Summary

The Global Business Intelligence Market was valued at USD 29.61 Billion in 2023 and is predicted to experience robust growth in the forecast period with a CAGR of 12.53% through 2029.
The global Business Intelligence (BI) market is experiencing significant growth, driven by the increasing need for data-driven decision-making, advancements in technology, and the rising adoption of cloud-based solutions. Businesses across various sectors are increasingly recognizing the value of leveraging BI tools to analyze vast amounts of data and gain actionable insights that enhance operational efficiency, improve customer experiences, and drive strategic initiatives. The proliferation of big data and the Internet of Things (IoT) has resulted in an explosion of data generation, making advanced analytics and BI tools essential for organizations to remain competitive. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) into BI platforms is revolutionizing the way businesses interpret data, offering predictive and prescriptive insights that were previously unattainable.
Cloud computing plays a pivotal role in the BI market's expansion, offering scalability, cost-effectiveness, and ease of access. Cloud-based BI solutions enable businesses of all sizes to deploy sophisticated analytics tools without the need for significant upfront investment in infrastructure. This democratization of BI tools is particularly beneficial for small and medium-sized enterprises (SMEs), allowing them to compete with larger organizations by making data-driven decisions. Additionally, the mobile BI trend is gaining traction, with the increasing use of smartphones and tablets enabling decision-makers to access real-time analytics on the go, thereby enhancing agility and responsiveness.
The BI market is also witnessing robust growth due to the rising demand for personalized customer experiences. Businesses are leveraging BI tools to analyze customer data, understand preferences, and deliver tailored offerings that enhance satisfaction and loyalty. In sectors such as retail, healthcare, and finance, BI applications are proving instrumental in optimizing supply chain operations, improving patient care, and detecting fraudulent activities, respectively. Despite the numerous benefits, challenges such as data privacy concerns, integration issues, and a shortage of skilled professionals persist. However, continuous technological advancements and increasing investments in BI solutions are expected to mitigate these challenges, further propelling market growth. Overall, the global Business Intelligence market is poised for substantial expansion, driven by technological innovation and the ever-growing importance of data in strategic business decision-making.
Key Market Drivers
Data-Driven Decision Making
The demand for data-driven decision-making is a primary driver of the global Business Intelligence (BI) market. In today's competitive business environment, organizations are increasingly relying on data analytics to inform their strategies and operations. BI tools enable companies to process vast amounts of data, extract actionable insights, and make informed decisions quickly. This data-centric approach helps businesses identify trends, forecast future outcomes, and uncover opportunities for growth and improvement. The ability to access real-time data and generate detailed reports empowers decision-makers to react swiftly to market changes and customer needs, enhancing operational efficiency and competitive advantage. Moreover, data-driven decision-making supports the identification of key performance indicators (KPIs) and metrics that are crucial for measuring success and achieving business objectives. As more organizations recognize the strategic value of leveraging data for decision-making, the adoption of BI solutions continues to rise, fueling market growth.
Technological Advancements
Technological advancements are significantly propelling the growth of the global BI market. Innovations in artificial intelligence (AI), machine learning (ML), and big data analytics are transforming BI tools, making them more powerful and user-friendly. AI and ML algorithms enhance the capabilities of BI platforms by enabling advanced data analysis, predictive analytics, and automated insights. These technologies allow businesses to uncover patterns and correlations that were previously hidden, providing deeper insights and more accurate forecasts. Additionally, the integration of natural language processing (NLP) and conversational interfaces simplifies the interaction with BI tools, making them accessible to non-technical users. Furthermore, advancements in data visualization techniques enable more intuitive and interactive dashboards, helping users easily interpret complex data sets. Cloud computing also plays a critical role, offering scalable and cost-effective BI solutions that can be accessed from anywhere. As technology continues to evolve, it drives the adoption of BI tools, expanding their application across various industries and enhancing their value proposition.
Rising Adoption of Cloud-Based Solutions
The increasing adoption of cloud-based BI solutions is a significant driver of market growth. Cloud computing offers numerous advantages, including scalability, flexibility, and cost-efficiency, which make BI tools accessible to businesses of all sizes. Cloud-based BI solutions eliminate the need for substantial upfront investments in hardware and infrastructure, reducing the financial barriers for small and medium-sized enterprises (SMEs). These solutions provide easy deployment, automatic updates, and seamless integration with existing systems, enhancing operational efficiency and reducing maintenance efforts. Additionally, cloud BI enables real-time data access and collaboration, allowing teams to work together effectively, regardless of their location. The ability to scale resources up or down based on demand ensures that businesses can handle varying data loads without compromising performance. As more organizations migrate to the cloud, driven by the need for agility and cost savings, the demand for cloud-based BI solutions continues to surge, driving the overall growth of the BI market.
Increased Focus on Customer Experience
An increased focus on enhancing customer experience is driving the adoption of BI tools across various industries. Businesses are leveraging BI solutions to gain a deeper understanding of customer behavior, preferences, and feedback. By analyzing customer data, companies can personalize their offerings, improve service quality, and foster stronger customer relationships. BI tools enable businesses to track and analyze customer interactions across multiple touchpoints, providing insights into the customer journey and identifying areas for improvement. This customer-centric approach helps in developing targeted marketing campaigns, optimizing sales strategies, and enhancing customer support. In sectors like retail, healthcare, and finance, where customer satisfaction is critical, BI applications play a crucial role in delivering tailored experiences that drive loyalty and retention. As the importance of customer experience continues to rise, organizations are increasingly investing in BI solutions to stay competitive and meet evolving customer expectations.
Key Market Challenges
Data Privacy and Security Concerns
One of the foremost challenges facing the global Business Intelligence (BI) market is data privacy and security. As organizations increasingly rely on BI tools to collect, store, and analyze vast amounts of sensitive information, the risk of data breaches and cyberattacks escalates. Companies must navigate stringent data protection regulations such as the General Data Protection Regulation (GDPR) in Europe, the California Consumer Privacy Act (CCPA) in the United States, and other local laws, which mandate rigorous data handling and security measures. Non-compliance can result in hefty fines and legal repercussions, not to mention severe reputational damage.
Moreover, the integration of BI systems with various data sources, including cloud platforms, on-premises databases, and third-party applications, creates multiple points of vulnerability. Ensuring robust encryption, access control, and continuous monitoring across these diverse environments is complex and resource-intensive. Data breaches can lead to significant financial losses and undermine customer trust, making security a top priority for businesses. Organizations must invest in advanced security technologies and adopt comprehensive data governance frameworks to safeguard against these threats. However, balancing the need for extensive data collection and analysis with stringent privacy requirements remains a delicate and ongoing challenge for the BI market.
Integration with Legacy Systems
Another significant challenge in the global BI market is the integration of BI tools with existing legacy systems. Many organizations operate with a patchwork of outdated IT infrastructures that were not designed to handle modern BI applications. These legacy systems often lack the interoperability and flexibility needed to seamlessly integrate with advanced BI platforms, leading to data silos and fragmented information flows.
The process of integrating BI solutions with legacy systems can be costly and time-consuming, requiring substantial investments in middleware, custom coding, and IT expertise. Moreover, there is a risk of data inconsistencies and inaccuracies during the integration process, which can compromise the quality and reliability of the BI insights generated. Organizations must undertake comprehensive data mapping and cleansing initiatives to ensure that data from disparate systems can be accurately consolidated and analyzed.
Additionally, legacy systems may not support real-time data processing and analytics, which are crucial for making timely and informed business decisions. Upgrading or replacing these systems with modern, scalable solutions that can fully leverage the capabilities of BI tools is often a necessary but challenging undertaking. The resistance to change from within the organization, coupled with the high costs associated with overhauling legacy systems, further complicates the integration process. As such, businesses must carefully plan and execute their BI integration strategies to overcome these hurdles and realize the full potential of their BI investments.
Shortage of Skilled Professionals
The global Business Intelligence market is grappling with a significant shortage of skilled professionals. As BI tools and technologies become more sophisticated, the demand for experts who can effectively deploy, manage, and interpret these systems has surged. However, there is a notable gap between the available talent and the skills required to meet the evolving needs of the BI industry.
BI professionals need a diverse skill set that includes technical proficiency in data analytics, database management, and software development, as well as strong business acumen to translate data insights into actionable strategies. Additionally, expertise in emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data analytics is increasingly essential. However, the pace of technological advancements often outstrips the ability of educational institutions and training programs to equip individuals with the necessary competencies.
Organizations face challenges in recruiting and retaining qualified BI professionals, leading to increased competition for top talent. This talent shortage can result in delayed project timelines, suboptimal implementation of BI solutions, and underutilization of the full capabilities of BI tools. Furthermore, the lack of skilled personnel can hinder an organization’s ability to derive meaningful insights from their data, impacting their decision-making processes and overall business performance.
High Implementation Costs
High implementation costs represent a substantial challenge in the global Business Intelligence market. Deploying BI solutions involves significant financial investments in software, hardware, and infrastructure. Additionally, there are costs associated with data integration, customization, and training personnel to effectively use these tools. For small and medium-sized enterprises (SMEs), these costs can be particularly prohibitive, limiting their ability to leverage BI for competitive advantage.
The initial outlay for BI software licenses can be substantial, especially for advanced analytics platforms that offer comprehensive features and capabilities. Moreover, the need for robust IT infrastructure to support BI applications adds to the financial burden. This includes investments in servers, storage, networking equipment, and cloud services, all of which must be scalable to accommodate growing data volumes and user demands.
Customization and integration costs further inflate the total expenditure. Tailoring BI solutions to meet specific business requirements and ensuring seamless integration with existing systems often require significant development efforts and specialized expertise. These processes can be time-consuming and resource-intensive, leading to project overruns and increased expenses.
Training and change management also contribute to the high costs of BI implementation. Employees must be adequately trained to use BI tools and interpret the insights generated, which involves both time and money. Additionally, fostering a data-driven culture within the organization may necessitate changes in workflows and business processes, further adding to the overall cost.
While cloud-based BI solutions offer a more cost-effective alternative by reducing upfront infrastructure investments, the subscription-based pricing models can still be expensive over the long term. To mitigate these challenges, organizations need to carefully evaluate their BI needs, prioritize essential features, and adopt a phased implementation approach to manage costs effectively
Key Market Trends
Integration of Artificial Intelligence and Machine Learning in BI
The integration of artificial intelligence (AI) and machine learning (ML) into Business Intelligence (BI) platforms is transforming the landscape of data analytics. Traditional BI tools focused primarily on descriptive and diagnostic analytics, which explain what happened and why. However, the infusion of AI and ML is pushing the boundaries toward predictive and prescriptive analytics. Predictive analytics uses historical data to forecast future trends and behaviors, while prescriptive analytics suggests possible actions based on these predictions. This shift enables businesses to not only understand past and present data but also to make informed decisions about the future. AI-driven BI tools can automate data preparation, identify patterns, and generate insights without manual intervention, significantly reducing the time and effort required for data analysis. For instance, anomaly detection algorithms can automatically identify outliers in financial transactions, helping to detect fraud. Moreover, natural language processing (NLP) allows users to interact with BI systems using conversational language, making advanced analytics accessible to non-technical users. This democratization of BI empowers a broader range of employees to leverage data in their decision-making processes, fostering a data-driven culture within organizations. As AI and ML technologies continue to advance, their integration into BI platforms is expected to become more seamless and sophisticated, driving further innovation and efficiency in data analytics.
Growing Adoption of Self-Service BI
Self-service Business Intelligence (BI) is gaining traction as organizations seek to empower their employees with the tools necessary to analyze data independently. Traditional BI systems often relied on IT departments to generate reports and dashboards, creating bottlenecks and limiting agility. In contrast, self-service BI tools enable end-users, including non-technical staff, to access, analyze, and visualize data without extensive IT involvement. This trend is fueled by the increasing availability of user-friendly BI platforms that offer drag-and-drop interfaces, intuitive dashboards, and interactive data visualization capabilities. By enabling employees at all levels to perform their own analyses, organizations can foster a more data-driven culture and enhance decision-making processes. Self-service BI tools also promote faster and more flexible reporting, allowing users to explore data in real-time and gain insights on demand. This agility is particularly valuable in dynamic business environments where timely information is crucial for maintaining a competitive edge. Additionally, self-service BI reduces the burden on IT departments, freeing them to focus on more strategic initiatives rather than routine data requests. As organizations continue to recognize the benefits of empowering their workforce with self-service BI, the adoption of these tools is expected to grow, driving significant changes in how data is accessed and utilized across industries.
Rise of Cloud-Based BI Solutions
The rise of cloud-based Business Intelligence (BI) solutions is a major trend shaping the global BI market. Traditional on-premises BI systems require significant upfront investment in hardware and infrastructure, along with ongoing maintenance costs. In contrast, cloud-based BI solutions offer a more flexible and cost-effective alternative. These platforms provide scalability, allowing organizations to adjust their resources based on demand without significant capital expenditure. Cloud BI solutions also offer enhanced accessibility, enabling users to access data and analytics tools from anywhere with an internet connection. This is particularly beneficial for organizations with distributed workforces or those that have adopted remote working practices. Furthermore, cloud-based BI platforms often come with robust security measures and regular updates, ensuring that organizations can leverage the latest features and protections without additional effort. The ability to integrate with various data sources, including other cloud services and on-premises systems, further enhances the appeal of cloud BI. As businesses continue to embrace digital transformation and seek agile, scalable solutions, the adoption of cloud-based BI is expected to accelerate, driving significant growth in the market.
Increased Focus on Data Governance and Security
As the volume of data generated by organizations continues to grow, the importance of data governance and security in Business Intelligence (BI) is becoming increasingly prominent. Effective data governance ensures that data is accurate, consistent, and accessible while maintaining compliance with regulatory requirements. In the context of BI, robust data governance frameworks help organizations manage the quality and integrity of their data, which is crucial for generating reliable insights. With the rising concerns over data privacy and security breaches, organizations are placing greater emphasis on implementing stringent data security measures. This includes encryption, access controls, and regular audits to protect sensitive information. The introduction of regulations such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States has further highlighted the need for comprehensive data governance and security practices. BI platforms are increasingly incorporating features that support these requirements, such as data lineage tracking, audit trails, and role-based access controls. By prioritizing data governance and security, organizations can ensure that their BI initiatives are both effective and compliant, fostering trust among stakeholders and minimizing risks associated with data misuse.
Expansion of Embedded BI
The expansion of embedded Business Intelligence (BI) is transforming the way organizations utilize analytics. Embedded BI involves integrating BI capabilities directly into business applications, workflows, and processes, providing users with real-time insights within their existing tools and environments. This seamless integration enhances the user experience by delivering relevant data and analytics at the point of decision-making, without the need to switch between different systems. Embedded BI supports a wide range of applications, from customer relationship management (CRM) and enterprise resource planning (ERP) systems to specialized industry-specific software. By embedding BI into these applications, organizations can drive greater user adoption and leverage data more effectively to optimize operations and improve outcomes. For example, sales teams can access real-time sales performance metrics within their CRM systems, enabling them to make data-driven decisions and respond to opportunities more quickly. The growing demand for contextual and actionable insights is driving the adoption of embedded BI across various industries. As technology continues to evolve, the capabilities of embedded BI are expected to become more advanced, offering deeper integrations and more sophisticated analytics features. This trend is set to play a significant role in the future of BI, enabling organizations to harness the full potential of their data.
Segmental Insights
Component Insights
Software segment dominates in the global Business Intelligence market in 2023. The rapid pace of technological advancements has significantly enhanced BI software capabilities. Modern BI tools incorporate advanced technologies such as artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), enabling more sophisticated data analysis and visualization. These innovations allow businesses to gain deeper insights, predict trends, and make data-driven decisions with greater accuracy and speed. The continuous improvement and integration of these technologies into BI software have made them indispensable tools for organizations striving to stay competitive.
As businesses generate and collect vast amounts of data, the need for efficient data analysis and reporting has grown exponentially. BI software provides the necessary tools to process, analyze, and visualize data, transforming raw information into actionable insights. This capability is crucial for organizations seeking to optimize operations, enhance customer experiences, and identify new business opportunities. The ability to make informed decisions based on real-time data has become a strategic priority for companies across various industries, driving the adoption of BI software.
The trend towards self-service BI has further propelled the software segment's dominance. Self-service BI tools empower non-technical users to access and analyze data without relying heavily on IT departments. These user-friendly platforms typically feature drag-and-drop interfaces, intuitive dashboards, and interactive data visualization capabilities, making it easier for employees at all levels to perform their analyses. This democratization of data access fosters a data-driven culture within organizations, leading to more agile and informed decision-making processes.
The rise of cloud-based BI solutions has also played a significant role in the software segment's dominance. Cloud BI platforms offer scalability, flexibility, and cost-efficiency, allowing businesses to deploy and manage BI tools without the need for substantial upfront investments in infrastructure. The accessibility of cloud-based solutions enables organizations to leverage advanced analytics tools from anywhere, facilitating collaboration and real-time data sharing among teams. The ongoing shift towards digital transformation and remote work environments has further accelerated the adoption of cloud-based BI software.
BI software's adaptability to various industry-specific applications contributes to its widespread adoption. Different sectors, such as healthcare, finance, retail, and manufacturing, leverage BI tools to address their unique challenges and requirements. For instance, healthcare providers use BI software to improve patient care and operational efficiency, while retailers utilize it to enhance inventory management and customer insights. The versatility and customization options available in BI software make it an attractive solution for diverse industries.
Regional Insights
North America dominates the global Business Intelligence market in 2023. North America, particularly the United States, boasts a highly advanced technological infrastructure. This includes widespread high-speed internet access, robust data centers, and cutting-edge cloud computing capabilities. Such an infrastructure provides a solid foundation for the deployment and use of sophisticated BI tools. Companies in this region can leverage high-performance computing resources to handle big data analytics efficiently, which is crucial for the effective utilization of BI solutions.
The adoption rate of BI tools among North American enterprises is significantly high. Companies in this region have a strong emphasis on data-driven decision-making, which drives the demand for BI software. Organizations across various industries, including finance, healthcare, retail, and manufacturing, rely heavily on BI tools to gain insights from their data, optimize operations, enhance customer experiences, and maintain competitive advantage. This widespread adoption is a key factor contributing to North America's dominance in the BI market.
North America is a global leader in technology innovation, with substantial investment in research and development (R&D). The region's commitment to innovation is evident through the presence of numerous tech hubs, such as Silicon Valley, which foster the development of cutting-edge BI technologies. Venture capital firms and investors in North America are also highly active in funding startups and established companies that are driving advancements in BI, AI, and data analytics. This continuous flow of investment fuels the growth and evolution of the BI market.
The BI market in North America is supported by a thriving ecosystem of vendors and tech companies. Major BI software providers, such as Microsoft, IBM, Tableau, and SAS, are headquartered in the region, offering a wide range of advanced BI solutions to meet the diverse needs of businesses. Additionally, North America is home to numerous startups and emerging companies that are innovating in the BI space, further enriching the market with new products and services.
The regulatory environment in North America also plays a role in the adoption of BI tools. Regulations such as the Sarbanes-Oxley Act (SOX) and the Health Insurance Portability and Accountability Act (HIPAA) require organizations to maintain high standards of data accuracy, transparency, and security. BI tools help companies comply with these regulations by providing robust data management, reporting, and auditing capabilities. The focus on data security and compliance drives the demand for reliable and sophisticated BI solutions.
North America has a highly skilled workforce with strong data literacy. The region's educational institutions produce a large number of graduates with expertise in data science, analytics, and information technology. This availability of skilled professionals enables organizations to effectively implement and utilize BI tools. Moreover, continuous professional development and training programs help ensure that the workforce stays updated with the latest BI technologies and practices.
Key Market Players
• Microsoft Corporation
• Salesforce, Inc.
• SAP SE
• IBM Corporation
• Oracle Corporation
• QlikTech International AB
• SAS Institute Inc.
• Teradata Operations, Inc.
• Domo, Inc.
• ThoughtSpot Inc.
Report Scope:
In this report, the Global Business Intelligence Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
• Business Intelligence Market, By Component:
o Software
o Services
• Business Intelligence Market, By Deployment Model:
o On-Premise
o Cloud-Based
o Hybrid Model
• Business Intelligence Market, By Functionality:
o Data Warehousing
o Online Analytical Processing
o Online Analytical Mining
o Data Visualization
o Reporting
• Business Intelligence Market, By User Type:
o Business Users
o Data Analysts
o IT Professionals
• Business Intelligence Market, By Industry Vertical:
o BFSI
o Retail & E-commerce
o Manufacturing
o Healthcare
o Others
• Business Intelligence Market, By Region:
o North America
§ United States
§ Canada
§ Mexico
o Europe
§ Germany
§ France
§ United Kingdom
§ Italy
§ Spain
o South America
§ Brazil
§ Argentina
§ Colombia
o Asia-Pacific
§ China
§ India
§ Japan
§ South Korea
§ Australia
o Middle East & Africa
§ Saudi Arabia
§ UAE
§ South Africa
Competitive Landscape
Company Profiles: Detailed analysis of the major companies present in the Global Business Intelligence Market.
Available Customizations:
Global Business Intelligence Market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:
Company Information
• Detailed analysis and profiling of additional market players (up to five).

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Table of Contents

1. Product Overview
1.1. Market Definition
1.2. Scope of the Market
1.2.1. Markets Covered
1.2.2. Years Considered for Study
1.2.3. Key Market Segmentations
2. Research Methodology
2.1. Baseline Methodology
2.2. Key Industry Partners
2.3. Major Association and Secondary Sources
2.4. Forecasting Methodology
2.5. Data Triangulation & Validation
2.6. Assumptions and Limitations
3. Executive Summary
4. Voice of Customer
5. Global Business Intelligence Market Outlook
5.1. Market Size & Forecast
5.1.1. By Value
5.2. Market Share & Forecast
5.2.1. By Component (Software, Services)
5.2.2. By Deployment Model (On-Premise, Cloud-Based, Hybrid Model)
5.2.3. By Functionality (Data Warehousing, Online Analytical Processing, Online Analytical Mining, Data Visualization, Reporting)
5.2.4. By User Type (Business Users, Data Analysts, IT Professionals)
5.2.5. By Industry Vertical (BFSI, Retail & E-commerce, Manufacturing, Healthcare, Others)
5.2.6. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
5.3. By Company (2023)
5.4. Market Map
6. North America Business Intelligence Market Outlook
6.1. Market Size & Forecast
6.1.1. By Value
6.2. Market Share & Forecast
6.2.1. By Component
6.2.2. By Deployment Model
6.2.3. By Functionality
6.2.4. By User Type
6.2.5. By Industry Vertical
6.2.6. By Country
6.3. North America: Country Analysis
6.3.1. United States Business Intelligence Market Outlook
6.3.1.1. Market Size & Forecast
6.3.1.1.1. By Value
6.3.1.2. Market Share & Forecast
6.3.1.2.1. By Component
6.3.1.2.2. By Deployment Model
6.3.1.2.3. By Functionality
6.3.1.2.4. By User Type
6.3.1.2.5. By Industry Vertical
6.3.2. Canada Business Intelligence Market Outlook
6.3.2.1. Market Size & Forecast
6.3.2.1.1. By Value
6.3.2.2. Market Share & Forecast
6.3.2.2.1. By Component
6.3.2.2.2. By Deployment Model
6.3.2.2.3. By Functionality
6.3.2.2.4. By User Type
6.3.2.2.5. By Industry Vertical
6.3.3. Mexico Business Intelligence Market Outlook
6.3.3.1. Market Size & Forecast
6.3.3.1.1. By Value
6.3.3.2. Market Share & Forecast
6.3.3.2.1. By Component
6.3.3.2.2. By Deployment Model
6.3.3.2.3. By Functionality
6.3.3.2.4. By User Type
6.3.3.2.5. By Industry Vertical
7. Europe Business Intelligence Market Outlook
7.1. Market Size & Forecast
7.1.1. By Value
7.2. Market Share & Forecast
7.2.1. By Component
7.2.2. By Deployment Model
7.2.3. By Functionality
7.2.4. By User Type
7.2.5. By Industry Vertical
7.2.6. By Country
7.3. Europe: Country Analysis
7.3.1. Germany Business Intelligence Market Outlook
7.3.1.1. Market Size & Forecast
7.3.1.1.1. By Value
7.3.1.2. Market Share & Forecast
7.3.1.2.1. By Component
7.3.1.2.2. By Deployment Model
7.3.1.2.3. By Functionality
7.3.1.2.4. By User Type
7.3.1.2.5. By Industry Vertical
7.3.2. France Business Intelligence Market Outlook
7.3.2.1. Market Size & Forecast
7.3.2.1.1. By Value
7.3.2.2. Market Share & Forecast
7.3.2.2.1. By Component
7.3.2.2.2. By Deployment Model
7.3.2.2.3. By Functionality
7.3.2.2.4. By User Type
7.3.2.2.5. By Industry Vertical
7.3.3. United Kingdom Business Intelligence Market Outlook
7.3.3.1. Market Size & Forecast
7.3.3.1.1. By Value
7.3.3.2. Market Share & Forecast
7.3.3.2.1. By Component
7.3.3.2.2. By Deployment Model
7.3.3.2.3. By Functionality
7.3.3.2.4. By User Type
7.3.3.2.5. By Industry Vertical
7.3.4. Italy Business Intelligence Market Outlook
7.3.4.1. Market Size & Forecast
7.3.4.1.1. By Value
7.3.4.2. Market Share & Forecast
7.3.4.2.1. By Component
7.3.4.2.2. By Deployment Model
7.3.4.2.3. By Functionality
7.3.4.2.4. By User Type
7.3.4.2.5. By Industry Vertical
7.3.5. Spain Business Intelligence Market Outlook
7.3.5.1. Market Size & Forecast
7.3.5.1.1. By Value
7.3.5.2. Market Share & Forecast
7.3.5.2.1. By Component
7.3.5.2.2. By Deployment Model
7.3.5.2.3. By Functionality
7.3.5.2.4. By User Type
7.3.5.2.5. By Industry Vertical
8. South America Business Intelligence Market Outlook
8.1. Market Size & Forecast
8.1.1. By Value
8.2. Market Share & Forecast
8.2.1. By Component
8.2.2. By Deployment Model
8.2.3. By Functionality
8.2.4. By User Type
8.2.5. By Industry Vertical
8.2.6. By Country
8.3. South America: Country Analysis
8.3.1. Brazil Business Intelligence Market Outlook
8.3.1.1. Market Size & Forecast
8.3.1.1.1. By Value
8.3.1.2. Market Share & Forecast
8.3.1.2.1. By Component
8.3.1.2.2. By Deployment Model
8.3.1.2.3. By Functionality
8.3.1.2.4. By User Type
8.3.1.2.5. By Industry Vertical
8.3.2. Colombia Business Intelligence Market Outlook
8.3.2.1. Market Size & Forecast
8.3.2.1.1. By Value
8.3.2.2. Market Share & Forecast
8.3.2.2.1. By Component
8.3.2.2.2. By Deployment Model
8.3.2.2.3. By Functionality
8.3.2.2.4. By User Type
8.3.2.2.5. By Industry Vertical
8.3.3. Argentina Business Intelligence Market Outlook
8.3.3.1. Market Size & Forecast
8.3.3.1.1. By Value
8.3.3.2. Market Share & Forecast
8.3.3.2.1. By Component
8.3.3.2.2. By Deployment Model
8.3.3.2.3. By Functionality
8.3.3.2.4. By User Type
8.3.3.2.5. By Industry Vertical
9. Middle East & Africa Business Intelligence Market Outlook
9.1. Market Size & Forecast
9.1.1. By Value
9.2. Market Share & Forecast
9.2.1. By Component
9.2.2. By Deployment Model
9.2.3. By Functionality
9.2.4. By User Type
9.2.5. By Industry Vertical
9.2.6. By Country
9.3. Middle East & Africa: Country Analysis
9.3.1. Saudi Arabia Business Intelligence Market Outlook
9.3.1.1. Market Size & Forecast
9.3.1.1.1. By Value
9.3.1.2. Market Share & Forecast
9.3.1.2.1. By Component
9.3.1.2.2. By Deployment Model
9.3.1.2.3. By Functionality
9.3.1.2.4. By User Type
9.3.1.2.5. By Industry Vertical
9.3.2. UAE Business Intelligence Market Outlook
9.3.2.1. Market Size & Forecast
9.3.2.1.1. By Value
9.3.2.2. Market Share & Forecast
9.3.2.2.1. By Component
9.3.2.2.2. By Deployment Model
9.3.2.2.3. By Functionality
9.3.2.2.4. By User Type
9.3.2.2.5. By Industry Vertical
9.3.3. South Africa Business Intelligence Market Outlook
9.3.3.1. Market Size & Forecast
9.3.3.1.1. By Value
9.3.3.2. Market Share & Forecast
9.3.3.2.1. By Component
9.3.3.2.2. By Deployment Model
9.3.3.2.3. By Functionality
9.3.3.2.4. By User Type
9.3.3.2.5. By Industry Vertical
10. Asia Pacific Business Intelligence Market Outlook
10.1. Market Size & Forecast
10.1.1. By Value
10.2. Market Share & Forecast
10.2.1. By Component
10.2.2. By Deployment Model
10.2.3. By Functionality
10.2.4. By User Type
10.2.5. By Industry Vertical
10.2.6. By Country
10.3. Asia Pacific: Country Analysis
10.3.1. China Business Intelligence Market Outlook
10.3.1.1. Market Size & Forecast
10.3.1.1.1. By Value
10.3.1.2. Market Share & Forecast
10.3.1.2.1. By Component
10.3.1.2.2. By Deployment Model
10.3.1.2.3. By Functionality
10.3.1.2.4. By User Type
10.3.1.2.5. By Industry Vertical
10.3.2. India Business Intelligence Market Outlook
10.3.2.1. Market Size & Forecast
10.3.2.1.1. By Value
10.3.2.2. Market Share & Forecast
10.3.2.2.1. By Component
10.3.2.2.2. By Deployment Model
10.3.2.2.3. By Functionality
10.3.2.2.4. By User Type
10.3.2.2.5. By Industry Vertical
10.3.3. Japan Business Intelligence Market Outlook
10.3.3.1. Market Size & Forecast
10.3.3.1.1. By Value
10.3.3.2. Market Share & Forecast
10.3.3.2.1. By Component
10.3.3.2.2. By Deployment Model
10.3.3.2.3. By Functionality
10.3.3.2.4. By User Type
10.3.3.2.5. By Industry Vertical
10.3.4. South Korea Business Intelligence Market Outlook
10.3.4.1. Market Size & Forecast
10.3.4.1.1. By Value
10.3.4.2. Market Share & Forecast
10.3.4.2.1. By Component
10.3.4.2.2. By Deployment Model
10.3.4.2.3. By Functionality
10.3.4.2.4. By User Type
10.3.4.2.5. By Industry Vertical
10.3.5. Australia Business Intelligence Market Outlook
10.3.5.1. Market Size & Forecast
10.3.5.1.1. By Value
10.3.5.2. Market Share & Forecast
10.3.5.2.1. By Component
10.3.5.2.2. By Deployment Model
10.3.5.2.3. By Functionality
10.3.5.2.4. By User Type
10.3.5.2.5. By Industry Vertical
11. Market Dynamics
11.1. Drivers
11.2. Challenges
12. Market Trends and Developments
13. Company Profiles
13.1. Microsoft Corporation
13.1.1. Business Overview
13.1.2. Key Revenue and Financials
13.1.3. Recent Developments
13.1.4. Key Personnel
13.1.5. Key Product/Services Offered
13.2. Salesforce, Inc.
13.2.1. Business Overview
13.2.2. Key Revenue and Financials
13.2.3. Recent Developments
13.2.4. Key Personnel
13.2.5. Key Product/Services Offered
13.3. SAP SE
13.3.1. Business Overview
13.3.2. Key Revenue and Financials
13.3.3. Recent Developments
13.3.4. Key Personnel
13.3.5. Key Product/Services Offered
13.4. IBM Corporation
13.4.1. Business Overview
13.4.2. Key Revenue and Financials
13.4.3. Recent Developments
13.4.4. Key Personnel
13.4.5. Key Product/Services Offered
13.5. Oracle Corporation
13.5.1. Business Overview
13.5.2. Key Revenue and Financials
13.5.3. Recent Developments
13.5.4. Key Personnel
13.5.5. Key Product/Services Offered
13.6. QlikTech International AB
13.6.1. Business Overview
13.6.2. Key Revenue and Financials
13.6.3. Recent Developments
13.6.4. Key Personnel
13.6.5. Key Product/Services Offered
13.7. SAS Institute Inc.
13.7.1. Business Overview
13.7.2. Key Revenue and Financials
13.7.3. Recent Developments
13.7.4. Key Personnel
13.7.5. Key Product/Services Offered
13.8. Teradata Operations, Inc.
13.8.1. Business Overview
13.8.2. Key Revenue and Financials
13.8.3. Recent Developments
13.8.4. Key Personnel
13.8.5. Key Product/Services Offered
13.9. Domo, Inc.
13.9.1. Business Overview
13.9.2. Key Revenue and Financials
13.9.3. Recent Developments
13.9.4. Key Personnel
13.9.5. Key Product/Services Offered
13.10. ThoughtSpot Inc.
13.10.1. Business Overview
13.10.2. Key Revenue and Financials
13.10.3. Recent Developments
13.10.4. Key Personnel
13.10.5. Key Product/Services Offered
14. Strategic Recommendations
15. About Us & Disclaimer