Big Data & Analytics Market by Component (Services, Software), Analytics Type (Descriptive, Diagnostic, Predictive), Data Type, Deployment Model, Application, Enterprise Size, Industry Vertical - Global Forecast 2025-2032
Description
The Big Data & Analytics Market was valued at USD 110.12 billion in 2024 and is projected to grow to USD 121.44 billion in 2025, with a CAGR of 10.35%, reaching USD 242.26 billion by 2032.
Setting the Stage for a Data-Driven Revolution Emphasizing the Pivotal Role of Big Data and Analytics in Modern Enterprise Decision Making
In a business environment driven by rapid technological advancements and ever-increasing data volumes, organizations are compelled to embrace big data and advanced analytics as central pillars of their strategic vision. This introduction establishes the crucial context for understanding how data-driven decision making has evolved from a competitive differentiator to a fundamental operational requirement. Through careful examination of emerging use cases, it becomes evident that enterprises leveraging sophisticated analytics capabilities are witnessing improved customer experiences, optimized supply chain efficiencies, and more resilient risk management practices.
This executive summary will guide readers through the key thematic areas shaping the market landscape, from transformative technology shifts and tariff implications to granular segmentation and regional dynamics. By weaving together insights on industry best practices and real-world applications, this section sets the stage for deeper exploration into the factors that will influence organizational success in the coming years. Ultimately, it underscores the importance of agile adaptation and strategic investment in analytics as a driver of sustained growth and competitive advantage.
Uncovering Transformational Forces Shaping the Big Data and Analytics Landscape as Emerging Technologies Redefine Business Capabilities
The landscape of big data and analytics is being reshaped by a constellation of transformative forces that are redefining how organizations collect, process, and act on information. Artificial intelligence and machine learning models are now capable of uncovering insights at unprecedented speed, powering real-time decision systems that were previously unattainable. At the same time, edge computing architectures are decentralizing analytics capabilities, enabling data processing closer to the source and reducing latency for mission-critical applications in manufacturing, retail, and telecommunications.
Another paradigm shift is the democratization of analytics through self-service platforms that empower business users to generate insights without extensive technical support. Coupled with advances in data privacy and governance frameworks, these innovations are fostering a culture of confidence around data usage. Moreover, the convergence of cloud-native architectures with containerization is simplifying deployment and scalability, ensuring that analytics solutions can evolve seamlessly alongside fluctuating demand. These developments collectively signal a new era in which agility and adaptability are paramount.
Assessing the Far-Reaching Impacts of 2025 United States Tariffs on the Big Data and Analytics Ecosystem across Supply Chain and Investment Strategies
The introduction of new United States tariffs slated for 2025 is poised to exert a substantial influence on the global big data and analytics ecosystem. Hardware components essential for high-performance computing clusters, as well as specialized devices for accelerated inference, may face increased import costs. Vendors are already exploring alternative manufacturing locations and negotiating localized production agreements to mitigate potential disruptions. These strategic adjustments underscore the importance of resilient supply chains in maintaining uninterrupted service delivery.
Software vendors, meanwhile, are evaluating licensing and subscription models to absorb cost fluctuations, while end users are reassessing total cost of ownership for on-premises deployments. Some organizations may accelerate migration to cloud-based platforms to avoid tariff-related overhead, yet this move must be balanced against data sovereignty and security considerations. In response to these pressures, collaborative partnerships between providers and clients are becoming more common, emphasizing co-innovation efforts and flexible contractual terms designed to shield both parties from volatility in trade policies.
Deep Diving into Segmentation Insights Highlighting Component, Analytics Type, Data Type, Deployment Model, Application, Enterprise Size, and Industry Vertical
A nuanced understanding of market segmentation reveals where value creation and competitive differentiation are most pronounced. When dissecting the market by component, the interplay between services and software emerges as a critical dynamic: managed services deliver operational support and infrastructure management, whereas professional services focus on consulting, system integration, and custom solution development. These service categories complement software offerings that range from data ingestion and preparation tools to advanced analytics engines and visualization platforms.
Delving deeper, analytics types span from descriptive reporting through diagnostic analysis, predictive modeling, and prescriptive recommendations, each addressing different stages in the decision lifecycle. Data taxonomy also plays a central role, encompassing semi-structured formats like JSON and XML, traditional relational datasets, and unstructured sources such as text logs and multimedia content. Deployment models oscillate between cloud solutions for scalability and on-premises implementations for strict security requirements. Equally important are application domains-customer analytics, fraud detection, operational monitoring, and risk assessment-serviced by organizations of varying scale, from multinational enterprises to agile small and medium businesses. Ultimately, vertical specialization in sectors like banking, healthcare, manufacturing, retail, and telecommunications brings tailored approaches that reflect unique data characteristics and regulatory mandates.
Examining Regional Dynamics Revealing How the Americas, Europe Middle East & Africa, and Asia-Pacific Regions Drive Unique Big Data and Analytics Trends
The competitive intensity and adoption rates of big data and analytics solutions vary markedly across regions, driven by economic maturity, regulatory environments, and technological infrastructures. In the Americas, a strong emphasis on cloud migration and digital transformation initiatives continues to fuel demand for sophisticated analytics platforms. Leading corporations are spearheading large-scale AI projects, bolstered by robust venture funding and supportive policy frameworks that prioritize data innovation.
Across Europe, the Middle East, and Africa, diversity in maturity levels gives rise to differentiated adoption patterns. Western European markets are characterized by stringent data privacy regulations and high enterprise spending on advanced analytics, while emerging economies in the region are investing selectively in foundational capabilities. In the Asia-Pacific region, rapid digitalization in markets such as India and Southeast Asia is complemented by expansive state-led initiatives in smart cities and Industry 4.0. Together, these regional dynamics form a complex mosaic where organizational strategies must be adapted to local nuances in infrastructure, talent availability, and governance.
Highlighting Key Industry Players Providing Critical Innovations and Strategic Partnerships That Shape the Competitive Big Data and Analytics Ecosystem
Leading providers in the big data and analytics arena continue to differentiate through integrated platform capabilities, strategic alliances, and targeted acquisitions. Global software vendors are enhancing their core offerings with embedded AI functionalities and seamless interoperability across hybrid environments. These developments are often accelerated through partnerships with niche specialists that bring domain-specific expertise in areas like natural language processing and graph analytics.
Meanwhile, cloud hyperscalers are expanding their managed services portfolios, offering turnkey solutions for data warehousing, machine learning pipelines, and real-time event streaming. Open source initiatives also play a pivotal role, fostering community-driven innovation and reducing entry barriers for new market entrants. Collaborative ecosystems, including academic and government partnerships, are further driving research breakthroughs and supporting commercialization of cutting-edge algorithms. As a result, organizations now have unprecedented access to a spectrum of solutions that can be customized to their strategic objectives and technology roadmaps.
Actionable Strategies for Industry Leaders to Capitalize on Emerging Data Opportunities and Navigate Regulatory and Technological Complexities
For industry leaders seeking to leverage data as a strategic asset, several actionable priorities have emerged. First, establishing a robust data governance framework ensures consistency, quality, and compliance, while accelerating the time to insight. Investing in talent development is equally imperative; organizations should cultivate cross-disciplinary teams that blend domain expertise, advanced analytics skills, and change management capabilities.
Second, embracing modular architectures and open integration standards allows for greater flexibility and cost efficiency. This includes leveraging microservices, APIs, and containerization to streamline deployment and scale resources dynamically. Third, leaders should form strategic alliances with technology providers, academic institutions, and industry consortia to co-develop innovative solutions and mitigate investment risk. Finally, adopting a continuous improvement mindset-anchored by performance metrics and feedback loops-enables organizations to refine use cases, optimize workflows, and sustain competitive advantage in an environment of constant disruption.
Elucidating the Rigorous Research Methodology Incorporating Comprehensive Secondary Data Review and Targeted Primary Validation to Ensure Analytical Integrity
This analysis is underpinned by a comprehensive research methodology designed to ensure analytical rigor and objectivity. The secondary research phase encompassed a thorough review of industry publications, technical journals, conference proceedings, and policy documents to establish a foundational understanding of market trends and technological developments. Complementing this, proprietary data repositories and white papers were examined to validate key themes and benchmark best practices.
The primary research phase involved in-depth interviews with C-suite executives, data scientists, and technology providers, as well as structured surveys targeting end-user organizations across diverse sectors. These interactions were carefully orchestrated to capture both strategic perspectives and operational realities. Data triangulation processes were implemented to reconcile insights, and quality control measures ensured the accuracy and consistency of findings. Together, these methods provide a robust framework for delivering reliable, actionable intelligence to executive decision makers.
Drawing Conclusive Perspectives on the Convergence of Market Dynamics, Technological Advancements, and Strategic Imperatives in Big Data and Analytics
In conclusion, the big data and analytics market is entering a phase defined by accelerated innovation, regulatory complexity, and heightened competition. Organizations that align their investment strategies with emerging technology paradigms-such as AI-driven automation and edge analytics-will be well positioned to extract maximum value from their data assets. Simultaneously, proactive risk mitigation measures, including supply chain diversification and stringent governance protocols, will safeguard continuity and trust.
Looking ahead, continued collaboration across public and private sectors, coupled with targeted skills development, will unlock new use cases and drive deeper integration of analytics into core business processes. Ultimately, the ability to translate data insights into strategic actions will differentiate industry leaders and shape the competitive landscape for years to come.
Market Segmentation & Coverage
This research report categorizes to forecast the revenues and analyze trends in each of the following sub-segmentations:
Component
Services
Managed Services
Professional Services
Software
Analytics Type
Descriptive
Diagnostic
Predictive
Prescriptive
Data Type
Semi-Structured
Structured
Unstructured
Deployment Model
Cloud
On-Premises
Application
Customer Analytics
Fraud Analytics
Operational Analytics
Risk Analytics
Enterprise Size
Large Enterprises
Small & Medium Enterprises
Industry Vertical
Banking Financial Services & Insurance
Healthcare
Manufacturing
Retail
Telecommunications
This research report categorizes to forecast the revenues and analyze trends in each of the following sub-regions:
Americas
North America
United States
Canada
Mexico
Latin America
Brazil
Argentina
Chile
Colombia
Peru
Europe, Middle East & Africa
Europe
United Kingdom
Germany
France
Russia
Italy
Spain
Netherlands
Sweden
Poland
Switzerland
Middle East
United Arab Emirates
Saudi Arabia
Qatar
Turkey
Israel
Africa
South Africa
Nigeria
Egypt
Kenya
Asia-Pacific
China
India
Japan
Australia
South Korea
Indonesia
Thailand
Malaysia
Singapore
Taiwan
This research report categorizes to delves into recent significant developments and analyze trends in each of the following companies:
Microsoft Corporation
International Business Machines Corporation
Oracle Corporation
SAP SE
Amazon Web Services, Inc.
Alphabet Inc.
SAS Institute Inc.
Salesforce, Inc.
Teradata Corporation
Dell Technologies Inc.
Please Note: PDF & Excel + Online Access - 1 Year
Setting the Stage for a Data-Driven Revolution Emphasizing the Pivotal Role of Big Data and Analytics in Modern Enterprise Decision Making
In a business environment driven by rapid technological advancements and ever-increasing data volumes, organizations are compelled to embrace big data and advanced analytics as central pillars of their strategic vision. This introduction establishes the crucial context for understanding how data-driven decision making has evolved from a competitive differentiator to a fundamental operational requirement. Through careful examination of emerging use cases, it becomes evident that enterprises leveraging sophisticated analytics capabilities are witnessing improved customer experiences, optimized supply chain efficiencies, and more resilient risk management practices.
This executive summary will guide readers through the key thematic areas shaping the market landscape, from transformative technology shifts and tariff implications to granular segmentation and regional dynamics. By weaving together insights on industry best practices and real-world applications, this section sets the stage for deeper exploration into the factors that will influence organizational success in the coming years. Ultimately, it underscores the importance of agile adaptation and strategic investment in analytics as a driver of sustained growth and competitive advantage.
Uncovering Transformational Forces Shaping the Big Data and Analytics Landscape as Emerging Technologies Redefine Business Capabilities
The landscape of big data and analytics is being reshaped by a constellation of transformative forces that are redefining how organizations collect, process, and act on information. Artificial intelligence and machine learning models are now capable of uncovering insights at unprecedented speed, powering real-time decision systems that were previously unattainable. At the same time, edge computing architectures are decentralizing analytics capabilities, enabling data processing closer to the source and reducing latency for mission-critical applications in manufacturing, retail, and telecommunications.
Another paradigm shift is the democratization of analytics through self-service platforms that empower business users to generate insights without extensive technical support. Coupled with advances in data privacy and governance frameworks, these innovations are fostering a culture of confidence around data usage. Moreover, the convergence of cloud-native architectures with containerization is simplifying deployment and scalability, ensuring that analytics solutions can evolve seamlessly alongside fluctuating demand. These developments collectively signal a new era in which agility and adaptability are paramount.
Assessing the Far-Reaching Impacts of 2025 United States Tariffs on the Big Data and Analytics Ecosystem across Supply Chain and Investment Strategies
The introduction of new United States tariffs slated for 2025 is poised to exert a substantial influence on the global big data and analytics ecosystem. Hardware components essential for high-performance computing clusters, as well as specialized devices for accelerated inference, may face increased import costs. Vendors are already exploring alternative manufacturing locations and negotiating localized production agreements to mitigate potential disruptions. These strategic adjustments underscore the importance of resilient supply chains in maintaining uninterrupted service delivery.
Software vendors, meanwhile, are evaluating licensing and subscription models to absorb cost fluctuations, while end users are reassessing total cost of ownership for on-premises deployments. Some organizations may accelerate migration to cloud-based platforms to avoid tariff-related overhead, yet this move must be balanced against data sovereignty and security considerations. In response to these pressures, collaborative partnerships between providers and clients are becoming more common, emphasizing co-innovation efforts and flexible contractual terms designed to shield both parties from volatility in trade policies.
Deep Diving into Segmentation Insights Highlighting Component, Analytics Type, Data Type, Deployment Model, Application, Enterprise Size, and Industry Vertical
A nuanced understanding of market segmentation reveals where value creation and competitive differentiation are most pronounced. When dissecting the market by component, the interplay between services and software emerges as a critical dynamic: managed services deliver operational support and infrastructure management, whereas professional services focus on consulting, system integration, and custom solution development. These service categories complement software offerings that range from data ingestion and preparation tools to advanced analytics engines and visualization platforms.
Delving deeper, analytics types span from descriptive reporting through diagnostic analysis, predictive modeling, and prescriptive recommendations, each addressing different stages in the decision lifecycle. Data taxonomy also plays a central role, encompassing semi-structured formats like JSON and XML, traditional relational datasets, and unstructured sources such as text logs and multimedia content. Deployment models oscillate between cloud solutions for scalability and on-premises implementations for strict security requirements. Equally important are application domains-customer analytics, fraud detection, operational monitoring, and risk assessment-serviced by organizations of varying scale, from multinational enterprises to agile small and medium businesses. Ultimately, vertical specialization in sectors like banking, healthcare, manufacturing, retail, and telecommunications brings tailored approaches that reflect unique data characteristics and regulatory mandates.
Examining Regional Dynamics Revealing How the Americas, Europe Middle East & Africa, and Asia-Pacific Regions Drive Unique Big Data and Analytics Trends
The competitive intensity and adoption rates of big data and analytics solutions vary markedly across regions, driven by economic maturity, regulatory environments, and technological infrastructures. In the Americas, a strong emphasis on cloud migration and digital transformation initiatives continues to fuel demand for sophisticated analytics platforms. Leading corporations are spearheading large-scale AI projects, bolstered by robust venture funding and supportive policy frameworks that prioritize data innovation.
Across Europe, the Middle East, and Africa, diversity in maturity levels gives rise to differentiated adoption patterns. Western European markets are characterized by stringent data privacy regulations and high enterprise spending on advanced analytics, while emerging economies in the region are investing selectively in foundational capabilities. In the Asia-Pacific region, rapid digitalization in markets such as India and Southeast Asia is complemented by expansive state-led initiatives in smart cities and Industry 4.0. Together, these regional dynamics form a complex mosaic where organizational strategies must be adapted to local nuances in infrastructure, talent availability, and governance.
Highlighting Key Industry Players Providing Critical Innovations and Strategic Partnerships That Shape the Competitive Big Data and Analytics Ecosystem
Leading providers in the big data and analytics arena continue to differentiate through integrated platform capabilities, strategic alliances, and targeted acquisitions. Global software vendors are enhancing their core offerings with embedded AI functionalities and seamless interoperability across hybrid environments. These developments are often accelerated through partnerships with niche specialists that bring domain-specific expertise in areas like natural language processing and graph analytics.
Meanwhile, cloud hyperscalers are expanding their managed services portfolios, offering turnkey solutions for data warehousing, machine learning pipelines, and real-time event streaming. Open source initiatives also play a pivotal role, fostering community-driven innovation and reducing entry barriers for new market entrants. Collaborative ecosystems, including academic and government partnerships, are further driving research breakthroughs and supporting commercialization of cutting-edge algorithms. As a result, organizations now have unprecedented access to a spectrum of solutions that can be customized to their strategic objectives and technology roadmaps.
Actionable Strategies for Industry Leaders to Capitalize on Emerging Data Opportunities and Navigate Regulatory and Technological Complexities
For industry leaders seeking to leverage data as a strategic asset, several actionable priorities have emerged. First, establishing a robust data governance framework ensures consistency, quality, and compliance, while accelerating the time to insight. Investing in talent development is equally imperative; organizations should cultivate cross-disciplinary teams that blend domain expertise, advanced analytics skills, and change management capabilities.
Second, embracing modular architectures and open integration standards allows for greater flexibility and cost efficiency. This includes leveraging microservices, APIs, and containerization to streamline deployment and scale resources dynamically. Third, leaders should form strategic alliances with technology providers, academic institutions, and industry consortia to co-develop innovative solutions and mitigate investment risk. Finally, adopting a continuous improvement mindset-anchored by performance metrics and feedback loops-enables organizations to refine use cases, optimize workflows, and sustain competitive advantage in an environment of constant disruption.
Elucidating the Rigorous Research Methodology Incorporating Comprehensive Secondary Data Review and Targeted Primary Validation to Ensure Analytical Integrity
This analysis is underpinned by a comprehensive research methodology designed to ensure analytical rigor and objectivity. The secondary research phase encompassed a thorough review of industry publications, technical journals, conference proceedings, and policy documents to establish a foundational understanding of market trends and technological developments. Complementing this, proprietary data repositories and white papers were examined to validate key themes and benchmark best practices.
The primary research phase involved in-depth interviews with C-suite executives, data scientists, and technology providers, as well as structured surveys targeting end-user organizations across diverse sectors. These interactions were carefully orchestrated to capture both strategic perspectives and operational realities. Data triangulation processes were implemented to reconcile insights, and quality control measures ensured the accuracy and consistency of findings. Together, these methods provide a robust framework for delivering reliable, actionable intelligence to executive decision makers.
Drawing Conclusive Perspectives on the Convergence of Market Dynamics, Technological Advancements, and Strategic Imperatives in Big Data and Analytics
In conclusion, the big data and analytics market is entering a phase defined by accelerated innovation, regulatory complexity, and heightened competition. Organizations that align their investment strategies with emerging technology paradigms-such as AI-driven automation and edge analytics-will be well positioned to extract maximum value from their data assets. Simultaneously, proactive risk mitigation measures, including supply chain diversification and stringent governance protocols, will safeguard continuity and trust.
Looking ahead, continued collaboration across public and private sectors, coupled with targeted skills development, will unlock new use cases and drive deeper integration of analytics into core business processes. Ultimately, the ability to translate data insights into strategic actions will differentiate industry leaders and shape the competitive landscape for years to come.
Market Segmentation & Coverage
This research report categorizes to forecast the revenues and analyze trends in each of the following sub-segmentations:
Component
Services
Managed Services
Professional Services
Software
Analytics Type
Descriptive
Diagnostic
Predictive
Prescriptive
Data Type
Semi-Structured
Structured
Unstructured
Deployment Model
Cloud
On-Premises
Application
Customer Analytics
Fraud Analytics
Operational Analytics
Risk Analytics
Enterprise Size
Large Enterprises
Small & Medium Enterprises
Industry Vertical
Banking Financial Services & Insurance
Healthcare
Manufacturing
Retail
Telecommunications
This research report categorizes to forecast the revenues and analyze trends in each of the following sub-regions:
Americas
North America
United States
Canada
Mexico
Latin America
Brazil
Argentina
Chile
Colombia
Peru
Europe, Middle East & Africa
Europe
United Kingdom
Germany
France
Russia
Italy
Spain
Netherlands
Sweden
Poland
Switzerland
Middle East
United Arab Emirates
Saudi Arabia
Qatar
Turkey
Israel
Africa
South Africa
Nigeria
Egypt
Kenya
Asia-Pacific
China
India
Japan
Australia
South Korea
Indonesia
Thailand
Malaysia
Singapore
Taiwan
This research report categorizes to delves into recent significant developments and analyze trends in each of the following companies:
Microsoft Corporation
International Business Machines Corporation
Oracle Corporation
SAP SE
Amazon Web Services, Inc.
Alphabet Inc.
SAS Institute Inc.
Salesforce, Inc.
Teradata Corporation
Dell Technologies Inc.
Please Note: PDF & Excel + Online Access - 1 Year
Table of Contents
194 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency & Pricing
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Adoption of edge computing architectures to process real time data closer to source
- 5.2. Integration of artificial intelligence and machine learning for predictive analytics in marketing campaigns
- 5.3. Implementation of privacy preserving data analytics techniques to comply with evolving regulations
- 5.4. Deployment of data fabric solutions to unify disparate data silos across hybrid cloud environments
- 5.5. Growing use of low code and no code analytics platforms to democratize data access across teams
- 5.6. Emergence of graph analytics for complex relationship mapping in fraud detection and risk management
- 5.7. Increased investment in real time streaming analytics to monitor IoT and sensor data continuously
- 5.8. Rise of synthetic data generation methods to address data scarcity and privacy challenges in AI
- 5.9. Expansion of automated data pipeline orchestration with integrated quality and governance controls
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Big Data & Analytics Market, by Component
- 8.1. Services
- 8.1.1. Managed Services
- 8.1.2. Professional Services
- 8.2. Software
- 9. Big Data & Analytics Market, by Analytics Type
- 9.1. Descriptive
- 9.2. Diagnostic
- 9.3. Predictive
- 9.4. Prescriptive
- 10. Big Data & Analytics Market, by Data Type
- 10.1. Semi-Structured
- 10.2. Structured
- 10.3. Unstructured
- 11. Big Data & Analytics Market, by Deployment Model
- 11.1. Cloud
- 11.2. On-Premises
- 12. Big Data & Analytics Market, by Application
- 12.1. Customer Analytics
- 12.2. Fraud Analytics
- 12.3. Operational Analytics
- 12.4. Risk Analytics
- 13. Big Data & Analytics Market, by Enterprise Size
- 13.1. Large Enterprises
- 13.2. Small & Medium Enterprises
- 14. Big Data & Analytics Market, by Industry Vertical
- 14.1. Banking Financial Services & Insurance
- 14.2. Healthcare
- 14.3. Manufacturing
- 14.4. Retail
- 14.5. Telecommunications
- 15. Big Data & Analytics Market, by Region
- 15.1. Americas
- 15.1.1. North America
- 15.1.2. Latin America
- 15.2. Europe, Middle East & Africa
- 15.2.1. Europe
- 15.2.2. Middle East
- 15.2.3. Africa
- 15.3. Asia-Pacific
- 16. Big Data & Analytics Market, by Group
- 16.1. ASEAN
- 16.2. GCC
- 16.3. European Union
- 16.4. BRICS
- 16.5. G7
- 16.6. NATO
- 17. Big Data & Analytics Market, by Country
- 17.1. United States
- 17.2. Canada
- 17.3. Mexico
- 17.4. Brazil
- 17.5. United Kingdom
- 17.6. Germany
- 17.7. France
- 17.8. Russia
- 17.9. Italy
- 17.10. Spain
- 17.11. China
- 17.12. India
- 17.13. Japan
- 17.14. Australia
- 17.15. South Korea
- 18. Competitive Landscape
- 18.1. Market Share Analysis, 2024
- 18.2. FPNV Positioning Matrix, 2024
- 18.3. Competitive Analysis
- 18.3.1. Microsoft Corporation
- 18.3.2. International Business Machines Corporation
- 18.3.3. Oracle Corporation
- 18.3.4. SAP SE
- 18.3.5. Amazon Web Services, Inc.
- 18.3.6. Alphabet Inc.
- 18.3.7. SAS Institute Inc.
- 18.3.8. Salesforce, Inc.
- 18.3.9. Teradata Corporation
- 18.3.10. Dell Technologies Inc.
Pricing
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