. Teradata
20.3.10.1. Overview
20.3.10.2. Product Portfolio
20.3.10.3. Sales Footprint
20.3.10.4. Strategy Overview
21. Assumptions and Acronyms Used
22. Research Methodology
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