예측 분석 시장 : 시장 규모, 점유율 및 성장률, 산업 분석 - 유형별, 용도별, 지역별 인사이트 및 예측(2026-2034년)
Predictive Analytics Market Size, Share, Growth and Global Industry Analysis By Type & Application, Regional Insights and Forecast to 2026-2034
상품코드:1930246
리서치사:Fortune Business Insights Pvt. Ltd.
발행일:2026년 01월
페이지 정보:영문 160 Pages
라이선스 & 가격 (부가세 별도)
한글목차
예측 분석 시장의 성장 동인
세계 예측 분석 시장은 기업들이 데이터 기반 의사결정 전략을 점점 더 많이 채택함에 따라 큰 주목을 받고 있습니다. 최근 보고서에 따르면, 2025년 시장 규모는 22억 2,200만 달러로 평가되었고, 2026년에는 275억 6,000만 달러로 성장하여 2034년까지 1,166억 5,000만 달러에 달할 것으로 예상되며, 예측 기간 동안 19.8%의 연평균 복합 성장률(CAGR)을 나타낼 것으로 예측됩니다. 2025년에는 북미가 38.7%의 점유율로 시장을 주도할 것으로 예상되며, 이는 북미의 산업 전반에 걸친 첨단 기술 및 데이터 분석 솔루션 도입이 활발하게 이루어지고 있음을 반영합니다.
예측 분석 소프트웨어는 과거 데이터와 실시간 데이터를 활용하여 미래의 트렌드와 결과를 예측합니다. 통계 모델, 머신러닝, AI 알고리즘을 활용하여 데이터 내 패턴과 연관성을 파악하여 기업이 정보에 입각한 의사결정을 내릴 수 있도록 돕습니다. 이 기술은 금융, 마케팅, 의료, 제조, 소매, BFSI(은행, 금융, 보험), 통신 산업 등 다양한 분야에 적용되어 조직의 프로세스 최적화, 업무 효율성 향상, 경쟁 우위 확보에 기여하고 있습니다.
시장 동향
시장의 중요한 트렌드 중 하나는 예측 분석과 기존 비즈니스 인텔리전스(BI) 플랫폼의 통합입니다. 예측 모델링과 과거 BI 인사이트를 결합하여 조직은 과거, 현재, 미래의 트렌드를 종합적으로 파악할 수 있습니다. 이 통합을 통해 실시간 예측, 미래지향적 의사결정, 비즈니스 성과 개선이 가능해집니다. 향상된 시각화 기능과 사용자 친화적인 인터페이스를 통해 애널리스트와 비즈니스 사용자 모두 원활하게 실행 가능한 인사이트에 접근할 수 있어 기업 전반 시장 도입을 촉진하고 있습니다.
시장 성장 동인
데이터 기반 의사결정에 대한 수요 증가: 기업들은 시장 변화, 고객 선호도, 운영상의 문제를 예측하기 위해 예측 분석을 점점 더 많이 활용하고 있습니다. 예를 들어, Keboola의 조사에 따르면, 비즈니스 전문가의 90%가 디지털 전환을 추진하는 데 있어 데이터 분석의 역할을 인식하고 있다고 합니다.
AI 및 IoT와의 통합: 예측 분석을 AI 및 IoT와 결합하여 예측 정확도, 업무 효율성, 자동화를 향상시킬 수 있습니다.
중소기업의 도입: 아시아태평양, 중동 및 아프리카, 남미 등 지역의 중소기업들은 경쟁력 강화와 제품 제공 개선을 위해 점차 예측 분석을 도입하고 있습니다.
억제요인
높은 성장 잠재력에도 불구하고, 높은 도입 비용과 데이터 품질 문제가 시장 확대를 제한할 수 있습니다. 소규모 조직은 예산의 제약에 직면하는 경우가 많으며, 예측 분석 시스템을 효과적으로 도입하고 유지하기 위해서는 숙련된 인력이 필요합니다. 또한, 데이터의 정확성, 일관성, 접근성 문제는 인사이트의 신뢰성을 떨어뜨리고 의사결정에 영향을 미치며 도입을 저해하는 요인으로 작용합니다.
시장 세분화
구축별: 시장은 클라우드 기반과 On-Premise형으로 구분됩니다. 2026년에는 클라우드 부문이 79.11%의 점유율을 차지할 것으로 예상되며, 모든 규모의 조직에서 확장성, 유연성, 비용 효율성, 접근성 등이 견인 요인으로 작용할 것으로 보입니다.
기업 규모별: 2026년 대기업이 61.69%의 점유율로 시장을 주도했습니다. 예측 분석을 통해 업무 최적화, 의사결정 개선, 경쟁 우위 확보가 가능하기 때문입니다. 중소기업(SME)은 AI 도입 증가와 업무 효율성 향상 필요성으로 인해 꾸준한 성장이 예상됩니다.
용도별: 시장 세분화에서는 수요 예측, 금융 리스크 예측, 가격 개인화, 예지보전, 기타로 구분됩니다. 예지보전 부문이 가장 큰 비중을 차지하며, 산업 설비 신뢰성 최적화, 비용 절감, 업무 효율성 향상을 실현합니다. 금융 리스크 예측은 리스크 평가 및 컴플라이언스의 중요성 때문에 가장 높은 CAGR로 성장할 것으로 예측됩니다.
최종 사용자별: BFSI(은행, 금융, 보험) 부문은 리스크 관리 개선, 규제 준수, 업무 효율성 향상에 힘입어 2026년 18.15%의 점유율을 차지하며 시장을 주도할 것으로 예측됩니다. 의료 부문은 환자 치료, 진단, 업무 계획에서 예측 분석의 활용으로 인해 가장 높은 CAGR을 나타낼 것으로 예측됩니다.
지역별 인사이트
북미: 미국과 캐나다의 고급 분석 기술 채택을 배경으로 2025년 86억 1,000만 달러, 2026년 106억 6,000만 달러로 시장을 견인할 것으로 예측됩니다. 미국 시장은 2026년 71억 6,000만 달러에 달할 것으로 예측됩니다.
아시아태평양: 가장 높은 CAGR로 성장할 것으로 예상되며, 2026년까지 일본이 13억 1,000만 달러, 중국이 21억 6,000만 달러, 인도가 12억 1,000만 달러에 달할 것으로 예측됩니다.
유럽: 데이터 양 증가와 분석 기술의 이점에 대한 인식이 높아지면서 꾸준한 성장이 예상됩니다. 2026년에는 영국이 18억 달러, 독일이 16억 8,000만 달러에 달할 것으로 예측됩니다.
중동, 아프리카 및 남미: 현지 스타트업의 부상, 기술 도입의 진전, 주요 시장 기업의 사업 확대로 인해 완만한 성장이 예상됩니다.
주요 산업 기업
주요 기업들은 시장 지위 강화를 위해 제품 혁신, 제휴, 인수, 확장 전략에 집중하고 있습니다. 주요 기업은 다음과 같습니다.
SAP SE, IBM Corporation, TIBCO Software, Amazon Web Services, Alteryx, Cloudera, SAS Institute, FICO, Accenture, AVEVA Group plc 등이 있습니다.
목차
제1장 서론
제2장 주요 요약
제3장 시장 역학
제4장 경쟁 구도
제5장 세계 예측 분석 시장 규모 추정·예측, 부문별, 2021년-2034년
제6장 북미 예측 분석 시장 규모 추정·예측, 부문별, 2021년-2034년
제7장 남미 예측 분석 시장 규모 추정·예측, 부문별, 2021년-2034년
제8장 유럽 예측 분석 시장 규모 추정·예측, 부문별, 2021년-2034년
제9장 중동 및 아프리카 예측 분석 시장 규모 추정·예측, 부문별, 2021년-2034년
제10장 아시아태평양 예측 분석 시장 규모 추정·예측, 부문별, 2021년-2034년
제11장 주요 10개사 기업 개요
제12장 주요 포인트
LSH
영문 목차
영문목차
Growth Factors of predictive analytics Market
The global predictive analytics market has gained significant traction as businesses increasingly adopt data-driven decision-making strategies. According to recent reports, the market was valued at USD 22.22 billion in 2025, expected to grow to USD 27.56 billion in 2026, and is projected to reach USD 116.65 billion by 2034, exhibiting a CAGR of 19.8% during the forecast period. In 2025, North America dominated the market with a 38.7% share, reflecting the region's strong adoption of advanced technologies and data analytics solutions across industries.
Predictive analytics software uses historical and real-time data to forecast future trends and outcomes. By leveraging statistical models, machine learning, and AI algorithms, the software identifies patterns and relationships within data, enabling businesses to make informed decisions. This technology is widely applied across finance, marketing, healthcare, manufacturing, retail, BFSI, and telecom industries, helping organizations optimize processes, enhance operational efficiency, and gain a competitive edge.
Market Trends
A significant trend in the market is the integration of predictive analytics with traditional Business Intelligence (BI) platforms. By combining predictive modeling with historical BI insights, organizations gain a comprehensive understanding of past, present, and future trends. This integration enables real-time predictions, proactive decision-making, and improved business performance. Enhanced visualization and user-friendly interfaces empower both analysts and business users to access actionable insights seamlessly, thereby driving market adoption across enterprises.
Market Growth Factors
Rising demand for data-driven decision-making: Companies are increasingly leveraging predictive analytics to anticipate market shifts, customer preferences, and operational challenges. For instance, according to Keboola, 90% of business professionals acknowledge the role of data analytics in driving digital transformation initiatives.
Integration with AI and IoT: Combining predictive analytics with AI and IoT enhances forecasting accuracy, operational efficiency, and automation.
SME adoption: Small and medium enterprises in regions like Asia Pacific, Middle East & Africa, and South America are gradually adopting predictive analytics to enhance competitiveness and improve product offerings.
Restraining Factors
Despite the strong growth potential, high implementation costs and data quality challenges may limit market expansion. Smaller organizations often face budget constraints and require skilled personnel to deploy and maintain predictive analytics systems effectively. In addition, poor data accuracy, consistency, and accessibility can reduce the reliability of insights, impacting decision-making and restraining adoption.
Market Segmentation
By Deployment: The market is divided into cloud and on-premise solutions. The cloud segment dominated with 79.11% share in 2026, driven by scalability, flexibility, cost efficiency, and accessibility for organizations of all sizes.
By Enterprise Type: Large enterprises dominated the market with a 61.69% share in 2026, as predictive analytics allows them to optimize operations, improve decision-making, and gain a competitive advantage. SMEs are projected to grow steadily due to increasing AI adoption and the need to enhance operational efficiency.
By Application: The market is segmented into demand forecasting, financial risk forecasting, pricing personalization, predictive maintenance, and others. The predictive maintenance segment holds the largest share, enabling industries to optimize equipment reliability, reduce costs, and improve operational efficiency. Financial risk forecasting is expected to grow at the highest CAGR due to its importance in risk assessment and compliance.
By End-User: BFSI dominates with 18.15% share in 2026, benefiting from improved risk management, regulatory compliance, and operational efficiency. The healthcare segment is expected to witness the highest CAGR, leveraging predictive analytics for patient care, diagnostics, and operational planning.
Regional Insights
North America: Dominated with USD 8.61 billion in 2025 and USD 10.66 billion in 2026, driven by adoption of advanced analytics in the U.S. and Canada. The U.S. market is projected to reach USD 7.16 billion in 2026.
Asia Pacific: Expected to grow at the highest CAGR, with Japan reaching USD 1.31 billion, China USD 2.16 billion, and India USD 1.21 billion by 2026.
Europe: Steady growth with UK at USD 1.80 billion and Germany at USD 1.68 billion in 2026, driven by increased data volumes and awareness of analytics benefits.
Middle East & Africa and South America: Moderate growth supported by local startups, technology adoption, and expansion of key market players.
Key Industry Players
Major players focus on product innovation, partnerships, acquisitions, and expansion strategies to strengthen market position. Key companies include:
SAP SE, IBM Corporation, TIBCO Software, Amazon Web Services, Alteryx, Cloudera, SAS Institute, FICO, Accenture, AVEVA Group plc.
Recent Developments:
Feb 2024: Wipro launched Enterprise AI-Ready Platform, integrating predictive analytics for dynamic workload management.
June 2023: Accenture acquired Nextira to enhance predictive analytics solutions for cloud-native applications.
May 2023: Teradata and FICO introduced integrated analytics solutions for real-time payments fraud and supply chain optimization.
Feb 2023: AVEVA introduced predictive analytics software for industrial asset monitoring, improving performance and reliability.
Conclusion
The predictive analytics market, valued at USD 22.22 billion in 2025 and expected to reach USD 116.65 billion by 2034, is experiencing rapid growth driven by data-driven decision-making, AI and IoT integration, and cloud-based solutions. North America leads in market share, while Asia Pacific demonstrates the highest growth potential. Despite challenges such as high costs and data accuracy issues, predictive analytics continues to transform industries including BFSI, healthcare, telecom, and manufacturing, enhancing operational efficiency, reducing risks, and supporting strategic business growth globally.
Segmentation
By Deployment
Cloud
On-premise
By Enterprise Type
Large Enterprises
Small and Medium Enterprises (SMEs)
By Application
Demand Forecasting
Financial Risk Forecasting
Pricing Personalization
Predictive Maintenance
Others (Churn Prevention)
By End-user
BFSI
Automotive
Telecom/Media
Healthcare
Life Sciences
Retail
Energy & Utility
Government
Others (Manufacturing, Education)
By Region
North America (By Deployment, By Enterprise Type, By Application, By End-user, and By Country)
U.S. (By End-user)
Canada (By End-user)
Mexico (By End-user)
South America (By Deployment, By Enterprise Type, By Application, By End-user, and By Country)
Brazil (By End-user)
Argentina (By End-user)
Rest of South America
Europe (By Deployment, By Enterprise Type, By Application, By End-user, and By Country)
U.K. (By End-user)
Germany (By End-user)
France (By End-user)
Italy (By End-user)
Spain (By End-user)
Russia (By End-user)
Benelux (By End-user)
Nordics (By End-user)
Rest of Europe
Middle East & Africa (By Deployment, By Enterprise Type, By Application, By End-user, and By Country)Turkey (By End-user)
Israel (By End-user)
GCC (By End-user)
North Africa (By End-user)
South Africa (By End-user)
Rest of the Middle East & Africa
Asia Pacific (By Deployment, By Enterprise Type, By Application, By End-user, and By Country)
China (By End-user)
Japan (By End-user)
India (By End-user)
South Korea (By End-user)
ASEAN (By End-user)
Oceania (By End-user)
Rest of Asia Pacific
Table of Content
1. Introduction
1.1. Definition, By Segment
1.2. Research Methodology/Approach
1.3. Data Sources
2. Executive Summary
3. Market Dynamics
3.1. Macro and Micro Economic Indicators
3.2. Drivers, Restraints, Opportunities and Trends
4. Competition Landscape
4.1. Business Strategies Adopted by Key Players
4.2. Consolidated SWOT Analysis of Key Players
4.3. Global Predictive Analytics Key Players Market Share/Ranking, 2025
5. Global Predictive Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034
5.1. Key Findings
5.2. By Deployment (USD)
5.2.1. Cloud
5.2.2. On-premise
5.3. By Enterprise Type (USD)
5.3.1. Large Enterprises
5.3.2. Small and Medium Enterprises (SMEs)
5.4. By Application (USD)
5.4.1. Demand Forecasting
5.4.2. Financial Risk Forecasting
5.4.3. Pricing Personalization
5.4.4. Predictive Maintenance
5.4.5. Others (Churn Prevention, etc.)
5.5. By End-user (USD)
5.5.1. BFSI
5.5.2. Automotive
5.5.3. Telecom/Media
5.5.4. Healthcare
5.5.5. Life Sciences
5.5.6. Retail
5.5.7. Energy & Utility
5.5.8. Government
5.5.9. Others (Manufacturing, Education, etc.)
5.6. By Region (USD)
5.6.1. North America
5.6.2. South America
5.6.3. Europe
5.6.4. Middle East & Africa
5.6.5. Asia Pacific
6. North America Predictive Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034
6.1. Key Findings
6.2. By Deployment (USD)
6.2.1. Cloud
6.2.2. On-premise
6.3. By Enterprise Type (USD)
6.3.1. Large Enterprises
6.3.2. Small and Medium Enterprises (SMEs)
6.4. By Application (USD)
6.4.1. Demand Forecasting
6.4.2. Financial Risk Forecasting
6.4.3. Pricing Personalization
6.4.4. Predictive Maintenance
6.4.5. Others (Churn Prevention, etc.)
6.5. By End-user (USD)
6.5.1. BFSI
6.5.2. Automotive
6.5.3. Telecom/Media
6.5.4. Healthcare
6.5.5. Life Sciences
6.5.6. Retail
6.5.7. Energy & Utility
6.5.8. Government
6.5.9. Others (Manufacturing, Education, etc.)
6.6. By Country (USD)
6.6.1. United States
6.6.1.1. End-user
6.6.2. Canada
6.6.2.1. End-user
6.6.3. Mexico
6.6.3.1. End-user
7. South America Predictive Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034
7.1. Key Findings
7.2. By Deployment (USD)
7.2.1. Cloud
7.2.2. On-premise
7.3. By Enterprise Type (USD)
7.3.1. Large Enterprises
7.3.2. Small and Medium Enterprises (SMEs)
7.4. By Application (USD)
7.4.1. Demand Forecasting
7.4.2. Financial Risk Forecasting
7.4.3. Pricing Personalization
7.4.4. Predictive Maintenance
7.4.5. Others (Churn Prevention, etc.)
7.5. By End-user (USD)
7.5.1. BFSI
7.5.2. Automotive
7.5.3. Telecom/Media
7.5.4. Healthcare
7.5.5. Life Sciences
7.5.6. Retail
7.5.7. Energy & Utility
7.5.8. Government
7.5.9. Others (Manufacturing, Education, etc.)
7.6. By Country (USD)
7.6.1. Brazil
7.6.1.1. End-user
7.6.2. Argentina
7.6.2.1. End-user
7.6.3. Rest of South America
8. Europe Predictive Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034
8.1. Key Findings
8.2. By Deployment (USD)
8.2.1. Cloud
8.2.2. On-premise
8.3. By Enterprise Type (USD)
8.3.1. Large Enterprises
8.3.2. Small and Medium Enterprises (SMEs)
8.4. By Application (USD)
8.4.1. Demand Forecasting
8.4.2. Financial Risk Forecasting
8.4.3. Pricing Personalization
8.4.4. Predictive Maintenance
8.4.5. Others (Churn Prevention, etc.)
8.5. By End-user (USD)
8.5.1. BFSI
8.5.2. Automotive
8.5.3. Telecom/Media
8.5.4. Healthcare
8.5.5. Life Sciences
8.5.6. Retail
8.5.7. Energy & Utility
8.5.8. Government
8.5.9. Others (Manufacturing, Education, etc.)
8.6. By Country (USD)
8.6.1. United Kingdom
8.6.1.1. End-user
8.6.2. Germany
8.6.2.1. End-user
8.6.3. France
8.6.3.1. End-user
8.6.4. Italy
8.6.4.1. End-user
8.6.5. Spain
8.6.5.1. End-user
8.6.6. Russia
8.6.6.1. End-user
8.6.7. Benelux
8.6.7.1. End-user
8.6.8. Nordics
8.6.8.1. End-user
8.6.9. Rest of Europe
9. Middle East & Africa Predictive Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034
9.1. Key Findings
9.2. By Deployment (USD)
9.2.1. Cloud
9.2.2. On-premise
9.3. By Enterprise Type (USD)
9.3.1. Large Enterprises
9.3.2. Small and Medium Enterprises (SMEs)
9.4. By Application (USD)
9.4.1. Demand Forecasting
9.4.2. Financial Risk Forecasting
9.4.3. Pricing Personalization
9.4.4. Predictive Maintenance
9.4.5. Others (Churn Prevention, etc.)
9.5. By End-user (USD)
9.5.1. BFSI
9.5.2. Automotive
9.5.3. Telecom/Media
9.5.4. Healthcare
9.5.5. Life Sciences
9.5.6. Retail
9.5.7. Energy & Utility
9.5.8. Government
9.5.9. Others (Manufacturing, Education, etc.)
9.6. By Country (USD)
9.6.1. Turkey
9.6.1.1. End-user
9.6.2. Israel
9.6.2.1. End-user
9.6.3. GCC
9.6.3.1. End-user
9.6.4. North Africa
9.6.4.1. End-user
9.6.5. South Africa
9.6.5.1. End-user
9.6.6. Rest of MEA
10. Asia Pacific Predictive Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034
10.1. Key Findings
10.2. By Deployment (USD)
10.2.1. Cloud
10.2.2. On-premise
10.3. By Enterprise Type (USD)
10.3.1. Large Enterprises
10.3.2. Small and Medium Enterprises (SMEs)
10.4. By Application (USD)
10.4.1. Demand Forecasting
10.4.2. Financial Risk Forecasting
10.4.3. Pricing Personalization
10.4.4. Predictive Maintenance
10.4.5. Others (Churn Prevention, etc.)
10.5. By End-user (USD)
10.5.1. BFSI
10.5.2. Automotive
10.5.3. Telecom/Media
10.5.4. Healthcare
10.5.5. Life Sciences
10.5.6. Retail
10.5.7. Energy & Utility
10.5.8. Government
10.5.9. Others (Manufacturing, Education, etc.)
10.6. By Country (USD)
10.6.1. China
10.6.1.1. End-user
10.6.2. India
10.6.2.1. End-user
10.6.3. Japan
10.6.3.1. End-user
10.6.4. South Korea
10.6.4.1. End-user
10.6.5. ASEAN
10.6.5.1. End-user
10.6.6. Oceania
10.6.6.1. End-user
10.6.7. Rest of Asia Pacific
11. Company Profiles for Top 10 Players (Based on data availability in public domain and/or on paid databases)
11.1. SAP SE
11.1.1. Overview
11.1.1.1. Key Management
11.1.1.2. Headquarters
11.1.1.3. Offerings/Business Segments
11.1.2. Key Details (Key details are consolidated data and not product/service specific)
11.1.2.1. Employee Size
11.1.2.2. Past and Current Revenue
11.1.2.3. Geographical Share
11.1.2.4. Business Segment Share
11.1.2.5. Recent Developments
11.2. IBM Corporation
11.2.1. Overview
11.2.1.1. Key Management
11.2.1.2. Headquarters
11.2.1.3. Offerings/Business Segments
11.2.2. Key Details (Key details are consolidated data and not product/service specific)
11.2.2.1. Employee Size
11.2.2.2. Past and Current Revenue
11.2.2.3. Geographical Share
11.2.2.4. Business Segment Share
11.2.2.5. Recent Developments
11.3. TIBCO Software Inc.
11.3.1. Overview
11.3.1.1. Key Management
11.3.1.2. Headquarters
11.3.1.3. Offerings/Business Segments
11.3.2. Key Details (Key details are consolidated data and not product/service specific)
11.3.2.1. Employee Size
11.3.2.2. Past and Current Revenue
11.3.2.3. Geographical Share
11.3.2.4. Business Segment Share
11.3.2.5. Recent Developments
11.4. Amazon Web Services, Inc.
11.4.1. Overview
11.4.1.1. Key Management
11.4.1.2. Headquarters
11.4.1.3. Offerings/Business Segments
11.4.2. Key Details (Key details are consolidated data and not product/service specific)
11.4.2.1. Employee Size
11.4.2.2. Past and Current Revenue
11.4.2.3. Geographical Share
11.4.2.4. Business Segment Share
11.4.2.5. Recent Developments
11.5. Alteryx
11.5.1. Overview
11.5.1.1. Key Management
11.5.1.2. Headquarters
11.5.1.3. Offerings/Business Segments
11.5.2. Key Details (Key details are consolidated data and not product/service specific)
11.5.2.1. Employee Size
11.5.2.2. Past and Current Revenue
11.5.2.3. Geographical Share
11.5.2.4. Business Segment Share
11.5.2.5. Recent Developments
11.6. Cloudera, Inc.
11.6.1. Overview
11.6.1.1. Key Management
11.6.1.2. Headquarters
11.6.1.3. Offerings/Business Segments
11.6.2. Key Details (Key details are consolidated data and not product/service specific)
11.6.2.1. Employee Size
11.6.2.2. Past and Current Revenue
11.6.2.3. Geographical Share
11.6.2.4. Business Segment Share
11.6.2.5. Recent Developments
11.7. SAS Institute Inc.
11.7.1. Overview
11.7.1.1. Key Management
11.7.1.2. Headquarters
11.7.1.3. Offerings/Business Segments
11.7.2. Key Details (Key details are consolidated data and not product/service specific)
11.7.2.1. Employee Size
11.7.2.2. Past and Current Revenue
11.7.2.3. Geographical Share
11.7.2.4. Business Segment Share
11.7.2.5. Recent Developments
11.8. FICO
11.8.1. Overview
11.8.1.1. Key Management
11.8.1.2. Headquarters
11.8.1.3. Offerings/Business Segments
11.8.2. Key Details (Key details are consolidated data and not product/service specific)
11.8.2.1. Employee Size
11.8.2.2. Past and Current Revenue
11.8.2.3. Geographical Share
11.8.2.4. Business Segment Share
11.8.2.5. Recent Developments
11.9. Accenture
11.9.1. Overview
11.9.1.1. Key Management
11.9.1.2. Headquarters
11.9.1.3. Offerings/Business Segments
11.9.2. Key Details (Key details are consolidated data and not product/service specific)
11.9.2.1. Employee Size
11.9.2.2. Past and Current Revenue
11.9.2.3. Geographical Share
11.9.2.4. Business Segment Share
11.9.2.5. Recent Developments
11.10. AVEVA Group plc
11.10.1. Overview
11.10.1.1. Key Management
11.10.1.2. Headquarters
11.10.1.3. Offerings/Business Segments
11.10.2. Key Details (Key details are consolidated data and not product/service specific)
