Dublin, Oct. 27, 2025 (GLOBE NEWSWIRE) — The “Big Data Analytics in Construction Market Report 2025” has been added to ResearchAndMarkets.com’s offering.
The global big data analytics market in the construction sector is witnessing substantial growth. Forecasts suggest that it will rise from $9.07 billion in 2024 to $9.83 billion in 2025, at a compound annual growth rate (CAGR) of 8.3%. This growth is fueled by the increasing need for real-time project monitoring, cost optimization, digital tool adoption in infrastructure, and a focus on improving construction productivity.
By 2029, the market is projected to reach $13.34 billion, with a slightly reduced CAGR of 7.9%, driven by a demand for predictive construction planning insights and data analytics integration with BIM tools. Other factors include an emphasis on risk mitigation, compliance, and a surge in construction activities with innovative applications of AI and machine learning.
Infrastructure development plays a significant role in the growth of big data analytics in construction, providing essential insights for improved planning and execution. The ongoing global investment in infrastructure, such as reported by the UK’s Office for National Statistics in 2023, highlights the sector’s expansion. In July 2024, investments reached $17.25 billion, a 3.9% increase from the previous year, emphasizing economic growth’s impact on the market.
Market leaders like Google LLC, Microsoft Corporation, and Siemens AG are driving innovation with advanced solutions. Notably, in January 2025, Aurigo Software launched Aurigo Lumina, an AI platform enhancing capital planning through better data insights, featuring generative AI and machine learning functionalities. This platform aims to address inefficiencies in data silos and project management.
Significant mergers and acquisitions also mark the sector, exemplified by Bentley Systems Inc.’s acquisition of Cesium GS Inc. in September 2024, enhancing Bentley’s capabilities in digital twins and large-scale visualizations.
Big data analytics in construction gathers, processes, and analyzes vast data throughout project lifecycles, providing stakeholders with valuable insights into patterns and trends. The sector’s essential applications include project management, design, planning, and operations, with solutions being deployed both on-premises and via cloud-based models.
Regionally, North America led the market in 2024. However, Asia-Pacific is projected as the fastest-growing region. The report encompasses global regions including Asia-Pacific, Western and Eastern Europe, North and South America, and the Middle East and Africa, covering countries such as the USA, China, and Germany.
Trade relations and tariff changes globally are impacting the market considerably. In early 2025, U.S. tariffs notably increased construction costs due to higher duties on essential materials, prompting the industry to explore local sourcing and supply chain diversification.
Report Scope
Discover the forefront markets and their swift expansion within the world of big data analytics in construction. Examine the market’s correlation with broader economic and demographic spectra, dissect the forces like technological innovation and regulatory changes shaping its trajectory. This report delves deeply into market facets such as characteristics, size, segmentation, and competition, alongside historic and forecasted growth trends by geography.
- Characterizes and defines market elements.
- Delivers insights on market size covering historical and forecasted development and growth.
- Forecasts informed by factors like AI advancement, geopolitical conflicts, and economic conditions.
- Breaks down market into sub-segments for detailed analysis.
- Presents regional insights, comparing historical growth and future forecasts by geography.
- Analyzes competitive landscape indicating market shares and identifying significant financial dealings.
- Suggests strategic growth plans as the market recovers post-crisis.
Markets Covered:
- By Component: Solution; Services
- By Deployment Model: On-premises; Cloud
- By Technology: Predictive Analytics; Machine Learning and AI; Data Visualization; IoT Integration
- By Application: Project Management; Design and Planning; Construction Management
- By End-User: General Contractors; Subcontractors; Project Owners; Architects and Engineers
Subsegments:
- By Solution: Data Management Tools; Analytics Platforms; Integration Tools; BIM Integration Software
- By Services: Managed Services; Professional Services; Consulting Services; Support and Maintenance
Leading companies in the sector include Google LLC, Microsoft Corporation, Siemens AG, and Accenture Plc. The report highlights dominant regions such as Asia-Pacific, Western and Eastern Europe, North America, South America, the Middle East, and Africa, covering diverse countries like the USA, China, India, Germany, and Brazil. Encompassing both five years of historical and ten years of forecast data, the report offers invaluable metrics and growth comparisons across regions and market segments.
Key Attributes
| Report Attribute | Details |
| No. of Pages | 250 |
| Forecast Period | 2025-2029 |
| Estimated Market Value (USD) in 2025 | $9.83 Billion |
| Forecasted Market Value (USD) by 2029 | $13.34 Billion |
| Compound Annual Growth Rate | 7.9% |
| Regions Covered | Global |
The companies featured in this Big Data Analytics in Construction market report include:
- Google LLC
- Microsoft Corporation
- Siemens AG
- Accenture PLC
- International Business Machines Corporation
- Oracle Corporation
- SAP SE
- Capgemini
- Bechtel Corporation
- Dassault Systemes S.E.
- Hexagon AB
- Autodesk Inc.
- SAS Institute Inc.
- Bentley Systems Incorporated
- Nemetschek SE
- Procore Technologies Inc.
- ConstructConnect Inc.
- Dodge Construction Network LLC
- VisiLean Corporation
- Rhumbix Inc.
- ALICE Technologies Inc.
- Mercator AI Inc.
- Environmental Systems Research Institute Inc.
For more information about this report visit https://www.researchandmarkets.com/r/4y3iml
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- Big Data Analytics in Construction Market
