Advanced Analytics Market Size by Offering and Delivery Mode - Global Forecast to 2031 | AI, Cloud, and Decision Automation Drive 14.7% CAGR to USD 193.23 Billion
Dublin, Oct. 09, 2026 (GLOBE NEWSWIRE) -- "Advanced Analytics Market by Offering, Delivery Mode - Global Forecast to 2031" has been added to ResearchAndMarkets.com's offering.
The advanced analytics market is projected to expand from USD 97.17 billion in 2026 to USD 193.23 billion by 2031, registering a CAGR of 14.7% during the forecast period. Growth is being supported by rising enterprise data volumes, broader adoption of AI and cloud platforms, and increasing demand for faster, more accurate decision-making across industries.
Organizations are integrating advanced analytics into core business operations to improve efficiency, control costs, strengthen risk management, and increase operational agility. Analytics revenue is increasingly linked to AI workloads, while embedded capabilities within enterprise software are expanding access across business functions. Consulting and services demand also indicates that implementation, data engineering, governance, and operational execution remain central to successful analytics programs.
Market expansion may be limited by poor data quality, legacy system integration complexity, fragmented technology environments, and shortages of skilled analytics professionals. Data privacy, model explainability, security, and regulatory compliance create additional barriers, particularly in highly regulated sectors. Vendors are responding with stronger governance, model management, and security capabilities.
Intelligent Decision Automation to Record the Fastest Application Growth
Intelligent decision automation is expected to be the fastest-growing application segment during the forecast period. Enterprises are progressing from static reporting toward platforms that recommend or execute actions across pricing, fraud prevention, IT operations, customer engagement, and supply chain management.
AI-driven decision engines, rules orchestration, and closed-loop analytics help organizations reduce decision latency, manage operational complexity, and respond to changing conditions in real time. Growing demand for measurable business outcomes is positioning intelligent decision automation as an important opportunity for advanced analytics vendors.
Machine Learning Driven Analytics to Lead Solution Offerings in 2026
The machine learning driven analytics segment is estimated to account for the largest market share in 2026. Adoption is supported by the growing use of predictive and prescriptive analytics across finance, operations, customer intelligence, and risk management.
Investments in AutoML, model management, and AI-assisted analytics are reducing technical barriers while improving scalability and continuous learning. As enterprises prioritize forecasting accuracy, operational optimization, and data-driven performance, machine learning-driven analytics will remain a core component of advanced analytics deployments.
North America Leads as Asia Pacific Posts the Fastest Growth
North America represents the largest advanced analytics market due to early technology adoption, substantial enterprise IT investment, and the presence of major cloud and analytics providers. Organizations in BFSI, healthcare, retail, and technology have integrated analytics extensively across strategic and operational workflows.
Asia Pacific is expected to register the highest growth rate through 2031. Rapid digitalization, expanding cloud infrastructure, government-led technology programs, and increasing enterprise AI adoption are driving regional investment. Europe, Latin America, and the Middle East & Africa also offer opportunities as organizations modernize data platforms and pursue industry-specific analytics strategies.
Research Coverage
The advanced analytics market report is segmented by offering, delivery mode, application, vertical, and region. Offerings include solutions and services, with solution categories covering Rule-based & Statistical Analytics, Machine Learning Driven Analytics, Augmented & Decision-centric Analytics, and Agentic & Autonomous Analytics.
Delivery modes include Standalone Analytics Software, Embedded & In-application Delivery, Cloud-native & Lakehouse-based Delivery, Edge & Distributed Analytics Delivery, and Agent-based & Autonomous Delivery Models. Applications include Customer & Revenue Intelligence, Financial Risk & Performance Management, Supply Chain & Operations Intelligence, Process & Quality Management, Human Capital Analytics, Product, Digital, & IT Operations Analytics, and Intelligent Decision Automation.
Industry coverage includes BFSI, Healthcare & Life Sciences, Retail & E-commerce, Manufacturing, Telecommunications, Energy & Utilities, Media & entertainment, Government & Public Sector, Transportation & Mobility, and Technology & Software. Regional analysis covers North America, Europe, Asia Pacific, the Middle East & Africa (MEA), and Latin America.
Primary Research Breakdown
Primary research included interviews with chief executive officers, innovation and technology directors, system integrators, managers, and executives from organizations participating in the advanced analytics market.
Competitive Landscape
The report assesses market shares, product innovation, growth strategies, service offerings, partnerships, investments, and go-to-market activity. Companies profiled include IBM, Microsoft, Google, Palantir, Oracle, SAS Institute, SAP, Adobe, AWS, Salesforce, Databricks, Snowflake, ServiceNow, Dataiku, DataRobot, H2O.ai, Qlik, Teradata, Alteryx, FICO, Celonis, TIBCO, ThoughtSpot, Accenture, Deloitte, Capgemini, Cognizant, and other established and emerging providers.
Key Benefits of the Advanced Analytics Market Report
The findings support market leaders and new entrants in evaluating revenue opportunities, understanding competitive conditions, prioritizing product development, and planning effective go-to-market strategies across the global advanced analytics market.
Key Attributes:
Key Topics Covered:
1 Introduction
1.1 Study Objectives
1.2 Market Definition
1.2.1 Inclusions and Exclusions
1.3 Market Scope
1.3.1 Market Segmentation
1.3.2 Years Considered
1.4 Currency Considered
1.5 Stakeholders
1.6 Summary of Changes
2 Executive Summary
2.1 Market Highlights and Key Insights
2.2 Key Market Participants: Mapping of Strategic Developments
2.3 Disruptive Trends in Advanced Analytics Market
2.4 High-Growth Segments
2.5 Regional Snapshot: Market Size, Growth Rate, and Forecast
3 Premium Insights
3.1 Attractive Opportunities in Advanced Analytics Market
3.2 Advanced Analytics Market, by Region
3.3 Advanced Analytics Market: Top Three Solutions
3.4 North America: Advanced Analytics Market, by Delivery Mode and Application
4 Market Overview
4.1 Introduction
4.2 Market Dynamics
4.2.1 Drivers
4.2.1.1 Alignment with AI Spending Cycles is Re-Prioritizing Analytics Investment
4.2.1.2 Platform-Centric Enterprise Architectures are Reshaping Analytics Procurement
4.2.1.3 Agentic and Autonomous Analytics Enabling Self-Directed Intelligence
4.2.2 Restraints
4.2.2.1 Advanced Analytics Fails Without Data Engineering Spend
4.2.2.2 Data Governance, Security, and Compliance Overhead
4.2.3 Opportunities
4.2.3.1 Shift from Descriptive to Prescriptive & Decision Automation
4.2.3.2 Vertical-Specific Analytics Monetization
4.2.3.3 Consumption-Based Pricing Aligns Analytics Spend with Value
4.2.4 Challenges
4.2.4.1 Analytics Roi Difficult to Attribute at Enterprise Scale
4.2.4.2 Fragmentation of Analytics Stack
4.3 Unmet Needs and White Spaces
4.3.1 Unmet Needs in Advanced Analytics Market
4.3.2 White Space Opportunities
4.4 Interconnected Markets and Cross-Sector Opportunities
4.4.1 Interconnected Markets
4.4.2 Cross-Sector Opportunities
4.5 Strategic Moves by Tier-1/2/3 Players
5 Industry Trends
5.1 Porter's Five Forces Analysis
5.1.1 Threat of New Entrants
5.1.2 Threat of Substitutes
5.1.3 Bargaining Power of Suppliers
5.1.4 Bargaining Power of Buyers
5.1.5 Intensity of Competition Rivalry
5.2 Macroeconomic Outlook
5.2.1 Introduction
5.2.2 Gdp Trends and Forecast
5.2.3 Trends in Global AI Industry
5.2.4 Trends in Global Big Data & Analytics Industry
5.3 Ecosystem Analysis
5.3.1 Solution Providers
5.3.1.1 Rule-Based & Statistical Analytics Providers
5.3.1.2 Machine Learning-Driven Analytics Providers
5.3.1.3 Augmented & Decision-Centric Analytics Providers
5.3.1.4 Agentic & Autonomous Analytics Providers
5.3.2 Service Providers
5.3.2.1 Professional Service Providers
5.3.2.2 Managed Service Providers
5.4 Supply Chain Analysis
5.5 Pricing Analysis
5.5.1 Average Selling Price of Offerings, by Key Player, 2026
5.5.2 Average Selling Price of Solutions, by Application, 2026
5.6 Investment and Funding Scenario
5.7 Case Study Analysis
5.7.1 Zynex Driving 60% Analytics Cost Savings Through Savant Labs
5.7.2 Holcim Enabling Real-Time Predictive Maintenance Across Industrial Assets Using C3 AI
5.7.3 Transforming End-To-End Business Processes Through Process Intelligence
5.7.4 Roku Enhancing Financial Planning Agility with Scalable Scenario Modeling
5.7.5 Strengthening Fraud Detection with Agentic AI-Driven Decision Intelligence
5.8 Key Conferences and Events, 2025-2026
5.9 Trends/Disruptions Impacting Customers' Businesses
6 Strategic Disruption: Patents, Digital, and AI Adoption
6.1 Key Technologies
6.1.1 Data Mining
6.1.2 Data Stream Processing
6.1.3 Decision Analytics
6.2 Complementary Technologies
6.2.1 Big Data Technologies
6.2.2 Cloud Computing
6.2.3 Business Intelligence
6.3 Adjacent Technologies
6.3.1 Machine Learning
6.3.2 Artificial Intelligence (AI)
6.3.3 Internet of Things (Iot)
6.4 Patent Analysis
6.4.1 Methodology
6.4.2 Patents Filed
6.4.3 Innovation and Patent Applications
6.5 Impact of AI/Gen AI on Advanced Analytics Market
6.5.1 Best Practices in Advanced Analytics Market
6.5.2 Case Studies of AI Implementation in Advanced Analytics Market
6.5.3 Interconnected Adjacent Ecosystem and Impact on Market Players
6.5.4 Clients' Readiness to Adopt Generative AI in Advanced Analytics Market
7 Regulatory Landscape
7.1 Regional Regulations and Compliance
7.1.1 Regulatory Bodies, Government Agencies, and Other Organizations
7.1.2 Regulations
7.1.2.1 North America
7.1.2.1.1 Securities Exchange Act of 1934 (Sec)
7.1.2.1.2 Artificial Intelligence and Data Act-Aida (Canada)
7.1.2.1.3 Commodity Exchange Act (Cftc)
7.1.2.1.4 Pipeda (Canada)
7.1.2.2 Europe
7.1.2.2.1 Europe Artificial Intelligence Act (European Union)
7.1.2.2.2 General Data Protection Regulation (European Union)
7.1.2.2.3 Data Protection Act 2018 (UK)
7.1.2.2.4 Federal Data Protection Act (Germany)
7.1.2.2.5 Personal Data Protection Code-Legislative Decree 196/2003 (Italy)
7.1.2.3 Asia-Pacific
7.1.2.3.1 Pdpa (Singapore)
7.1.2.3.2 Digital Personal Data Protection Act, 2023 (India)
7.1.2.3.3 Act on Protection of Personal Information (Japan)
7.1.2.3.4 Basic Act on Artificial Intelligence (South Korea)
7.1.2.4 Middle East & Africa
7.1.2.4.1 Federal Decree-Law No. 45 of 2021 on Protection of Personal Data (UAE)
7.1.2.4.2 Personal Data Protection Law (KSA)
7.1.2.4.3 Protection of Personal Information Act (South Africa)
7.1.2.4.4 Personal Data Privacy Protection Law (Qatar)
7.1.2.4.5 Law on Protection of Personal Data No. 6698 (Turkey)
7.1.2.5 Latin America
7.1.2.5.1 General Data Protection Law - Lgpd (Brazil)
7.1.2.5.2 Federal Law on Protection of Personal Data Held by Private Parties (Mexico)
7.1.2.5.3 Personal Data Protection Law No. 25,326 (Argentina)
8 Customer Landscape & Buyer Behavior
8.1 Decision-Making Process
8.2 Key Stakeholders Involved in Buying Process and Their Evaluation Criteria
8.2.1 Key Stakeholders in Buying Process
8.2.2 Buying Criteria
8.3 Adoption Barriers & Internal Challenges
8.4 Unmet Needs from Various Industry Verticals
9 Advanced Analytics Market, by Offering
9.1 Introduction
9.1.1 Drivers: Advanced Analytics Market, by Offering
9.2 Solutions
9.2.1 Rule-Based & Statistical Analytics
9.2.1.1 Enabling Foundational Insights Through Standardized Reporting and Statistical Analysis
9.2.1.2 Reporting & Dashboards Tools
9.2.1.3 Self-Service and Ad-Hoc Analytics
9.2.1.4 Descriptive & Diagnostic Analytics
9.2.2 Machine Learning-Driven Analytics
9.2.2.1 Tapping into Forward-Looking Insights with Improved Scalability Through Data-Driven Learning Models
9.2.2.2 Predictive Analytics
9.2.2.3 Prescriptive Analytics
9.2.3 Augmented & Decision-Centric Analytics
9.2.3.1 Accelerating Decision-Making Through AI-Assisted Insight Generation and Execution
9.2.3.2 Augmented Insight Discovery
9.2.3.3 Automl-Assisted Analytics
9.2.3.4 Analytics Automation and Orchestration
9.2.3.5 Embedded and In-Workflow Analytics
9.2.4 Agentic & Autonomous Analytics
9.2.4.1 Enabling Continuous, Self-Directed Decision-Making Through Autonomous Analytics Systems
9.2.4.2 Analytics Copilots & Assistants
9.2.4.3 Autonomous Analytics Agents
9.2.4.4 Multi-Agent Decision Execution
9.3 Services
9.3.1 Professional Services
9.3.1.1 Enabling Successful Analytics Adoption Through Expert-Led Strategy and Execution
9.3.1.2 Strategy & Consulting
9.3.1.3 Implementation & Integration
9.3.1.4 Advanced Modeling & AI Development
9.3.2 Managed Services
9.3.2.1 Sustaining Analytical Performance Through Continuous Management and Optimization
9.3.2.2 Managed Data & Intelligence Platforms
9.3.2.3 Model Operations & Optimization
9.3.2.4 Autonomous & AI-Driven Operations
10 Advanced Analytics Market, by Delivery Mode
10.1 Introduction
10.1.1 Drivers: Advanced Analytics Market, by Delivery Mode
10.2 Standalone Analytics Software
10.2.1 Enabling Controlled and Customizable Analytics Through Independent Platforms
10.3 Embedded & In-Application Delivery
10.3.1 Driving Analytics' Adoption by Delivering Insights Directly Within Business Workflows
10.4 Cloud-Native & Lakehouse-Based Delivery
10.4.1 Scaling Advanced Analytics Through Flexible and Cloud-First Architectures
10.5 Edge & Distributed Analytics Delivery
10.5.1 Enabling Real-Time Analytics Closer to Data Sources and Operations
10.6 Agent-Based & Autonomous Delivery Models
10.6.1 Automating Enterprise Decisions Through Self-Directed and Intelligent Analytics Systems
11 Advanced Analytics Market, by Application
11.1 Introduction
11.1.1 Drivers: Advanced Analytics Market, by Application
11.2 Customer & Revenue Intelligence
11.2.1 Offering Data-Driven Customer Understanding and Revenue Optimization Across Sectors
11.2.2 Customer Segmentation, Clv, and Churn
11.2.3 Marketing Attribution & Campaign Effectiveness
11.2.4 Pricing, Promotion, and Recommendation
11.3 Financial Risk & Performance Management
11.3.1 Strengthening Financial Stability Through Analytics-Driven Risk Control and Performance Optimization
11.3.2 Financial Planning, Forecasting, and Performance
11.3.3 Credit, Market, and Operational Risk
11.3.4 Fraud Management, Aml, and Compliance
11.4 Supply Chain & Operations Intelligence
11.4.1 Building Resilient and Adaptive Supply Chains Through Analytics-Driven Operational Visibility
11.4.2 Demand Planning & Forecasting
11.4.3 Supply Chain, Logistics, and Network Optimization
11.4.4 Asset Performance & Maintenance Planning
11.5 Process & Quality Management
11.5.1 Improving Operational Excellence Through Analytics-Led Process Visibility and Quality Control
11.5.2 Process Intelligence & Optimization
11.5.3 Quality Management & Defect Reduction
11.5.4 Yield & Throughput Optimization
11.6 Human Capital Analytics
11.6.1 Enabling Data-Driven Workforce Decisions to Improve Productivity and Organizational Resilience
11.6.2 Workforce Planning & Capacity Management
11.6.3 Employee Performance & Engagement
11.6.4 Talent Acquisition, Retention, and Attrition
11.7 Product, Digital, and It Operations Analytics
11.7.1 Enhancing Digital Reliability and Product Performance Through Analytics-Led Operational Intelligence
11.7.2 Product Usage & Performance
11.7.3 Digital Experience Monitoring
11.7.4 It & Platform Operations Analytics
11.8 Intelligent Decision Automation
11.8.1 Accelerating Business Outcomes Through Analytics-Driven and Automated Decision Execution
11.8.2 Automated Decision Management
11.8.3 Closed-Loop Business Process Control
11.8.4 Predictive Intervention & Exception Management
12 Advanced Analytics Market, by Vertical
12.1 Introduction
12.1.1 Drivers: Advanced Analytics Market, by Vertical
12.2 BFSI
12.2.1 Strengthening Financial Trust and Profitability Through Risk-Aware and Data-Driven Intelligence
12.3 Healthcare & Life Sciences
12.3.1 Improving Patient Outcomes and Operational Efficiency Through Analytics-Enabled Healthcare Intelligence
12.4 Retail & Ecommerce
12.4.1 Driving Revenue Growth and Personalization Through Customer-Centric Analytics
12.5 Manufacturing
12.5.1 Driving Operational Excellence and Resilience Through Analytics-Led Manufacturing Intelligence
12.6 Telecommunications
12.6.1 Enhancing Network Performance and Customer Experience Through Analytics-Driven Telecom Intelligence
12.7 Energy & Utilities
12.7.1 Improving Reliability and Sustainability Through Analytics-Enabled Energy Intelligence
12.8 Media & Entertainment
12.8.1 Maximizing Audience Engagement and Monetization Through Analytics-Driven Content Intelligence
12.9 Government & Public Sector
12.9.1 Enhancing Transparency and Service Delivery Through Analytics-Enabled Public Sector Intelligence
12.10 Transportation & Mobility
12.10.1 Improving Safety, Efficiency, and Sustainability Through Analytics-Led Mobility Intelligence
12.11 Technology & Software
12.11.1 Scaling Digital Innovation and Platform Performance Through Analytics-Native Software Intelligence
12.12 Other Verticals
13 Advanced Analytics Market, by Region
13.1 Introduction
13.2 North America
13.2.1 North America: Advanced Analytics Market Drivers
13.2.2 US
13.2.2.1 Scaling Governed, Cloud-Native Analytics Driven by AI Investment, Regulatory Focus, and Hyperscale Infrastructure Expansion
13.2.3 Canada
13.2.3.1 Advancing Trusted and Compliant Analytics Adoption Through Strong AI Research, Data Sovereignty Focus, and Public-Sector Leadership
13.3 Europe
13.3.1 Europe: Advanced Analytics Market Drivers
13.3.2 UK
13.3.2.1 Accelerating Analytics Adoption Through Strong Digital Regulation, Cloud Maturity, and AI-First Enterprise Strategies
13.3.3 Germany
13.3.3.1 Driving Industrial and Manufacturing Analytics Through Industry 4.0 Leadership and Data Sovereignty Priorities
13.3.4 France
13.3.4.1 Expanding Analytics Adoption Through Strong Public-Sector Leadership and National AI Investment Programs
13.3.5 Italy
13.3.5.1 Accelerating Analytics Adoption Through Enterprise Digitalization, Cloud Modernization, and EU-Backed Investment Programs
13.3.6 Rest of Europe
13.4 Asia-Pacific
13.4.1 Asia-Pacific: Advanced Analytics Market Drivers
13.4.2 China
13.4.2.1 Scaling Analytics Adoption Through State-Led Digital Infrastructure, AI Investment, and Platform-Driven Data Ecosystems
13.4.3 India
13.4.3.1 Accelerating Analytics Growth Through Digital Public Infrastructure, Cloud Adoption, and Enterprise Modernization
13.4.4 Japan
13.4.4.1 Advancing Analytics Maturity Through Enterprise Modernization, Productivity Focus, and Industrial Data Integration
13.4.5 Asean
13.4.6 Rest of Asia-Pacific
13.5 Middle East & Africa
13.5.1 Middle East & Africa: Advanced Analytics Market Drivers
13.5.2 Saudi Arabia
13.5.2.1 Scaling Advanced Analytics Through Vision 2030-Driven Digital Transformation and Data-Led Governance
13.5.3 UAE
13.5.3.1 Advancing Analytics Maturity Through Smart Government Leadership and AI-First National Strategies
13.5.4 Turkey
13.5.4.1 Advancing Analytics Adoption Through Financial-Sector Leadership and Enterprise Digital Transformation
13.5.5 South Africa
13.5.5.1 Anchoring Analytics Growth Through BFSI Dominance, Public-Sector Modernization, and Risk-Focused Use Cases
13.5.6 Rest of Middle East & Africa
13.6 Latin America
13.6.1 Latin America: Advanced Analytics Market Drivers
13.6.2 Brazil
13.6.2.1 Driving Analytics Adoption Through Large-Scale Enterprise Digitalization and Financial-Sector Innovation
13.6.3 Mexico
13.6.3.1 Expanding Analytics Usage Through Manufacturing Integration and Cross-Border Digital Transformation
13.6.4 Rest of Latin America
14 Competitive Landscape
14.1 Overview
14.2 Key Player Strategies, 2021-2025
14.3 Revenue Analysis, 2021-2025
14.4 Market Share Analysis, 2025
14.4.1 Market Ranking Analysis, 2025
14.5 Brand Comparative Analysis
14.5.1 Brand Comparative Analysis (1/2)
14.5.1.1 Ibm (US)
14.5.1.2 Microsoft (US)
14.5.1.3 Sap (Germany)
14.5.1.4 Sas Institute (US)
14.5.1.5 Alteryx (US)
14.5.2 Brand Comparative Analysis for by Agentic & Autonomous Analytics (2/2)
14.5.2.1 Palantir (US)
14.5.2.2 C3 AI (US)
14.5.2.3 Celonis (Germany)
14.5.2.4 Sas Institute (US)
14.5.2.5 Savant Labs (US)
14.6 Company Evaluation Matrix: Key Players (Tier 1)
14.6.1 Stars
14.6.2 Emerging Leaders
14.6.3 Pervasive Players
14.6.4 Participants
14.6.5 Company Footprint: Key Players (Tier 1), 2025
14.6.5.1 Company Footprint
14.6.5.2 Regional Footprint
14.6.5.3 Offering Footprint
14.6.5.4 Delivery Mode Footprint
14.6.5.5 Application Footprint
14.6.5.6 Vertical Footprint
14.7 Company Evaluation Matrix: Key Players (Tier 2 & 3)
14.7.1 Stars
14.7.2 Emerging Leaders
14.7.3 Pervasive Players
14.7.4 Participants
14.7.5 Company Footprint: Key Players (Tier 2 & 3), 2025
14.7.5.1 Company Footprint
14.7.5.2 Regional Footprint
14.7.5.3 Offering Footprint
14.7.5.4 Delivery Mode Footprint
14.7.5.5 Application Footprint
14.7.5.6 Vertical Footprint
14.8 Company Evaluation Matrix: Key Players (Agentic & Autonomous Analytics)
14.8.1 Stars
14.8.2 Emerging Leaders
14.8.3 Company Footprint: Key Players (Agentic & Autonomous Analytics), 2025
14.8.3.1 Company Footprint
14.8.3.2 Regional Footprint
14.8.3.3 Offering Footprint
14.8.3.4 Delivery Mode Footprint
14.8.3.5 Application Footprint
14.8.3.6 Vertical Footprint
14.9 Company Valuation and Financial Metrics
14.10 Competitive Scenario
14.10.1 Product Launches and Enhancements
14.10.2 Deals
15 Company Profiles
15.1 Introduction
15.2 Key Players
15.2.1 Ibm
15.2.1.1 Business Overview
15.2.1.2 Products/Solutions/Services Offered
15.2.1.3 Recent Developments
15.2.1.3.1 Product Launches and Enhancements
15.2.1.3.2 Deals
15.2.1.4 Analyst's View
15.2.1.4.1 Key Strengths
15.2.1.4.2 Strategic Choices
15.2.1.4.3 Weaknesses and Competitive Threats
15.2.2 Google
15.2.2.1 Business Overview
15.2.2.2 Products/Solutions/Services Offered
15.2.2.3 Recent Developments
15.2.2.3.1 Product Launches and Enhancements
15.2.2.3.2 Deals
15.2.2.4 Analyst's View
15.2.2.4.1 Key Strengths
15.2.2.4.2 Strategic Choices
15.2.2.4.3 Weaknesses and Competitive Threats
15.2.3 Microsoft
15.2.3.1 Business Overview
15.2.3.2 Products/Solutions/Services Offered
15.2.3.3 Recent Developments
15.2.3.3.1 Product Launches and Enhancements
15.2.3.3.2 Deals
15.2.4 Moody's Analytics
15.2.4.1 Business Overview
15.2.4.2 Products/Solutions/Services Offered
15.2.4.3 Recent Developments
15.2.4.3.1 Product Launches and Enhancements
15.2.4.3.2 Deals
15.2.4.4 Analyst's View
15.2.4.4.1 Key Strengths
15.2.4.4.2 Strategic Choices
15.2.4.4.3 Weaknesses and Competitive Threats
15.2.5 Salesforce
15.2.5.1 Business Overview
15.2.5.2 Products/Solutions/Services Offered
15.2.5.3 Recent Developments
15.2.5.3.1 Product Launches and Enhancements
15.2.5.3.2 Deals
15.2.6 Pegasystems
15.2.6.1 Business Overview
15.2.6.2 Products/Solutions/Services Offered
15.2.6.3 Recent Developments
15.2.6.3.1 Product Launches and Enhancements
15.2.6.3.2 Deals
15.2.7 Snowflake
15.2.7.1 Business Overview
15.2.7.2 Products/Solutions/Services Offered
15.2.7.3 Recent Developments
15.2.7.3.1 Product Launches and Enhancements
15.2.7.3.2 Deals
15.2.8 Oracle
15.2.8.1 Business Overview
15.2.8.2 Products/Solutions/Services Offered
15.2.8.3 Recent Developments
15.2.8.3.1 Product Launches and Enhancements
15.2.8.3.2 Deals
15.2.9 Servicenow
15.2.10 AWS
15.2.11 Sap
15.2.12 Nice
15.2.13 Workday
15.2.14 Adobe
15.2.15 Splunk (Cisco)
15.2.16 Infor (Koch Industries)
15.2.17 Teradata
15.3 Tier 2 & 3 Players
15.3.1 Fico
15.3.2 Anaplan
15.3.3 H2O.AI
15.3.4 Databricks
15.3.5 Altair
15.3.6 Tibco
15.3.7 Fractal Analytics
15.3.8 Mu Sigma
15.3.9 Epic Systems
15.3.10 Strategy
15.3.11 Qlik
15.3.12 Thoughtspot
15.3.13 Domo
15.3.14 Sisense
15.3.15 Yellowfin (Idera)
15.3.16 Zoho
15.3.17 Gooddata
15.3.18 Alteryx
15.3.19 Domino Data Lab
15.3.20 Knime
15.4 Agentic & Autonomous Analytics Players
15.4.1 Savant Labs
15.4.1.1 Business Overview
15.4.1.2 Products/Solutions/Services Offered
15.4.1.3 Recent Developments
15.4.1.3.1 Product Launches and Enhancements
15.4.1.3.2 Deals
15.4.1.4 Analyst's View
15.4.1.4.1 Key Strengths
15.4.1.4.2 Strategic Choices
15.4.1.4.3 Weaknesses and Competitive Threats
15.4.2 Palantir
15.4.2.1 Business Overview
15.4.2.2 Products/Solutions/Services Offered
15.4.2.3 Recent Developments
15.4.2.3.1 Product Launches and Enhancements
15.4.2.3.2 Deals
15.4.2.4 Analyst's View
15.4.2.4.1 Key Strengths
15.4.2.4.2 Strategic Choices
15.4.2.4.3 Weaknesses and Competitive Threats
15.4.3 C3.AI
15.4.3.1 Business Overview
15.4.3.2 Products/Solutions/Services Offered
15.4.3.3 Recent Developments
15.4.3.3.1 Product Launches and Enhancements
15.4.3.3.2 Deals
15.4.3.3.3 Other Developments
15.4.3.4 Analyst's View
15.4.3.4.1 Key Strengths
15.4.3.4.2 Strategic Choices
15.4.3.4.3 Weaknesses and Competitive Threats
15.4.4 Sas Institute
15.4.5 Celonis
15.4.6 Datarobot
15.4.7 Dataiku
15.5 Other Players
15.5.1 Accenture
15.5.2 Deloitte
15.5.3 Capgemini
15.5.4 Cognizant
16 Research Methodology
16.1 Research Data
16.1.1 Secondary Data
16.1.2 Primary Data
16.1.2.1 Breakup of Primary Profiles
16.1.2.2 Key Industry Insights
16.2 Data Triangulation
16.3 Market Size Estimation
16.3.1 Top-Down Approach
16.3.2 Bottom-Up Approach
16.4 Market Forecast
16.5 Research Assumptions
16.6 Study Limitations
17 Appendix
17.1 Discussion Guide
17.2 Knowledgestore: The Subscription Portal
17.3 Customization Options
List of Tables [471]
List of Figures [66]
Companies Featured
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