Engineering design models (3D/BIM): e.g., obtaining quantities, model attributes, and design status from CAD/BIM software. Document control systems – to track deliverables (engineering drawings, vendor documents, and transmittals to subcontractors. Procurement and supply chain systems – including purchase order status, expected delivery dates, supplier progress (manufacturing and shipping statuses), and material management (inventory at site). Construction progress tracking – this may involve integration of field data capture tools (for daily installed quantities, workforce and equipment logs, system completion, among others. Project controls systems – scheduling (Primavera P6 or equivalent) and cost control (budget, earned value metrics). Figure 2 – Data Lake for EPC Integration can be achieved through a combination of direct APIs, middleware, or scheduled ETL (Extract-Transform-Load) processes that pull data from each system into the central repository (lake warehouse) A consolidated project data environment that ensures consistent, up-to-date information lays the groundwork for all other phases by making sure that any tool or analysis draws on trustworthy, current data rather than outdated or conflicting sources. Immediate benefits include reduction in time spent reconciling data setting up the stage for the next phases of this strategic framework. 4. Phase 2: Automated Dashboards and Stakeholder Visibility With integrated data in place, Phase 2 focuses on converting data into easily consumable information for decision-makers. The goal is to replace static, manually prepared reports with dynamic dashboards that provide near real-time insights. Key to these dashboards is that they are automated. Data from Phase 1’s central repository feeds these visualizations continuously or on a schedule (e.g., every 24 hours). Modern business intelligence tools (like Microsoft Power BI, Tableau, etc.) can connect directly to databases or cloud data lakes.
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