
Region:Asia
Author(s):Sanjna
Product Code:KROD9978
November 2024
90

By Type of Analytics; Vietnams data analytics market is segmented by type of analytics into descriptive, predictive, prescriptive, and diagnostic analytics. Descriptive analytics dominates the market due to its wide application in summarizing historical data to help companies understand trends. Organizations in retail and financial sectors rely on descriptive analytics to create detailed reports on past sales, customer behaviors, and financial trends, enabling better decision-making processes.
By Deployment Mode: The market is further segmented by deployment mode into on-premise and cloud-based solutions. Cloud-based deployment holds a dominant market share due to its cost-effectiveness, scalability, and flexibility. The rapid growth of cloud infrastructure in Vietnam, coupled with lower upfront costs compared to on-premise systems, has encouraged enterprises of all sizes to opt for cloud-based data analytics. Additionally, the cloud-based model supports remote access, which has become essential for businesses transitioning to hybrid work environments post-pandemic.
Vietnam Data Analytics Market Competitive LandscapeThe Vietnam data analytics market is dominated by a few major players, both local and international, offering a variety of analytics solutions. Companies like FPT Corporation and Viettel Group have established strong local presence with robust partnerships, while global firms like IBM and Microsoft have secured significant market positions through cutting-edge technological innovations. The market is characterized by collaborations between local IT firms and global giants to offer advanced analytics solutions.

Growth Drivers
Challenges
Vietnam data analytics market is expected to see substantial growth, driven by increasing demand for real-time data insights, expansion of cloud infrastructure, and growing adoption of AI-driven analytics solutions. Government-backed digital transformation programs will further accelerate the deployment of analytics across key sectors like healthcare, finance, and manufacturing. Moreover, businesses will increasingly leverage data analytics to enhance customer experience and improve operational efficiency.
Market Opportunities
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Segments |
Sub-segments |
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By Type of Analytics |
Descriptive Analytics |
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Predictive Analytics |
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Prescriptive Analytics |
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Diagnostic Analytics |
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By Deployment Mode |
On-Premise |
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Cloud-Based |
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By End-Use Industry |
Banking, Financial Services, and Insurance |
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Government |
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IT & Telecommunications |
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Retail |
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Healthcare |
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By Organization Size |
Small and Medium-Sized Enterprises (SMEs) |
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Large Enterprises |
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By Region |
Northern |
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Central |
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Southern |
1.1. Definition and Scope
1.2. Market Taxonomy
1.3. Market Growth Rate
1.4. Market Segmentation Overview
2.1. Historical Market Size
2.2. Year-On-Year Growth Analysis
2.3. Key Market Developments and Milestones
3.1. Growth Drivers
3.1.1. Increased Adoption of Big Data Solutions (Industry Penetration)
3.1.2. Digital Transformation Initiatives (Government and Enterprise)
3.1.3. Proliferation of IoT Devices (Data Generation)
3.1.4. Growing Demand for Real-Time Analytics (Decision-Making Efficiency)
3.2. Market Challenges
3.2.1. Lack of Skilled Workforce (Talent Gap)
3.2.2. Data Privacy and Security Concerns (Regulatory Compliance)
3.2.3. High Implementation Costs (Budget Constraints)
3.2.4. Fragmented IT Infrastructure (Integration Issues)
3.3. Opportunities
3.3.1. Expansion of Cloud Computing Solutions (Infrastructure Flexibility)
3.3.2. Emerging AI and Machine Learning Use Cases (Automated Analytics)
3.3.3. International Collaborations for Technological Advancements (Market Expansion)
3.3.4. Rising Adoption of Data-Driven Decision-Making in SMEs (New Market Penetration)
3.4. Trends
3.4.1. Integration of Analytics with IoT (Enhanced Predictive Capabilities)
3.4.2. Increased Focus on Data Governance (Compliance and Data Quality)
3.4.3. Adoption of Data-as-a-Service (DaaS) Models (Subscription-based Solutions)
3.4.4. Growing Use of Advanced Visualization Tools (User Experience Enhancement)
3.5. Government Regulations
3.5.1. Data Privacy Regulations (Decree 13/2023 on Personal Data Protection)
3.5.2. National Digital Transformation Program (Support for Analytics Adoption)
3.5.3. Cybersecurity Law (Impact on Data Storage and Handling)
3.5.4. Open Data Initiatives (Encouraging Public Data Access for Enterprises)
3.6. SWOT Analysis
3.7. Stakeholder Ecosystem (End-Users, Providers, and Integrators)
3.8. Porters Five Forces Analysis (Industry Dynamics)
3.9. Competitive Landscape (Maturity, Innovation, and Strategic Partnerships)
4.1. By Type of Analytics (In Value %)
4.1.1. Descriptive Analytics
4.1.2. Predictive Analytics
4.1.3. Prescriptive Analytics
4.1.4. Diagnostic Analytics
4.2. By Deployment Mode (In Value %)
4.2.1. On-Premise
4.2.2. Cloud-Based
4.3. By End-Use Industry (In Value %)
4.3.1. Banking, Financial Services, and Insurance (BFSI)
4.3.2. Government
4.3.3. IT & Telecommunications
4.3.4. Retail
4.3.5. Healthcare
4.4. By Organization Size (In Value %)
4.4.1. Small and Medium-Sized Enterprises (SMEs)
4.4.2. Large Enterprises
4.5. By Region (In Value %)
4.5.1. Northern Vietnam
4.5.2. Central Vietnam
4.5.3. Southern Vietnam
5.1. Detailed Profiles of Major Companies
5.1.1. FPT Corporation
5.1.2. Viettel Group
5.1.3. IBM Vietnam
5.1.4. Microsoft Vietnam
5.1.5. Oracle Vietnam
5.1.6. Hitachi Vantara Vietnam
5.1.7. DXC Technology Vietnam
5.1.8. SAS Vietnam
5.1.9. SAP Vietnam
5.1.10. Teradata Vietnam
5.2. Cross Comparison Parameters (Revenue, Number of Analytics Solutions, Regional Coverage, Cloud Deployment Models, Industry Focus, Strategic Partnerships, R&D Investment, Market Share)
5.3. Market Share Analysis
5.4. Strategic Initiatives
5.5. Mergers and Acquisitions
5.6. Investment Analysis
5.7. Government Incentives for Analytics Adoption
5.8. Private Equity and Venture Capital Investments
6.1. Data Security Standards
6.2. Data Sovereignty and Localization Laws
6.3. Compliance with International Data Regulations (GDPR, HIPAA)
7.1. Future Market Size Projections
7.2. Key Factors Driving Future Market Growth
8.1. By Type of Analytics (In Value %)
8.2. By Deployment Mode (In Value %)
8.3. By End-Use Industry (In Value %)
8.4. By Organization Size (In Value %)
8.5. By Region (In Value %)
9.1. TAM/SAM/SOM Analysis
9.2. Customer Segmentation and Targeting Strategies
9.3. Go-to-Market Strategies for New Entrants
9.4. Innovation Roadmap for Data Analytics Providers
The initial phase of research involves mapping the entire data analytics ecosystem in Vietnam. This includes identifying key variables such as market players, industry verticals, technology platforms, and regulatory guidelines that impact the market.
During this step, historical data is analyzed to understand market trends, adoption rates, and the revenue generated by different segments. Industry reports, government publications, and proprietary databases are used to validate market insights.
Key hypotheses related to market growth, technology integration, and future trends are validated through interviews with industry experts. These consultations offer critical insights into market dynamics from professionals who operate within the analytics space.
The final step involves synthesizing research findings and engaging with major analytics providers in Vietnam to validate data on sales performance, customer adoption, and market growth projections. This ensures that the final report is accurate, comprehensive, and validated by industry stakeholders.
The Vietnam data analytics market is valued at USD 4 billion, driven by the increasing need for digital transformation across industries and the rapid growth of IoT applications in business operations.
Challenges in Vietnam data analytics market include a lack of skilled professionals, concerns around data privacy and security, and high implementation costs associated with deploying advanced analytics systems.
Key players in Vietnam data analytics market include FPT Corporation, Viettel Group, IBM Vietnam, Microsoft Vietnam, and Oracle Vietnam, which dominate due to their strong local presence and technological expertise.
Vietnam data analytics market is propelled by factors such as increased adoption of big data technologies, government-led digital transformation programs, and the rising demand for real-time data insights in business operations.
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