Data Center Infrastructure Market Forecasts to 2032 – Global Analysis By Component (Hardware, Software and Services), Product, Data Center Type, Tier Type, Enterprise Size, End User and By Geography
Description
According to Stratistics MRC, the Global Predictive Analytics Market is accounted for $24.61 billion in 2025 and is expected to reach $156.95 billion by 2032 growing at a CAGR of 30.3% during the forecast period. Predictive analytics involves applying statistical models, historical data, and machine learning to forecast future trends or events. It enables organizations to interpret data patterns, anticipate outcomes, and make strategic decisions. Commonly used across industries like healthcare, finance, and marketing, predictive analytics supports areas such as demand forecasting, risk management, fraud detection, and customer behavior analysis. By leveraging data insights, it empowers businesses to enhance performance, improve planning accuracy, and achieve better operational and strategic outcomes.
According to the blog, 92% of executives had used cutting-edge digital transformation techniques to improve their consumers' experiences.
Market Dynamics:
Driver:
Increasing demand for data-driven decision-making
The surge in digital transformation initiatives has amplified the need for advanced tools that can convert raw data into actionable insights. Businesses are adopting predictive models to anticipate consumer behavior, optimize supply chains, and reduce operational risks. As competition intensifies, data-driven decision-making is becoming a critical differentiator for market leaders. Improvements in cloud computing and big data platforms are further accelerating adoption. This growing reliance on analytics is positioning predictive solutions as indispensable for modern enterprises.
Restraint:
High implementation costs
Smaller organizations struggle to allocate budgets for advanced platforms and specialized data science teams. Integration with legacy systems adds complexity, increasing both time and financial commitments. High upfront costs can delay adoption, particularly in emerging markets with limited resources. Ongoing expenses for maintenance, upgrades, and training further burden organizations. These financial challenges remain a key restraint, slowing widespread deployment of predictive analytics solutions.
Opportunity:
Integration of AI and machine learning (ML)
Advanced algorithms enable more accurate forecasting, anomaly detection, and personalized recommendations. Industries such as healthcare, finance, and retail are leveraging AI-driven predictive models to enhance decision-making precision. Cloud-based platforms are making these capabilities more accessible, reducing barriers to entry. Continuous innovation in natural language processing and deep learning is expanding the scope of predictive applications. This integration is expected to drive transformative outcomes across multiple sectors, creating significant market opportunities.
Threat:
Data security and privacy concerns
Organizations must comply with stringent privacy regulations such as GDPR and CCPA, which complicate data handling practices. Rising cyberattacks highlight vulnerabilities in analytics platforms, undermining trust among users. Companies are investing heavily in encryption, access controls, and secure cloud environments to mitigate risks. However, balancing innovation with compliance remains a persistent challenge. Without robust safeguards, privacy concerns could hinder adoption and limit market expansion.
Covid-19 Impact:
Organizations used predictive models to forecast demand fluctuations, manage supply chain disruptions, and assess financial risks. Healthcare providers leveraged analytics to track infection trends and optimize resource allocation. Remote work environments further boosted reliance on cloud-based predictive platforms. While some industries faced budget constraints, the crisis underscored the value of data-driven resilience. Post-pandemic strategies now emphasize agility, automation, and predictive insights as core components of recovery planning.
The solutions segment is expected to be the largest during the forecast period
The solutions segment is expected to account for the largest market share during the forecast period, due to its comprehensive offerings across industries. Businesses are increasingly adopting packaged solutions that integrate data management, visualization, and forecasting capabilities. These tools streamline decision-making processes and reduce reliance on manual analysis. Vendors are enhancing solutions with AI-driven features to improve accuracy and usability. The scalability of cloud-based solutions makes them attractive to both large enterprises and SMEs.
The retail & e-commerce segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the retail & e-commerce segment is predicted to witness the highest growth rate. Companies in this sector are using predictive models to forecast demand, personalize marketing, and optimize inventory. The rise of online shopping has intensified competition, driving retailers to leverage analytics for customer retention. Advanced algorithms help identify purchasing patterns and improve recommendation engines. Integration with omnichannel platforms enhances customer experiences and boosts sales performance.
Region with largest share:
During the forecast period, the Asia Pacific region is expected to hold the largest market share. Rapid digitalization across countries like China, India, and Japan is fueling demand for advanced analytics. Governments are investing in smart city initiatives and digital infrastructure, creating fertile ground for adoption. Enterprises in the region are increasingly leveraging predictive tools to enhance competitiveness and efficiency. Strategic collaborations between global vendors and local firms are accelerating market penetration.
Region with highest CAGR:
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR. The region benefits from strong technological leadership and extensive R&D investments. Companies are pioneering innovations in AI-driven analytics, cloud platforms, and real-time forecasting. Regulatory frameworks are supportive, encouraging faster commercialization of advanced solutions. Enterprises are integrating predictive analytics into core operations, from healthcare diagnostics to financial risk management.
Key players in the market
Some of the key players in Predictive Analytics Market include IBM, Google, Microsoft, Amazon Web Services, SAP, HPE, Oracle, FICO, SAS Institute, RapidMiner, Tableau, Alteryx, TIBCO Software, Teradata, and Qlik.
Key Developments:
In November 2025, IBM and Web Summit today unveiled a new global sports-tech competition proposal. The Sports Tech Startup Challenge will spotlight startups using AI to revolutionize sports from athlete performance and stadium operations to fan engagement with regional events planned for Qatar, Vancouver, and Rio, culminating with global winners being selected during Web Summit Lisbon 2026. Participation will be subject to local laws and official rules to be published before each regional competition.
In October 2025, Oracle announced the latest capabilities added to Oracle Database@AWS to better support mission-critical enterprise workloads in the cloud. In addition, customers can now procure Oracle Database@AWS through qualified AWS and Oracle channel partners. This gives customers the flexibility to procure Oracle Database@AWS through their trusted partners and continue to innovate, modernize, and solve complex business problems in the cloud.
Components Covered:
• Solutions
• Services
Deployment Modes Covered:
• On-Premises
• Cloud-Based
• Hybrid
Organization Sizes Covered:
• Large Enterprises
• Small & Medium Enterprises (SMEs)
Technologies Covered:
• Machine Learning
• Statistical Modeling
• Data Mining
• Big Data Analytics
• Natural Language Processing (NLP)
Applications Covered:
• Risk Management & Fraud Detection
• Healthcare & Clinical Decision Support
• Customer & Marketing Analytics
• Human Resource Analytics
• Operations & Supply Chain Optimization
• Financial Analytics
• Sales Forecasting
• Other Applications
End Users Covered:
• Banking, Financial Services & Insurance (BFSI)
• Transportation & Logistics
• Retail & E-commerce
• Government & Defense
• Healthcare & Life Sciences
• Energy & Utilities
• Manufacturing
• Telecom & IT
Regions Covered:
• North America
US
Canada
Mexico
• Europe
Germany
UK
Italy
France
Spain
Rest of Europe
• Asia Pacific
Japan
China
India
Australia
New Zealand
South Korea
Rest of Asia Pacific
• South America
Argentina
Brazil
Chile
Rest of South America
• Middle East & Africa
Saudi Arabia
UAE
Qatar
South Africa
Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances
According to the blog, 92% of executives had used cutting-edge digital transformation techniques to improve their consumers' experiences.
Market Dynamics:
Driver:
Increasing demand for data-driven decision-making
The surge in digital transformation initiatives has amplified the need for advanced tools that can convert raw data into actionable insights. Businesses are adopting predictive models to anticipate consumer behavior, optimize supply chains, and reduce operational risks. As competition intensifies, data-driven decision-making is becoming a critical differentiator for market leaders. Improvements in cloud computing and big data platforms are further accelerating adoption. This growing reliance on analytics is positioning predictive solutions as indispensable for modern enterprises.
Restraint:
High implementation costs
Smaller organizations struggle to allocate budgets for advanced platforms and specialized data science teams. Integration with legacy systems adds complexity, increasing both time and financial commitments. High upfront costs can delay adoption, particularly in emerging markets with limited resources. Ongoing expenses for maintenance, upgrades, and training further burden organizations. These financial challenges remain a key restraint, slowing widespread deployment of predictive analytics solutions.
Opportunity:
Integration of AI and machine learning (ML)
Advanced algorithms enable more accurate forecasting, anomaly detection, and personalized recommendations. Industries such as healthcare, finance, and retail are leveraging AI-driven predictive models to enhance decision-making precision. Cloud-based platforms are making these capabilities more accessible, reducing barriers to entry. Continuous innovation in natural language processing and deep learning is expanding the scope of predictive applications. This integration is expected to drive transformative outcomes across multiple sectors, creating significant market opportunities.
Threat:
Data security and privacy concerns
Organizations must comply with stringent privacy regulations such as GDPR and CCPA, which complicate data handling practices. Rising cyberattacks highlight vulnerabilities in analytics platforms, undermining trust among users. Companies are investing heavily in encryption, access controls, and secure cloud environments to mitigate risks. However, balancing innovation with compliance remains a persistent challenge. Without robust safeguards, privacy concerns could hinder adoption and limit market expansion.
Covid-19 Impact:
Organizations used predictive models to forecast demand fluctuations, manage supply chain disruptions, and assess financial risks. Healthcare providers leveraged analytics to track infection trends and optimize resource allocation. Remote work environments further boosted reliance on cloud-based predictive platforms. While some industries faced budget constraints, the crisis underscored the value of data-driven resilience. Post-pandemic strategies now emphasize agility, automation, and predictive insights as core components of recovery planning.
The solutions segment is expected to be the largest during the forecast period
The solutions segment is expected to account for the largest market share during the forecast period, due to its comprehensive offerings across industries. Businesses are increasingly adopting packaged solutions that integrate data management, visualization, and forecasting capabilities. These tools streamline decision-making processes and reduce reliance on manual analysis. Vendors are enhancing solutions with AI-driven features to improve accuracy and usability. The scalability of cloud-based solutions makes them attractive to both large enterprises and SMEs.
The retail & e-commerce segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the retail & e-commerce segment is predicted to witness the highest growth rate. Companies in this sector are using predictive models to forecast demand, personalize marketing, and optimize inventory. The rise of online shopping has intensified competition, driving retailers to leverage analytics for customer retention. Advanced algorithms help identify purchasing patterns and improve recommendation engines. Integration with omnichannel platforms enhances customer experiences and boosts sales performance.
Region with largest share:
During the forecast period, the Asia Pacific region is expected to hold the largest market share. Rapid digitalization across countries like China, India, and Japan is fueling demand for advanced analytics. Governments are investing in smart city initiatives and digital infrastructure, creating fertile ground for adoption. Enterprises in the region are increasingly leveraging predictive tools to enhance competitiveness and efficiency. Strategic collaborations between global vendors and local firms are accelerating market penetration.
Region with highest CAGR:
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR. The region benefits from strong technological leadership and extensive R&D investments. Companies are pioneering innovations in AI-driven analytics, cloud platforms, and real-time forecasting. Regulatory frameworks are supportive, encouraging faster commercialization of advanced solutions. Enterprises are integrating predictive analytics into core operations, from healthcare diagnostics to financial risk management.
Key players in the market
Some of the key players in Predictive Analytics Market include IBM, Google, Microsoft, Amazon Web Services, SAP, HPE, Oracle, FICO, SAS Institute, RapidMiner, Tableau, Alteryx, TIBCO Software, Teradata, and Qlik.
Key Developments:
In November 2025, IBM and Web Summit today unveiled a new global sports-tech competition proposal. The Sports Tech Startup Challenge will spotlight startups using AI to revolutionize sports from athlete performance and stadium operations to fan engagement with regional events planned for Qatar, Vancouver, and Rio, culminating with global winners being selected during Web Summit Lisbon 2026. Participation will be subject to local laws and official rules to be published before each regional competition.
In October 2025, Oracle announced the latest capabilities added to Oracle Database@AWS to better support mission-critical enterprise workloads in the cloud. In addition, customers can now procure Oracle Database@AWS through qualified AWS and Oracle channel partners. This gives customers the flexibility to procure Oracle Database@AWS through their trusted partners and continue to innovate, modernize, and solve complex business problems in the cloud.
Components Covered:
• Solutions
• Services
Deployment Modes Covered:
• On-Premises
• Cloud-Based
• Hybrid
Organization Sizes Covered:
• Large Enterprises
• Small & Medium Enterprises (SMEs)
Technologies Covered:
• Machine Learning
• Statistical Modeling
• Data Mining
• Big Data Analytics
• Natural Language Processing (NLP)
Applications Covered:
• Risk Management & Fraud Detection
• Healthcare & Clinical Decision Support
• Customer & Marketing Analytics
• Human Resource Analytics
• Operations & Supply Chain Optimization
• Financial Analytics
• Sales Forecasting
• Other Applications
End Users Covered:
• Banking, Financial Services & Insurance (BFSI)
• Transportation & Logistics
• Retail & E-commerce
• Government & Defense
• Healthcare & Life Sciences
• Energy & Utilities
• Manufacturing
• Telecom & IT
Regions Covered:
• North America
US
Canada
Mexico
• Europe
Germany
UK
Italy
France
Spain
Rest of Europe
• Asia Pacific
Japan
China
India
Australia
New Zealand
South Korea
Rest of Asia Pacific
• South America
Argentina
Brazil
Chile
Rest of South America
• Middle East & Africa
Saudi Arabia
UAE
Qatar
South Africa
Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances
Table of Contents
200 Pages
- 1 Executive Summary
- 2 Preface
- 2.1 Abstract
- 2.2 Stake Holders
- 2.3 Research Scope
- 2.4 Research Methodology
- 2.4.1 Data Mining
- 2.4.2 Data Analysis
- 2.4.3 Data Validation
- 2.4.4 Research Approach
- 2.5 Research Sources
- 2.5.1 Primary Research Sources
- 2.5.2 Secondary Research Sources
- 2.5.3 Assumptions
- 3 Market Trend Analysis
- 3.1 Introduction
- 3.2 Drivers
- 3.3 Restraints
- 3.4 Opportunities
- 3.5 Threats
- 3.6 Product Analysis
- 3.7 End User Analysis
- 3.8 Emerging Markets
- 3.9 Impact of Covid-19
- 4 Porters Five Force Analysis
- 4.1 Bargaining power of suppliers
- 4.2 Bargaining power of buyers
- 4.3 Threat of substitutes
- 4.4 Threat of new entrants
- 4.5 Competitive rivalry
- 5 Global Data Center Infrastructure Market, By Component
- 5.1 Introduction
- 5.2 Hardware
- 5.2.1 Power systems
- 5.2.2 Cooling systems
- 5.2.3 Racks & enclosures
- 5.2.4 Networking equipment
- 5.3 Software
- 5.3.1 Data Center Infrastructure Management (DCIM)
- 5.3.2 Monitoring & automation tools
- 5.3.3 Energy optimization software
- 5.4 Services
- 5.4.1 Consulting & design
- 5.4.2 Integration & deployment
- 5.4.3 Maintenance & support
- 6 Global Data Center Infrastructure Market, By Product
- 6.1 Introduction
- 6.2 Power Infrastructure
- 6.2.1 Backup Systems
- 6.2.2 Distribution Units
- 6.3 Cooling Infrastructure
- 6.3.1 Air-based Cooling
- 6.3.2 Liquid Cooling
- 6.4 IT Racks & Enclosures
- 6.5 Networking Equipment
- 6.6 DCIM Solutions
- 7 Global Data Center Infrastructure Market, By Data Center Type
- 7.1 Introduction
- 7.2 Cloud Data Centers
- 7.3 Enterprise Data Centers
- 7.4 Colocation Data Centers
- 7.5 Edge & Micro Data Centers
- 8 Global Data Center Infrastructure Market, By Tier Type
- 8.1 Introduction
- 8.2 Tier 1
- 8.3 Tier 2
- 8.4 Tier 3
- 8.5 Tier 4
- 9 Global Data Center Infrastructure Market, By Enterprise Size
- 9.1 Introduction
- 9.2 Small & Medium Enterprises (SMEs)
- 9.3 Large Enterprises
- 10 Global Data Center Infrastructure Market, By End User
- 10.1 Introduction
- 10.2 IT & Telecom
- 10.3 Healthcare
- 10.4 Banking, Financial Services, Insurance (BFSI)
- 10.5 Retail & E-commerce
- 10.6 Government & Defense
- 10.7 Manufacturing
- 10.8 Energy & Utilities
- 10.9 Other End Users
- 11 Global Data Center Infrastructure Market, By Geography
- 11.1 Introduction
- 11.2 North America
- 11.2.1 US
- 11.2.2 Canada
- 11.2.3 Mexico
- 11.3 Europe
- 11.3.1 Germany
- 11.3.2 UK
- 11.3.3 Italy
- 11.3.4 France
- 11.3.5 Spain
- 11.3.6 Rest of Europe
- 11.4 Asia Pacific
- 11.4.1 Japan
- 11.4.2 China
- 11.4.3 India
- 11.4.4 Australia
- 11.4.5 New Zealand
- 11.4.6 South Korea
- 11.4.7 Rest of Asia Pacific
- 11.5 South America
- 11.5.1 Argentina
- 11.5.2 Brazil
- 11.5.3 Chile
- 11.5.4 Rest of South America
- 11.6 Middle East & Africa
- 11.6.1 Saudi Arabia
- 11.6.2 UAE
- 11.6.3 Qatar
- 11.6.4 South Africa
- 11.6.5 Rest of Middle East & Africa
- 12 Key Developments
- 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
- 12.2 Acquisitions & Mergers
- 12.3 New Product Launch
- 12.4 Expansions
- 12.5 Other Key Strategies
- 13 Company Profiling
- 13.1 Equinix
- 13.2 Advanced Micro Devices (AMD)
- 13.3 Digital Realty
- 13.4 Nvidia
- 13.5 NTT Communications
- 13.6 Huawei Technologies
- 13.7 China Telecom
- 13.8 Hewlett Packard Enterprise (HPE)
- 13.9 Amazon Web Services (AWS)
- 13.10 Dell Technologies
- 13.11 Microsoft Azure
- 13.12 Cisco Systems
- 13.13 Google Cloud
- 13.14 Oracle
- 13.15 IBM
- List of Tables
- Table 1 Global Data Center Infrastructure Market Outlook, By Region (2024-2032) ($MN)
- Table 2 Global Data Center Infrastructure Market Outlook, By Component (2024-2032) ($MN)
- Table 3 Global Data Center Infrastructure Market Outlook, By Hardware (2024-2032) ($MN)
- Table 4 Global Data Center Infrastructure Market Outlook, By Power systems (2024-2032) ($MN)
- Table 5 Global Data Center Infrastructure Market Outlook, By Cooling systems (2024-2032) ($MN)
- Table 6 Global Data Center Infrastructure Market Outlook, By Racks & enclosures (2024-2032) ($MN)
- Table 7 Global Data Center Infrastructure Market Outlook, By Networking equipment (2024-2032) ($MN)
- Table 8 Global Data Center Infrastructure Market Outlook, By Software (2024-2032) ($MN)
- Table 9 Global Data Center Infrastructure Market Outlook, By Data Center Infrastructure Management (DCIM) (2024-2032) ($MN)
- Table 10 Global Data Center Infrastructure Market Outlook, By Monitoring & automation tools (2024-2032) ($MN)
- Table 11 Global Data Center Infrastructure Market Outlook, By Energy optimization software (2024-2032) ($MN)
- Table 12 Global Data Center Infrastructure Market Outlook, By Services (2024-2032) ($MN)
- Table 13 Global Data Center Infrastructure Market Outlook, By Consulting & design (2024-2032) ($MN)
- Table 14 Global Data Center Infrastructure Market Outlook, By Integration & deployment (2024-2032) ($MN)
- Table 15 Global Data Center Infrastructure Market Outlook, By Maintenance & support (2024-2032) ($MN)
- Table 16 Global Data Center Infrastructure Market Outlook, By Product (2024-2032) ($MN)
- Table 17 Global Data Center Infrastructure Market Outlook, By Power Infrastructure (2024-2032) ($MN)
- Table 18 Global Data Center Infrastructure Market Outlook, By Backup Systems (2024-2032) ($MN)
- Table 19 Global Data Center Infrastructure Market Outlook, By Distribution Units (2024-2032) ($MN)
- Table 20 Global Data Center Infrastructure Market Outlook, By Cooling Infrastructure (2024-2032) ($MN)
- Table 21 Global Data Center Infrastructure Market Outlook, By Air-based Cooling (2024-2032) ($MN)
- Table 22 Global Data Center Infrastructure Market Outlook, By Liquid Cooling (2024-2032) ($MN)
- Table 23 Global Data Center Infrastructure Market Outlook, By IT Racks & Enclosures (2024-2032) ($MN)
- Table 24 Global Data Center Infrastructure Market Outlook, By Networking Equipment (2024-2032) ($MN)
- Table 25 Global Data Center Infrastructure Market Outlook, By DCIM Solutions (2024-2032) ($MN)
- Table 26 Global Data Center Infrastructure Market Outlook, By Data Center Type (2024-2032) ($MN)
- Table 27 Global Data Center Infrastructure Market Outlook, By Cloud Data Centers (2024-2032) ($MN)
- Table 28 Global Data Center Infrastructure Market Outlook, By Enterprise Data Centers (2024-2032) ($MN)
- Table 29 Global Data Center Infrastructure Market Outlook, By Colocation Data Centers (2024-2032) ($MN)
- Table 30 Global Data Center Infrastructure Market Outlook, By Edge & Micro Data Centers (2024-2032) ($MN)
- Table 31 Global Data Center Infrastructure Market Outlook, By Tier Type (2024-2032) ($MN)
- Table 32 Global Data Center Infrastructure Market Outlook, By Tier 1 (2024-2032) ($MN)
- Table 33 Global Data Center Infrastructure Market Outlook, By Tier 2 (2024-2032) ($MN)
- Table 34 Global Data Center Infrastructure Market Outlook, By Tier 3 (2024-2032) ($MN)
- Table 35 Global Data Center Infrastructure Market Outlook, By Tier 4 (2024-2032) ($MN)
- Table 36 Global Data Center Infrastructure Market Outlook, By Enterprise Size (2024-2032) ($MN)
- Table 37 Global Data Center Infrastructure Market Outlook, By Small & Medium Enterprises (SMEs) (2024-2032) ($MN)
- Table 38 Global Data Center Infrastructure Market Outlook, By Large Enterprises (2024-2032) ($MN)
- Table 39 Global Data Center Infrastructure Market Outlook, By End User (2024-2032) ($MN)
- Table 40 Global Data Center Infrastructure Market Outlook, By IT & Telecom (2024-2032) ($MN)
- Table 41 Global Data Center Infrastructure Market Outlook, By Healthcare (2024-2032) ($MN)
- Table 42 Global Data Center Infrastructure Market Outlook, By Banking, Financial Services, Insurance (BFSI) (2024-2032) ($MN)
- Table 43 Global Data Center Infrastructure Market Outlook, By Retail & E-commerce (2024-2032) ($MN)
- Table 44 Global Data Center Infrastructure Market Outlook, By Government & Defense (2024-2032) ($MN)
- Table 45 Global Data Center Infrastructure Market Outlook, By Manufacturing (2024-2032) ($MN)
- Table 46 Global Data Center Infrastructure Market Outlook, By Energy & Utilities (2024-2032) ($MN)
- Table 47 Global Data Center Infrastructure Market Outlook, By Other End Users (2024-2032) ($MN)
- Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
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