Self-Service Business Intelligence (BI) Market - Global Industry Size, Share, Trends, Opportunity, and Forecast Segmented by Deployment Model (On-Premises and On-Demand), By Business Function (Finance, Marketing, Sales, Operations and Human Resources (HR)), By Region, and By Competition 2019-2029

  • Industry : ICT
  • Pages : NA
  • Published Date : NA
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Summary

Report Description


Forecast Period

2025-2029

Market Size (2023)

USD 8.01 billion

CAGR (2024-2029)

11.14%

Fastest Growing Segment

On-Premises

Largest Market

North America




Market Overview

Global Self-Service Business Intelligence (BI) Market has valued at USD 8.01 billion in 2023 and is anticipated to project robust growth in the forecast period with a CAGR of 11.14% through 2029. Factors such as increase in air passenger traffic globally, improvement in airport infrastructure in developing nations, and increased adoption of touchscreen, multimedia, and biometric kiosks to enhance passenger experience drive the growth of the market across the globe.

Key Market Drivers

User Empowerment and Accessibility:

The primary catalyst for the growth of self-service BI is the democratization of data. Traditional BI systems often required specialized skills, limiting data access to a select group of individuals. Self-service BI solutions, however, empower a broader user base by providing intuitive interfaces, enabling non-technical users to interact with and derive insights from data. This democratization fosters a data-driven culture within organizations, where decision-makers at all levels can contribute to informed decision-making.

Rise of Data-Driven Decision-Making:

In an era where data is abundant, organizations recognize the need to harness this resource for strategic decision-making. Self-service BI equips users with tools that facilitate real-time analysis, allowing for quicker and more agile decision-making processes. The shift towards data-driven decision-making has become a competitive necessity, and self-service BI platforms are instrumental in facilitating this transition.

Cost Efficiency and Time Savings:

Traditional BI implementations often involved lengthy development cycles and incurred high costs. Self-service BI platforms significantly reduce the time and resources required for data analysis and reporting. Empowering users to create their own reports and dashboards reduces the burden on IT departments and accelerates the overall decision-making process. This cost-effectiveness makes self-service BI a compelling choice for organizations seeking agile and efficient solutions.

Advancements in Data Visualization and Analytics:

The evolution of data visualization and analytics tools has played a pivotal role in driving the adoption of self-service BI. Modern BI platforms offer user-friendly interfaces with drag-and-drop functionalities, allowing users to create visually appealing and insightful reports without the need for coding expertise. This accessibility to advanced analytics has broadened the scope of data exploration and interpretation.

Cloud Computing and Scalability:

The proliferation of cloud computing has been a game-changer for self-service BI. Cloud-based BI solutions provide scalability, flexibility, and accessibility, making it easier for organizations to deploy and manage their BI initiatives. This shift to the cloud not only reduces infrastructure costs but also facilitates seamless collaboration and data sharing across geographically dispersed teams.

Integration with Big Data Technologies:

The advent of big data technologies has expanded the scope of data sources available to organizations. Self-service BI platforms have evolved to integrate seamlessly with diverse data sets, including those from big data repositories. This capability enables users to analyze and derive insights from vast and varied datasets, unlocking new dimensions of business intelligence.

Mobile BI for On-the-Go Decision-Making:

The proliferation of mobile devices has transformed the way business professionals access information. Self-service BI platforms have embraced mobile BI, allowing users to access reports and dashboards on-the-go. This mobility not only enhances user convenience but also ensures that decision-makers have real-time access to critical insights regardless of their location.

 

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Key Market Challenges

Technological Complexity and Integration:

The rapid evolution of technology, while a driver of growth, also poses challenges in terms of complexity and integration. Self-Service Business Intelligence (BI) are becoming more sophisticated with the integration of biometrics, artificial intelligence, and machine learning. Coordinating these technologies seamlessly and ensuring interoperability across different systems and vendors can be a daunting task for airports.

Cybersecurity Concerns:

As Self-Service Business Intelligence (BI) become more interconnected and data-driven, the risk of cybersecurity threats looms large. Protecting sensitive passenger information and ensuring the secure operation of kiosks are paramount. The potential for breaches or malicious attacks poses a significant challenge that the industry must proactively address through robust cybersecurity measures and continuous monitoring.

Maintenance and Reliability:

Self-Service Business Intelligence (BI) operate in a high-traffic environment, making maintenance a critical challenge. Regular wear and tear, exposure to varying environmental conditions, and the need for frequent software updates demand a robust maintenance strategy. Ensuring the reliability of kiosks is essential to prevent disruptions in passenger services and maintain the overall efficiency of airport operations.

Standardization Across Airports:

The lack of standardized processes and interfaces for Self-Service Business Intelligence (BI) across different airports and regions poses a challenge for both vendors and airport authorities. Achieving a level of standardization could enhance interoperability, reduce implementation costs, and streamline processes for passengers. However, achieving consensus on such standards presents a complex task that requires collaboration at an international level.

Regulatory Compliance:

Airports operate within a highly regulated environment, and compliance with industry standards and government regulations is non-negotiable. Self-Service Business Intelligence (BI) must adhere to various regulations related to data protection, accessibility, and aviation security. Navigating this regulatory landscape, which may vary across countries, adds an additional layer of complexity to the deployment and operation of airport kiosks.

User Acceptance and Accessibility:

While Self-Service Business Intelligence (BI) aim to enhance efficiency, their success ultimately relies on user acceptance. Ensuring that kiosks are user-friendly, accessible to passengers with diverse needs, and accommodating different languages and cultural preferences is a challenge. Striking the right balance between technological sophistication and user simplicity is crucial for widespread adoption.

Strategies for Overcoming Challenges:

Collaboration and Industry Standards:

Addressing the challenge of standardization requires collaboration among key stakeholders, including airport authorities, vendors, and regulatory bodies. Establishing industry-wide standards for Self-Service Business Intelligence (BI) can facilitate interoperability, streamline implementation, and foster innovation in a consistent framework.

Robust Cybersecurity Measures:

To tackle cybersecurity concerns, the industry must invest in robust cybersecurity measures, including encryption, secure data storage, and continuous monitoring. Collaborative efforts to share threat intelligence and best practices can enhance the overall cybersecurity posture of airport kiosk systems.

Predictive Maintenance Solutions:

Implementing predictive maintenance solutions can mitigate challenges related to maintenance and reliability. By leveraging data analytics and IoT (Internet of Things) technologies, airports can proactively identify and address potential issues, minimizing downtime and ensuring the continuous operation of airport kiosks.

User-Centric Design and Accessibility:

To enhance user acceptance, Self-Service Business Intelligence (BI) should undergo user testing and feedback processes during their design and development phases. Incorporating features that cater to diverse user needs, including accessibility features for passengers with disabilities, can contribute to a positive user experience and wider adoption.

Regulatory Compliance Monitoring:

Staying abreast of evolving regulations and compliance requirements is essential. Airport authorities and kiosk vendors should work together to ensure that Self-Service Business Intelligence (BI) adhere to the latest standards, and regular audits can be conducted to verify compliance.

Conclusion:

The challenges faced by the global Self-Service Business Intelligence (BI) market are complex but not insurmountable. Addressing these challenges requires a concerted effort from industry stakeholders, including technology providers, airports, regulators, and passengers. By fostering collaboration, embracing industry standards, and investing in innovative solutions, the global Self-Service Business Intelligence (BI) market can continue its evolution, providing passengers with enhanced experiences while overcoming the hurdles that lie ahead.

Key Market Trends

Rising Demand for Self-Service Solutions:

Self-Service Business Intelligence (BI) have gained prominence due to the growing demand for self-service solutions among passengers. These kiosks offer an array of services, including check-in, baggage tagging, and boarding pass printing, empowering travelers to navigate the airport journey independently. This trend not only expedites the passenger process but also reduces operational costs for airports.

Touchless Technology and Biometrics:

The ongoing global focus on hygiene and health has accelerated the adoption of touchless technology in airport kiosks. Biometric authentication, such as facial recognition and fingerprint scanning, is becoming increasingly prevalent, offering a secure and efficient means of identity verification. This not only enhances security measures but also aligns with the contactless expectations of post-pandemic travelers.

Integration of Artificial Intelligence (AI):

Artificial Intelligence is revolutionizing Self-Service Business Intelligence (BI) by providing advanced functionalities. AI-powered virtual assistants assist passengers in real-time, offering information on flights, services, and airport amenities. Moreover, AI algorithms analyze data to optimize kiosk placements, streamline passenger flows, and predict peak times, contributing to a more intelligent and responsive airport environment.

Customization and Multifunctionality:

Modern Self-Service Business Intelligence (BI) are designed to cater to diverse passenger needs. They go beyond the conventional check-in processes, offering services such as rebooking, seat upgrades, and even facilitating retail transactions. This trend reflects the industry's commitment to providing a tailored and seamless travel experience for passengers with varying requirements.

Enhanced User Interface and Accessibility:

The user interface of Self-Service Business Intelligence (BI) has undergone significant improvements, emphasizing user-friendliness and accessibility. Large touchscreens, clear graphics, and multilingual options cater to a global audience, ensuring that passengers from different cultural backgrounds can easily navigate and utilize the kiosk services.

Sustainability and Green Initiatives:

Environmental consciousness has permeated the aviation industry, and Self-Service Business Intelligence (BI) are no exception. Manufacturers are increasingly incorporating sustainable materials, energy-efficient components, and recycling options in kiosk designs. This commitment to eco-friendly solutions aligns with global efforts to reduce the carbon footprint of air travel.

Global Expansion and Emerging Markets:

The demand for Self-Service Business Intelligence (BI) is not limited to established aviation hubs. Emerging markets and regional airports are witnessing increased adoption as they strive to enhance their infrastructure and accommodate growing air traffic. This trend reflects the democratization of advanced airport technologies, making air travel more accessible globally.

Cybersecurity and Data Privacy Concerns:

With the integration of sophisticated technologies, cybersecurity and data privacy have become paramount considerations. Airport authorities and kiosk manufacturers are investing in robust cybersecurity measures to safeguard passenger information and prevent potential breaches. Striking a balance between innovation and security is crucial for the sustained growth of the Self-Service Business Intelligence (BI) market.The Global Self-Service Business Intelligence (BI) Market is undergoing a transformative journey, propelled by technological advancements, changing passenger expectations, and a renewed focus on sustainability. The trends outlined above underscore the industry's commitment to creating a seamless, secure, and user-centric airport experience. As we navigate the skies of the future, Self-Service Business Intelligence (BI) will continue to play a pivotal role in shaping the trajectory of air travel, ensuring that the journey is as remarkable as the destination.

Segmental Insights

Deployment Mode Insights

On-premises solutions often appeal to businesses with stringent security and compliance requirements. Industries such as finance, healthcare, and government may prefer on-premises BI solutions to maintain greater control over their data and ensure compliance with industry regulations.

On-premises deployments allow organizations to have more direct control over their data governance policies. This can be particularly important in industries where data privacy and governance are critical considerations.

On-premises solutions offer organizations a higher degree of customization and control over their BI environment. This can be crucial for businesses with specific requirements or those that want to integrate BI tools seamlessly into their existing infrastructure.

In some cases, on-premises solutions may be preferred for their potential to provide faster performance and lower latency. This is especially relevant for businesses dealing with large datasets and requiring real-time or near-real-time analytics.

Some organizations may have legacy systems in place that are better suited to on-premises solutions. Migrating from traditional infrastructure to cloud-based solutions can be a complex process, and businesses may choose to stick with on-premises solutions until they undergo a comprehensive digital transformation.

It's important to note that the preference for on-premises or cloud-based solutions can vary based on industry trends, technological advancements, and evolving business needs. For the most accurate and up-to-date information regarding the Global Self-Service BI Market in 2023, it's recommended to refer to recent market reports, industry analyses, or consult with experts in the field.  

 

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Regional Insights

North America to gain dominant revenue share during the forecast period. The growing digital transformation is driving the investment in self-service BI tools to understand the market conditions. Also, the presence of prominent number of key market players in U.S. is expected to fuel the country’s growth rate.Europe to gain second position in revenue share. The increasing investments in digital tools by start-ups and SMEs to fuel the demand for self-service analytics. The increasing competition across European countries and to sustain market challenges the businesses are keen in implementing innovative digital solutions.Asia Pacific to witness rapid growth rate during the forecast period. The increasing population in countries such as India and China is creating huge set of structured and unstructured data. Thus, to understand the market trends and customer’s needs, industries are adopting self-service BI tools. With the rapid investment in digitalization across industries, India is expected to gain rapid CAGR.

Recent Developments

June 2023: ThoughtSpot Inc. announced the acquisition of BI platform provider, Mode Analytics, to boost the capabilities of data teams and the ecosystem. Together, the companies can offer quick self-service analytics for all types of use cases.

March 2023: AtScale announced collaboration with Snowflake Ready Technology Validation Partner to boost business intelligence and analytics with higher performance. The integration includes self-service analytics capabilities of consumer interaction with live data.

February 2023: Omni Analytics announced the commercial availability of its next-generation BI platform with self-service tools and fully governed capabilities. The company aims to offer growing enterprises needs through its services, with cost-effective and higher performance capabilities.

May 2022: Snowflake Inc. announced partnership with analytics automation company, Savant Labs, to extract operational insights using self-service analytics. As per the companies this is helping in reducing engineers’ workload and offers quick insights locked across data sources.

August 2021: Zoho Corporation launched an AI-driven business intelligence platform to boost enterprises with augmented analytics and self-service data preparation. The company is helping businesses with easily managing and creating data pipeline by integrating with Zoho DataPrep tools.

Key Market Players

  • Cisco Systems, Inc. (U.S.)
  • IBM Corporation (U.S.)
  • Microsoft (U.S.)
  • Oracle (U.S.)
  • SAP (Germany)
  • MapR Technologies, Inc. (U.S.)
  • RapidMiner, Inc. (U.S.)
  • Birst, Inc. (U.S.)
  • ALTERYX, INC. (U.S.)
  • Zoho Corporation Pvt. Ltd. (India)

By Component

By Deployment Model

By Business Function

By Region

Hardware

Software

Services

Automated Passport Control

Common-use Self Service (CUSS) Kiosk

Information Kiosk

Baggage Check-In Kiosk

Ticketing Kiosk

Others

Small

Medium

Large

North America

Europe

Asia Pacific

South America

Middle East & Africa

 

Report Scope:

In this report, the Global Self-Service Business Intelligence (BI) Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

  • Self-Service Business Intelligence (BI) Market, By Component:

o   Hardware

o   Software

o   Services

  • Self-Service Business Intelligence (BI) Market, By Deployment Model:

o   Automated Passport Control

o   Common-use Self Service (CUSS) Kiosk

o   Information Kiosk

o   Baggage Check-In Kiosk

o   Ticketing Kiosk

o   Others

  • Self-Service Business Intelligence (BI) Market, By Business Function

o   Small

o   Medium

o   Large

  • Self-Service Business Intelligence (BI) Market, By Region:

o   North America

§  United States

§  Canada

§  Mexico

o   Europe

§  France

§  United Kingdom

§  Italy

§  Germany

§  Spain

§  Netherlands

§  Belgium

o   Asia-Pacific

§  China

§  India

§  Japan

§  Australia

§  South Korea

§  Thailand

§  Malaysia

o   South America

§  Brazil

§  Argentina

§  Colombia

§  Chile

o   Middle East & Africa

§  South Africa

§  Saudi Arabia

§  UAE

§  Turkey

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Self-Service Business Intelligence (BI) Market.

Available Customizations:

Global Self-Service Business Intelligence (BI) 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).

Global Self-Service Business Intelligence (BI) Market is an upcoming report to be released soon. If you wish an early delivery of this report or want to confirm the date of release, please contact us at [email protected]

Table of content

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.    Objective of the Study

2.2.    Baseline Methodology

2.3.    Formulation of the Scope

2.4.    Assumptions and Limitations

2.5.    Sources of Research

2.5.1.Secondary Research

2.5.2.Primary Research

2.6.    Approach for the Market Study

2.6.1.The Bottom-Up Approach

2.6.2.The Top-Down Approach

2.7.    Methodology Followed for Calculation of Market Size & Market Shares

2.8.    Forecasting Methodology

2.8.1.Data Triangulation & Validation

3.         Executive Summary

4.         Impact of COVID-19 on Global Self-Service Business Intelligence (BI) Market

5.         Voice of Customer

6.         Global Self-Service Business Intelligence (BI) Market Overview

7.         Global Self-Service Business Intelligence (BI) Market Outlook

7.1.    Market Size & Forecast

7.1.1.By Value

7.2.    Market Share & Forecast

7.2.1.By Type (Software and Services)

7.2.2.By Deployment Model (On-Premises and On-Demand)

1.1.1.By Business Function (Finance, Marketing, Sales, Operations and Human Resources (HR))

1.1.2.By Region

1.2.    By Company (2023)

1.3.    Market Map

2.         North America Self-Service Business Intelligence (BI) Market Outlook

2.1.    Market Size & Forecast

2.1.1.By Value

2.2.    Market Share & Forecast

2.2.1.By Type

2.2.2.By Deployment Model

2.2.3.By Business Function

2.2.4.By Country

2.3.    North America: Country Analysis

2.3.1.United States Self-Service Business Intelligence (BI) Market Outlook

2.3.1.1.      Market Size & Forecast

2.3.1.1.1.    By Value

2.3.1.2.      Market Share & Forecast

2.3.1.2.1.               By Type

2.3.1.2.2.               By Deployment Model

2.3.1.2.3.               By Business Function

2.3.2.Canada Self-Service Business Intelligence (BI) Market Outlook

2.3.2.1.      Market Size & Forecast

2.3.2.1.1.    By Value

2.3.2.2.      Market Share & Forecast

2.3.2.2.1.               By Type

2.3.2.2.2.               By Deployment Model

2.3.2.2.3.               By Business Function

2.3.3.Mexico Self-Service Business Intelligence (BI) Market Outlook

2.3.3.1.      Market Size & Forecast

2.3.3.1.1.    By Value

2.3.3.2.      Market Share & Forecast

2.3.3.2.1.               By Type

2.3.3.2.2.               By Deployment Model

2.3.3.2.3.               By Business Function

3.         Europe Self-Service Business Intelligence (BI) Market Outlook

3.1.    Market Size & Forecast

3.1.1.By Value

3.2.    Market Share & Forecast

3.2.1.By Type

3.2.2.By Deployment Model

3.2.3.By Business Function

3.2.4.By Country

3.3.    Europe: Country Analysis

3.3.1.Germany Self-Service Business Intelligence (BI) Market Outlook

3.3.1.1.      Market Size & Forecast

3.3.1.1.1.    By Value

3.3.1.2.      Market Share & Forecast

3.3.1.2.1.               By Type

3.3.1.2.2.               By Deployment Model

3.3.1.2.3.               By Business Function

3.3.2.France Self-Service Business Intelligence (BI) Market Outlook

3.3.2.1.      Market Size & Forecast

3.3.2.1.1.    By Value

3.3.2.2.      Market Share & Forecast

3.3.2.2.1.               By Type

3.3.2.2.2.               By Deployment Model

3.3.2.2.3.               By Business Function

3.3.3.United Kingdom Self-Service Business Intelligence (BI) Market Outlook

3.3.3.1.      Market Size & Forecast

3.3.3.1.1.    By Value

3.3.3.2.      Market Share & Forecast

3.3.3.2.1.               By Type

3.3.3.2.2.               By Deployment Model

3.3.3.2.3.               By Business Function

3.3.4.Italy Self-Service Business Intelligence (BI) Market Outlook

3.3.4.1.      Market Size & Forecast

3.3.4.1.1.    By Value

3.3.4.2.      Market Share & Forecast

3.3.4.2.1.               By Type

3.3.4.2.2.               By Deployment Model

3.3.4.2.3.               By Business Function

3.3.5.Spain Self-Service Business Intelligence (BI) Market Outlook

3.3.5.1.      Market Size & Forecast

3.3.5.1.1.    By Value

3.3.5.2.      Market Share & Forecast

3.3.5.2.1.               By Type

3.3.5.2.2.               By Deployment Model

3.3.5.2.3.               By Business Function

3.3.6.Netherlands Self-Service Business Intelligence (BI) Market Outlook

3.3.6.1.      Market Size & Forecast

3.3.6.1.1.    By Value

3.3.6.2.      Market Share & Forecast

3.3.6.2.1.               By Type

3.3.6.2.2.               By Deployment Model

3.3.6.2.3.               By Business Function

3.3.7.Belgium Self-Service Business Intelligence (BI) Market Outlook

3.3.7.1.      Market Size & Forecast

3.3.7.1.1.    By Value

3.3.7.2.      Market Share & Forecast

3.3.7.2.1.               By Type

3.3.7.2.2.               By Deployment Model

3.3.7.2.3.               By Business Function

4.         South America Self-Service Business Intelligence (BI) Market Outlook

4.1.    Market Size & Forecast

4.1.1.By Value

4.2.    Market Share & Forecast

4.2.1.By Type

4.2.2.By Deployment Model

4.2.3.By Business Function

4.2.4.By Country

4.3.    South America: Country Analysis

4.3.1.Brazil Self-Service Business Intelligence (BI) Market Outlook

4.3.1.1.      Market Size & Forecast

4.3.1.1.1.    By Value

4.3.1.2.      Market Share & Forecast

4.3.1.2.1.               By Type

4.3.1.2.2.               By Deployment Model

4.3.1.2.3.               By Business Function

4.3.2.Colombia Self-Service Business Intelligence (BI) Market Outlook

4.3.2.1.      Market Size & Forecast

4.3.2.1.1.    By Value

4.3.2.2.      Market Share & Forecast

4.3.2.2.1.               By Type

4.3.2.2.2.               By Deployment Model

4.3.2.2.3.               By Business Function

4.3.3.Argentina Self-Service Business Intelligence (BI) Market Outlook

4.3.3.1.      Market Size & Forecast

4.3.3.1.1.    By Value

4.3.3.2.      Market Share & Forecast

4.3.3.2.1.               By Type

4.3.3.2.2.               By Deployment Model

4.3.3.2.3.               By Business Function

4.3.4.Chile Self-Service Business Intelligence (BI) Market Outlook

4.3.4.1.      Market Size & Forecast

4.3.4.1.1.    By Value

4.3.4.2.      Market Share & Forecast

4.3.4.2.1.               By Type

4.3.4.2.2.               By Deployment Model

4.3.4.2.3.               By Business Function

5.         Middle East & Africa Self-Service Business Intelligence (BI) Market Outlook

5.1.    Market Size & Forecast

5.1.1.By Value

5.2.    Market Share & Forecast

5.2.1.By Type

5.2.2.By Deployment Model

5.2.3.By Business Function

5.2.4.By Country

5.3.    Middle East & Africa: Country Analysis

5.3.1.Saudi Arabia Self-Service Business Intelligence (BI) Market Outlook

5.3.1.1.      Market Size & Forecast

5.3.1.1.1.    By Value

5.3.1.2.      Market Share & Forecast

5.3.1.2.1.               By Type

5.3.1.2.2.               By Deployment Model

5.3.1.2.3.               By Business Function

5.3.2.UAE Self-Service Business Intelligence (BI) Market Outlook

5.3.2.1.      Market Size & Forecast

5.3.2.1.1.    By Value

5.3.2.2.      Market Share & Forecast

5.3.2.2.1.               By Type

5.3.2.2.2.               By Deployment Model

5.3.2.2.3.               By Business Function

5.3.3.South Africa Self-Service Business Intelligence (BI) Market Outlook

5.3.3.1.      Market Size & Forecast

5.3.3.1.1.    By Value

5.3.3.2.      Market Share & Forecast

5.3.3.2.1.               By Type

5.3.3.2.2.               By Deployment Model

5.3.3.2.3.               By Business Function

5.3.4.Turkey Self-Service Business Intelligence (BI) Market Outlook

5.3.4.1.      Market Size & Forecast

5.3.4.1.1.    By Value

5.3.4.2.      Market Share & Forecast

5.3.4.2.1.               By Type

5.3.4.2.2.               By Deployment Model

5.3.4.2.3.               By Business Function

6.         Asia Pacific Self-Service Business Intelligence (BI) Market Outlook

6.1.    Market Size & Forecast

6.1.1.By Type

6.1.2.By Deployment Model

6.1.3.By Business Function

6.1.4.By Country

6.2.    Asia-Pacific: Country Analysis

6.2.1.China Self-Service Business Intelligence (BI) Market Outlook

6.2.1.1.      Market Size & Forecast

6.2.1.1.1.    By Value

6.2.1.2.      Market Share & Forecast

6.2.1.2.1.               By Type

6.2.1.2.2.               By Deployment Model

6.2.1.2.3.               By Business Function

6.2.2.India Self-Service Business Intelligence (BI) Market Outlook

6.2.2.1.      Market Size & Forecast

6.2.2.1.1.    By Value

6.2.2.2.      Market Share & Forecast

6.2.2.2.1.               By Type

6.2.2.2.2.               By Deployment Model

6.2.2.2.3.               By Business Function

6.2.3.Japan Self-Service Business Intelligence (BI) Market Outlook

6.2.3.1.      Market Size & Forecast

6.2.3.1.1.    By Value

6.2.3.2.      Market Share & Forecast

6.2.3.2.1.               By Type

6.2.3.2.2.               By Deployment Model

6.2.3.2.3.               By Business Function

6.2.4.South Korea Self-Service Business Intelligence (BI) Market Outlook

6.2.4.1.      Market Size & Forecast

6.2.4.1.1.    By Value

6.2.4.2.      Market Share & Forecast

6.2.4.2.1.               By Type

6.2.4.2.2.               By Deployment Model

6.2.4.2.3.               By Business Function

6.2.5.Australia Self-Service Business Intelligence (BI) Market Outlook

6.2.5.1.      Market Size & Forecast

6.2.5.1.1.    By Value

6.2.5.2.      Market Share & Forecast

6.2.5.2.1.               By Type

6.2.5.2.2.               By Deployment Model

6.2.5.2.3.               By Business Function

6.2.6.Thailand Self-Service Business Intelligence (BI) Market Outlook

6.2.6.1.      Market Size & Forecast

6.2.6.1.1.    By Value

6.2.6.2.      Market Share & Forecast

6.2.6.2.1.               By Type

6.2.6.2.2.               By Deployment Model

6.2.6.2.3.               By Business Function

6.2.7.Malaysia Self-Service Business Intelligence (BI) Market Outlook

6.2.7.1.      Market Size & Forecast

6.2.7.1.1.    By Value

6.2.7.2.      Market Share & Forecast

6.2.7.2.1.               By Type

6.2.7.2.2.               By Deployment Model

6.2.7.2.3.               By Business Function

7.         Market Dynamics

7.1.    Drivers

7.2.    Challenges

8.         Market Trends and Developments

9.         Company Profiles

15.1.  Materna IPS GmbH.

15.1.1.     Business Overview

15.1.2.     Key Revenue and Financials  

15.1.3.     Recent Developments

15.1.4.     Key Personnel/Key Contact Person

15.1.5.     Key Product/Services Offered

15.2.  Collins Aerospace.

15.2.1.     Business Overview

15.2.2.     Key Revenue and Financials  

15.2.3.     Recent Developments

15.2.4.     Key Personnel/Key Contact Person

15.2.5.     Key Product/Services Offered

15.3.  KIOSK Information Systems, Inc.

15.3.1.     Business Overview

15.3.2.     Key Revenue and Financials  

15.3.3.     Recent Developments

15.3.4.     Key Personnel/Key Contact Person

15.3.5.     Key Product/Services Offered

15.4.  Amadeus IT Group SA.

15.4.1.     Business Overview

15.4.2.     Key Revenue and Financials  

15.4.3.     Recent Developments

15.4.4.     Key Personnel/Key Contact Person

15.4.5.     Key Product/Services Offered

15.5.  IER.

15.5.1.     Business Overview

15.5.2.     Key Revenue and Financials  

15.5.3.     Recent Developments

15.5.4.     Key Personnel/Key Contact Person

15.5.5.     Key Product/Services Offered

15.6.  Thales Group.

15.6.1.     Business Overview

15.6.2.     Key Revenue and Financials  

15.6.3.     Recent Developments

15.6.4.     Key Personnel/Key Contact Person

15.6.5.     Key Product/Services Offered

15.7.  SITA .

15.7.1.     Business Overview

15.7.2.     Key Revenue and Financials  

15.7.3.     Recent Developments

15.7.4.     Key Personnel/Key Contact Person

15.7.5.     Key Product/Services Offered

16.      Strategic Recommendations

17.  About Us & Disclaimer

Figures and Tables

Frequently asked questions

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The market size of the Global Self-Service Business Intelligence (BI) Market was USD 8.01 billion in 2023.

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Which was the dominant segment in the Global Self-Service Business Intelligence (BI) Market in 2023?

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North America dominated the market in 2023.

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The rising emergence of cloud computing technologies has revolutionized the landscape of Business Intelligence (BI) in recent years. Cloud computing has fundamentally transformed how organizations access, manage, and leverage their data, offering unprecedented scalability, flexibility, and cost-effectiveness. In the realm of BI, the cloud has become a catalyst for innovation, enabling businesses to harness the power of data-driven decision-making in ways that were once inconceivable.

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