Business Intelligence Market by Component (Services, Software), Function (Customer Service, Finance, Human Resources), Technology, Deployment Mode, Organization Size, Industry Vertical - Global Forecast 2025-2032
Description
The Business Intelligence Market was valued at USD 39.86 billion in 2024 and is projected to grow to USD 44.94 billion in 2025, with a CAGR of 13.96%, reaching USD 113.44 billion by 2032.
A strategic orientation for business intelligence leaders to align technology, talent, and governance toward measurable outcomes and sustained competitive advantage
The contemporary business intelligence landscape requires leaders to recalibrate strategy around data-driven decision making, operational resilience, and accelerated digital initiatives. Organizations face heightened expectations from stakeholders to convert complex data flows into timely, actionable insights that inform both tactical operations and long-term strategy. As budgets shift toward cloud architectures and analytics embedded into workflows, executives must balance technology investment with governance, talent, and process change to realize measurable outcomes.
In practice, this means aligning cross-functional priorities so that analytics initiatives are not siloed within IT or a single business unit. Successful programs integrate stakeholder input from finance, operations, sales, and customer service early in the scoping phase, and they adopt iterative delivery models that prioritize high-impact use cases. Consequently, leaders who couple disciplined data stewardship with pragmatic deployment plans create durable competitive advantage, while those who delay integration and change management risk wasted investment and slow adoption.
How emerging technologies, evolving deployment models, and governance pressures are jointly redefining where and how business intelligence delivers strategic value
Several transformative shifts are reshaping how organizations conceive and deploy business intelligence, and these shifts demand both tactical responses and strategic repositioning. First, the transition from descriptive reporting to embedded analytics and predictive capabilities is changing where value is captured, moving insights closer to decision makers in operations, customer service, and sales. Second, cloud-native architectures and hybrid deployments enable faster iteration and lower friction for scaling analytics, though they also introduce nuanced governance and integration challenges.
Moreover, the democratization of analytics tools is broadening user personas, which elevates the importance of intuitive interfaces, governed data catalogs, and training programs. Advances in location intelligence, mobile access, and social analytics are expanding the scope of insight beyond traditional business intelligence use cases, enabling contextualized decisions in field service, retail, and marketing operations. Finally, intensified focus on privacy, data protection, and ethical AI is prompting more rigorous controls and transparency throughout the analytics development lifecycle, ensuring trust and regulatory compliance.
Practical consequences of tariff adjustments on global procurement, vendor strategies, and the shift toward software-first and cloud-delivered analytics solutions
The introduction of tariffs and trade policy adjustments in 2025 has introduced tangible complexity across procurement, supply chain planning, and cost management for organizations relying on global technology and services ecosystems. Tariffs alter the landed cost of hardware and certain software bundles when bundled with proprietary appliances, prompting procurement teams to re-evaluate supplier contracts, consider alternate sourcing strategies, and accelerate conversations about software-centric architectures that reduce dependence on tariff-exposed components.
As a result, finance and procurement leaders are increasingly collaborating with IT and product teams to model scenario-based cost implications, identify opportunities for localizing certain services, and renegotiate commercial terms that allocate geopolitical risk more equitably. Simultaneously, vendors and systems integrators are responding by offering more flexible licensing, cloud-first delivery options, and managed services that abstract hardware ownership. Over time, these adaptations are shifting investment toward software, cloud consumption, and service-level guarantees that mitigate tariff volatility. In addition, organizations are strengthening inventory optimization and leveraging predictive analytics to anticipate supplier disruptions, thereby reducing exposure and preserving service continuity.
Deep segmentation insights reveal how component choices, functional needs, advanced technologies, deployment preferences, and vertical demands determine adoption and value realization
A granular view of segmentation reveals distinct adoption patterns and value drivers across components, functional domains, technologies, deployment modes, organization sizes, and industry verticals. In component terms, services adoption skews toward managed services where organizations seek outsourced operational expertise, and professional services remain essential for complex integrations and bespoke implementations; software adoption concentrates around dashboards and scorecards for executive oversight, data integration and ETL for lineage and quality management, query and analysis tools for analysts, and reporting and visualization platforms for broad stakeholder consumption. Functionally, analytics use proliferates in customer service to improve retention and support efficiency, in finance to enhance forecasting and controls, in human resources to optimize talent and workforce planning, in operations to streamline processes and reduce costs, and in sales and marketing to refine targeting and measure campaign impact.
From a technology standpoint, advanced and predictive analytics drive strategic differentiation through machine learning and prescriptive models, location intelligence augments contextual decisioning for field operations and retail placement, mobile BI brings insights to on-the-go workers, social BI enables reputation and sentiment analysis, and traditional BI continues to provide the stable reporting foundation organizations rely upon. Deployment mode choices reflect a clear tension between cloud-based solutions that offer scalability and rapid innovation and on-premises deployments that deliver control and data residency. Organization size shapes adoption curves, with large enterprises often investing in integrated platforms and cross-functional programs while small and medium enterprises pursue focused, cost-effective solutions that deliver rapid ROI. Industry verticals demonstrate unique priorities: banking, financial services, and insurance emphasize risk, compliance, and customer analytics; education and government prioritize transparency and operational efficiency; healthcare focuses on patient outcomes and data privacy; IT and telecom prioritize network and customer analytics; manufacturing targets supply chain and production optimization; and retail and e-commerce prioritize personalization, inventory optimization, and omnichannel analytics.
How regional regulatory environments, infrastructure maturity, and local ecosystem dynamics influence deployment, adoption patterns, and partner strategies
Regional dynamics are reshaping investment priorities and deployment strategies, with each geography presenting distinct regulatory, talent, and infrastructure considerations. In the Americas, organizations continue to accelerate cloud adoption and embedded analytics, driven by strong demand for real-time operational insights, customer analytics, and consolidated reporting across distributed operations. Investment in managed services and cloud-native analytics platforms is prevalent, and there is a pronounced focus on regulatory compliance and data governance frameworks that align with regional privacy expectations.
Across Europe, Middle East & Africa, regulatory regimes and data sovereignty concerns shape deployment patterns, often favoring hybrid architectures and local data handling capabilities. Public sector modernization initiatives and digital transformation in regulated industries such as banking and healthcare are creating sustained demand for secure, auditable analytics solutions. In Asia-Pacific, rapid digital adoption and mobile-first behaviors drive demand for location intelligence, mobile BI, and social analytics, while a competitive vendor landscape and strong growth in small and medium enterprise spending encourage modular, consumption-based pricing models. Each region’s ecosystem nuances influence partner selection, implementation timelines, and talent availability, requiring tailored go-to-market and delivery approaches.
Competitive landscape shaped by platform depth, specialist expertise, partnerships, and outcome-oriented services that drive successful adoption and differentiation
Competitive dynamics in the business intelligence and analytics ecosystem reflect a mix of established enterprise software providers, nimble specialists, and systems integrators that together shape buyer choices through product capability, service depth, and network presence. Market leaders differentiate through integrated platforms that combine data integration, governance, and advanced analytics, while focused specialists capture pockets of demand by delivering depth in areas such as location intelligence, mobile analytics, or domain-specific reporting. Partnerships and alliances between technology vendors, cloud providers, and consulting firms play a pivotal role in enabling end-to-end solutions that address complex enterprise requirements.
At the same time, companies that emphasize interoperability, open APIs, and clear upgrade paths tend to win enterprise trust, especially among large organizations with heterogeneous technology stacks. Service providers that offer outcome-oriented engagements, measured by operational metrics and business KPIs rather than only technical deliverables, are increasingly preferred. Additionally, investment in professional services and customer success functions is a consistent differentiator, because successful adoption often hinges on change management, training, and iterative performance tuning rather than on product features alone.
Actionable steps for executives to align analytics investments, governance, talent, and procurement strategies to accelerate adoption and reduce strategic risk
Leaders should prioritize a set of pragmatic actions that accelerate value delivery while reducing operational and regulatory risk. First, align analytics investments with defined business outcomes by selecting high-impact use cases in customer service, finance, operations, or sales and marketing, and apply iterative pilots to validate hypotheses and measure ROI. Second, adopt hybrid architecture strategies that combine cloud-based innovation with on-premises controls where data residency or latency demands require it, thereby preserving flexibility while respecting regulatory constraints.
Third, strengthen data governance and privacy frameworks to ensure that accelerated analytics adoption does not outpace controls; this includes cataloging critical data assets, defining clear ownership, and embedding privacy-by-design into development cycles. Fourth, invest in skills and change management to broaden analytic literacy across roles, enabling frontline managers and non-technical users to leverage dashboards and embedded insights effectively. Fifth, reassess procurement and supplier strategies in light of tariff exposure and geopolitical risk by exploring local sourcing, flexible licensing, and managed services that shift capital intensity away from hardware. Finally, cultivate vendor ecosystems and implementation partners that offer vertical expertise, proven delivery methodologies, and measurable outcome guarantees to de-risk large-scale deployments.
A rigorous, multi-method research process combining executive interviews, secondary analysis, segmentation mapping, and validation workshops to ensure credible and actionable insights
The research approach synthesizes qualitative and quantitative methods to produce robust, validated insights. Primary research included structured interviews with executives across functions such as finance, operations, sales, and IT, as well as discussions with service providers and implementation partners to capture real-world deployment experiences and pain points. Secondary research complemented these perspectives by analyzing white papers, regulatory publications, vendor documentation, and public filings to trace technology trends and policy developments. Data triangulation reconciled divergent viewpoints by cross-validating interview findings with documented evidence and practitioner feedback.
Segmentation mapping was applied to organize findings across components, functions, technologies, deployment modes, organization sizes, and industry verticals, ensuring that conclusions reflect heterogeneous adoption patterns. Where possible, longitudinal comparisons highlighted directional shifts year over year without relying on proprietary projections. To preserve rigor, validation workshops with industry practitioners were convened to stress-test assumptions and refine recommendations. Limitations include variation in regional data availability and evolving policy landscapes, which were addressed through scenario analysis and sensitivity checks to maintain the relevance and applicability of the insights.
A concise synthesis of strategic priorities, operational imperatives, and risk mitigations that executives must pursue to convert analytics potential into competitive advantage
In closing, the convergence of cloud-native delivery, advanced analytics, and evolving governance expectations is reshaping how organizations capture value from data. Executives who proactively align cross-functional priorities, invest in governed analytics capabilities, and pursue flexible deployment models will be better positioned to translate insight into measurable operational and customer-facing outcomes. The tariff environment and geopolitical uncertainty further underscore the need for adaptable procurement strategies and vendor relationships that can absorb disruption while preserving service continuity.
Moving forward, organizations should focus on practical, high-impact initiatives that demonstrate quick wins while building foundational capabilities such as data quality, cataloging, and governance. By adopting iterative delivery models, investing in analytic literacy, and partnering with providers that offer outcome-oriented services, leaders can accelerate adoption and realize sustained returns. The imperative for action is clear: thoughtful, coordinated investment across technology, people, and process will determine which organizations convert analytics potential into competitive advantage.
Note: PDF & Excel + Online Access - 1 Year
A strategic orientation for business intelligence leaders to align technology, talent, and governance toward measurable outcomes and sustained competitive advantage
The contemporary business intelligence landscape requires leaders to recalibrate strategy around data-driven decision making, operational resilience, and accelerated digital initiatives. Organizations face heightened expectations from stakeholders to convert complex data flows into timely, actionable insights that inform both tactical operations and long-term strategy. As budgets shift toward cloud architectures and analytics embedded into workflows, executives must balance technology investment with governance, talent, and process change to realize measurable outcomes.
In practice, this means aligning cross-functional priorities so that analytics initiatives are not siloed within IT or a single business unit. Successful programs integrate stakeholder input from finance, operations, sales, and customer service early in the scoping phase, and they adopt iterative delivery models that prioritize high-impact use cases. Consequently, leaders who couple disciplined data stewardship with pragmatic deployment plans create durable competitive advantage, while those who delay integration and change management risk wasted investment and slow adoption.
How emerging technologies, evolving deployment models, and governance pressures are jointly redefining where and how business intelligence delivers strategic value
Several transformative shifts are reshaping how organizations conceive and deploy business intelligence, and these shifts demand both tactical responses and strategic repositioning. First, the transition from descriptive reporting to embedded analytics and predictive capabilities is changing where value is captured, moving insights closer to decision makers in operations, customer service, and sales. Second, cloud-native architectures and hybrid deployments enable faster iteration and lower friction for scaling analytics, though they also introduce nuanced governance and integration challenges.
Moreover, the democratization of analytics tools is broadening user personas, which elevates the importance of intuitive interfaces, governed data catalogs, and training programs. Advances in location intelligence, mobile access, and social analytics are expanding the scope of insight beyond traditional business intelligence use cases, enabling contextualized decisions in field service, retail, and marketing operations. Finally, intensified focus on privacy, data protection, and ethical AI is prompting more rigorous controls and transparency throughout the analytics development lifecycle, ensuring trust and regulatory compliance.
Practical consequences of tariff adjustments on global procurement, vendor strategies, and the shift toward software-first and cloud-delivered analytics solutions
The introduction of tariffs and trade policy adjustments in 2025 has introduced tangible complexity across procurement, supply chain planning, and cost management for organizations relying on global technology and services ecosystems. Tariffs alter the landed cost of hardware and certain software bundles when bundled with proprietary appliances, prompting procurement teams to re-evaluate supplier contracts, consider alternate sourcing strategies, and accelerate conversations about software-centric architectures that reduce dependence on tariff-exposed components.
As a result, finance and procurement leaders are increasingly collaborating with IT and product teams to model scenario-based cost implications, identify opportunities for localizing certain services, and renegotiate commercial terms that allocate geopolitical risk more equitably. Simultaneously, vendors and systems integrators are responding by offering more flexible licensing, cloud-first delivery options, and managed services that abstract hardware ownership. Over time, these adaptations are shifting investment toward software, cloud consumption, and service-level guarantees that mitigate tariff volatility. In addition, organizations are strengthening inventory optimization and leveraging predictive analytics to anticipate supplier disruptions, thereby reducing exposure and preserving service continuity.
Deep segmentation insights reveal how component choices, functional needs, advanced technologies, deployment preferences, and vertical demands determine adoption and value realization
A granular view of segmentation reveals distinct adoption patterns and value drivers across components, functional domains, technologies, deployment modes, organization sizes, and industry verticals. In component terms, services adoption skews toward managed services where organizations seek outsourced operational expertise, and professional services remain essential for complex integrations and bespoke implementations; software adoption concentrates around dashboards and scorecards for executive oversight, data integration and ETL for lineage and quality management, query and analysis tools for analysts, and reporting and visualization platforms for broad stakeholder consumption. Functionally, analytics use proliferates in customer service to improve retention and support efficiency, in finance to enhance forecasting and controls, in human resources to optimize talent and workforce planning, in operations to streamline processes and reduce costs, and in sales and marketing to refine targeting and measure campaign impact.
From a technology standpoint, advanced and predictive analytics drive strategic differentiation through machine learning and prescriptive models, location intelligence augments contextual decisioning for field operations and retail placement, mobile BI brings insights to on-the-go workers, social BI enables reputation and sentiment analysis, and traditional BI continues to provide the stable reporting foundation organizations rely upon. Deployment mode choices reflect a clear tension between cloud-based solutions that offer scalability and rapid innovation and on-premises deployments that deliver control and data residency. Organization size shapes adoption curves, with large enterprises often investing in integrated platforms and cross-functional programs while small and medium enterprises pursue focused, cost-effective solutions that deliver rapid ROI. Industry verticals demonstrate unique priorities: banking, financial services, and insurance emphasize risk, compliance, and customer analytics; education and government prioritize transparency and operational efficiency; healthcare focuses on patient outcomes and data privacy; IT and telecom prioritize network and customer analytics; manufacturing targets supply chain and production optimization; and retail and e-commerce prioritize personalization, inventory optimization, and omnichannel analytics.
How regional regulatory environments, infrastructure maturity, and local ecosystem dynamics influence deployment, adoption patterns, and partner strategies
Regional dynamics are reshaping investment priorities and deployment strategies, with each geography presenting distinct regulatory, talent, and infrastructure considerations. In the Americas, organizations continue to accelerate cloud adoption and embedded analytics, driven by strong demand for real-time operational insights, customer analytics, and consolidated reporting across distributed operations. Investment in managed services and cloud-native analytics platforms is prevalent, and there is a pronounced focus on regulatory compliance and data governance frameworks that align with regional privacy expectations.
Across Europe, Middle East & Africa, regulatory regimes and data sovereignty concerns shape deployment patterns, often favoring hybrid architectures and local data handling capabilities. Public sector modernization initiatives and digital transformation in regulated industries such as banking and healthcare are creating sustained demand for secure, auditable analytics solutions. In Asia-Pacific, rapid digital adoption and mobile-first behaviors drive demand for location intelligence, mobile BI, and social analytics, while a competitive vendor landscape and strong growth in small and medium enterprise spending encourage modular, consumption-based pricing models. Each region’s ecosystem nuances influence partner selection, implementation timelines, and talent availability, requiring tailored go-to-market and delivery approaches.
Competitive landscape shaped by platform depth, specialist expertise, partnerships, and outcome-oriented services that drive successful adoption and differentiation
Competitive dynamics in the business intelligence and analytics ecosystem reflect a mix of established enterprise software providers, nimble specialists, and systems integrators that together shape buyer choices through product capability, service depth, and network presence. Market leaders differentiate through integrated platforms that combine data integration, governance, and advanced analytics, while focused specialists capture pockets of demand by delivering depth in areas such as location intelligence, mobile analytics, or domain-specific reporting. Partnerships and alliances between technology vendors, cloud providers, and consulting firms play a pivotal role in enabling end-to-end solutions that address complex enterprise requirements.
At the same time, companies that emphasize interoperability, open APIs, and clear upgrade paths tend to win enterprise trust, especially among large organizations with heterogeneous technology stacks. Service providers that offer outcome-oriented engagements, measured by operational metrics and business KPIs rather than only technical deliverables, are increasingly preferred. Additionally, investment in professional services and customer success functions is a consistent differentiator, because successful adoption often hinges on change management, training, and iterative performance tuning rather than on product features alone.
Actionable steps for executives to align analytics investments, governance, talent, and procurement strategies to accelerate adoption and reduce strategic risk
Leaders should prioritize a set of pragmatic actions that accelerate value delivery while reducing operational and regulatory risk. First, align analytics investments with defined business outcomes by selecting high-impact use cases in customer service, finance, operations, or sales and marketing, and apply iterative pilots to validate hypotheses and measure ROI. Second, adopt hybrid architecture strategies that combine cloud-based innovation with on-premises controls where data residency or latency demands require it, thereby preserving flexibility while respecting regulatory constraints.
Third, strengthen data governance and privacy frameworks to ensure that accelerated analytics adoption does not outpace controls; this includes cataloging critical data assets, defining clear ownership, and embedding privacy-by-design into development cycles. Fourth, invest in skills and change management to broaden analytic literacy across roles, enabling frontline managers and non-technical users to leverage dashboards and embedded insights effectively. Fifth, reassess procurement and supplier strategies in light of tariff exposure and geopolitical risk by exploring local sourcing, flexible licensing, and managed services that shift capital intensity away from hardware. Finally, cultivate vendor ecosystems and implementation partners that offer vertical expertise, proven delivery methodologies, and measurable outcome guarantees to de-risk large-scale deployments.
A rigorous, multi-method research process combining executive interviews, secondary analysis, segmentation mapping, and validation workshops to ensure credible and actionable insights
The research approach synthesizes qualitative and quantitative methods to produce robust, validated insights. Primary research included structured interviews with executives across functions such as finance, operations, sales, and IT, as well as discussions with service providers and implementation partners to capture real-world deployment experiences and pain points. Secondary research complemented these perspectives by analyzing white papers, regulatory publications, vendor documentation, and public filings to trace technology trends and policy developments. Data triangulation reconciled divergent viewpoints by cross-validating interview findings with documented evidence and practitioner feedback.
Segmentation mapping was applied to organize findings across components, functions, technologies, deployment modes, organization sizes, and industry verticals, ensuring that conclusions reflect heterogeneous adoption patterns. Where possible, longitudinal comparisons highlighted directional shifts year over year without relying on proprietary projections. To preserve rigor, validation workshops with industry practitioners were convened to stress-test assumptions and refine recommendations. Limitations include variation in regional data availability and evolving policy landscapes, which were addressed through scenario analysis and sensitivity checks to maintain the relevance and applicability of the insights.
A concise synthesis of strategic priorities, operational imperatives, and risk mitigations that executives must pursue to convert analytics potential into competitive advantage
In closing, the convergence of cloud-native delivery, advanced analytics, and evolving governance expectations is reshaping how organizations capture value from data. Executives who proactively align cross-functional priorities, invest in governed analytics capabilities, and pursue flexible deployment models will be better positioned to translate insight into measurable operational and customer-facing outcomes. The tariff environment and geopolitical uncertainty further underscore the need for adaptable procurement strategies and vendor relationships that can absorb disruption while preserving service continuity.
Moving forward, organizations should focus on practical, high-impact initiatives that demonstrate quick wins while building foundational capabilities such as data quality, cataloging, and governance. By adopting iterative delivery models, investing in analytic literacy, and partnering with providers that offer outcome-oriented services, leaders can accelerate adoption and realize sustained returns. The imperative for action is clear: thoughtful, coordinated investment across technology, people, and process will determine which organizations convert analytics potential into competitive advantage.
Note: PDF & Excel + Online Access - 1 Year
Table of Contents
188 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Rapid adoption of AI-driven hyper-personalization in e-commerce customer journeys optimizing conversion rates
- 5.2. Surge in eco-conscious packaging innovations among direct-to-consumer brands to address sustainability demands
- 5.3. Growth of cross-border digital payment platforms leveraging blockchain for cost-efficient global transactions
- 5.4. Expansion of subscription-based business models in consumer electronics driving predictable revenue streams
- 5.5. Implementation of real-time supply chain visibility through IoT sensors and predictive analytics for resilience
- 5.6. Rising investments in carbon capture and storage technologies by energy companies under evolving regulations
- 5.7. Emergence of augmented reality try-on features in online fashion retail to enhance shopper engagement
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Business Intelligence Market, by Component
- 8.1. Services
- 8.1.1. Managed Services
- 8.1.2. Professional Services
- 8.2. Software
- 8.2.1. Dashboards & Scorecards
- 8.2.2. Data Integration & ETL
- 8.2.3. Query & Analysis
- 8.2.4. Reporting & Visualization
- 9. Business Intelligence Market, by Function
- 9.1. Customer Service
- 9.2. Finance
- 9.3. Human Resources
- 9.4. Operations
- 9.5. Sales & Marketing
- 10. Business Intelligence Market, by Technology
- 10.1. Advanced & Predictive Analytics
- 10.2. Location Intelligence
- 10.3. Mobile BI
- 10.4. Social BI
- 10.5. Traditional BI
- 11. Business Intelligence Market, by Deployment Mode
- 11.1. Cloud-Based
- 11.2. On-Premises
- 12. Business Intelligence Market, by Organization Size
- 12.1. Large Enterprises
- 12.2. Small & Medium Enterprises
- 13. Business Intelligence Market, by Industry Vertical
- 13.1. Banking, Financial Services, and Insurance
- 13.2. Education
- 13.3. Government & Defense
- 13.4. Healthcare
- 13.5. IT & Telecom
- 13.6. Manufacturing
- 13.7. Retail & E-Commerce
- 14. Business Intelligence Market, by Region
- 14.1. Americas
- 14.1.1. North America
- 14.1.2. Latin America
- 14.2. Europe, Middle East & Africa
- 14.2.1. Europe
- 14.2.2. Middle East
- 14.2.3. Africa
- 14.3. Asia-Pacific
- 15. Business Intelligence Market, by Group
- 15.1. ASEAN
- 15.2. GCC
- 15.3. European Union
- 15.4. BRICS
- 15.5. G7
- 15.6. NATO
- 16. Business Intelligence Market, by Country
- 16.1. United States
- 16.2. Canada
- 16.3. Mexico
- 16.4. Brazil
- 16.5. United Kingdom
- 16.6. Germany
- 16.7. France
- 16.8. Russia
- 16.9. Italy
- 16.10. Spain
- 16.11. China
- 16.12. India
- 16.13. Japan
- 16.14. Australia
- 16.15. South Korea
- 17. Competitive Landscape
- 17.1. Market Share Analysis, 2024
- 17.2. FPNV Positioning Matrix, 2024
- 17.3. Competitive Analysis
- 17.3.1. Alteryx Inc.
- 17.3.2. Cisco Systems Inc.
- 17.3.3. Databricks, Inc.
- 17.3.4. Domo, Inc.
- 17.3.5. GoodData Corporation
- 17.3.6. Google LLC By Alphabet Inc.
- 17.3.7. Hitachi Vantara LLC
- 17.3.8. Idera, Inc.
- 17.3.9. International Business Machines Corporation
- 17.3.10. Koch Industries, Inc.
- 17.3.11. Microsoft Corporation
- 17.3.12. MicroStrategy, Inc.
- 17.3.13. Oracle Corporation
- 17.3.14. QlikTech International AB
- 17.3.15. Rackspace US, Inc.
- 17.3.16. Salesforce, Inc.
- 17.3.17. SAP SE
- 17.3.18. SAS Institute Inc.
- 17.3.19. Sisense Inc.
- 17.3.20. TARGIT A/S
- 17.3.21. ThoughtSpot, Inc.
- 17.3.22. TIBCO Software Inc.
- 17.3.23. Top Ramdor Systems & Computers (1990) LTD Company
- 17.3.24. VMware Inc.
- 17.3.25. Zoho Corporation Pvt. Ltd.
Pricing
Currency Rates
Questions or Comments?
Our team has the ability to search within reports to verify it suits your needs. We can also help maximize your budget by finding sections of reports you can purchase.
