Chapters 1.2, 4.1–4.3 – Technologies, Data Conversion, Structuring, Modeling:

• Centralized vs fragmented data

• Principles of data structure

• Roles of Excel, DWH, and databases

Chapters 5.2, 7.2 – QTO Automation, ETL with Python:

• Data filtering and grouping

• Automating QTO and quantity takeoff

• Python scripts and ETL logic

Chapter 10.2 – Roadmap for Digital Transformation:

• Strategic stages of digital change

• Organizational setup

• Prioritization and execution paths

Chapters 4.1, 8.1–8.2 – From CAD (BIM) to Storage & Analytics:

• Translating Revit/IFC to structured tables

• BIM as a database

• Building analytical backends

Chapters 7.3, 10.2 – Building ETL Pipelines + Strategic Integration:

• Combining Excel, BIM, ERP

• Automating flows between tools

• Connecting scattered data sources

Chapters 7.3, 7.4 – ETL Pipelines and Orchestration (Airflow, n8n):

• Building pipelines

• Scheduling jobs

• Using tools like Airflow or n8n to control the flow 

Chapters 2.1, 10.1 – Fragmentation, ROI, Survival Strategy:

• Hidden costs of bad data

• Risk of inaction

• ROI of data initiatives

• Convincing stakeholders

Module 1 – Data Automation and Workflows in Construction:

• Overview of data sources
• Excel vs systems
• Typical data flows in construction
• Foundational data logic

Module 3 – Automated Data Processing Workflow:

• Setting up ETL workflows
• CAD/BIM extraction
• Automation in Excel/PDF reporting

Module 8 – Converting Unstructured CAD into Structured Formats 

• From IFC/Revit to tables
• Geometric vs semantic data
• Tools for parsing and transforming CAD models

Module 13 – Key Stages of Transformation 

• Transformation roadmap
• Change management
• Roles and responsibilities
• KPIs and success metrics

Module 8 – Integrating Diverse Data Systems and Formats

• Excel, ERP, BIM integration
• Data connection and file exchange
• Structuring hybrid pipelines

Module 7 – Automating Data Quality Assurance Processes 

• Rules and checks
• Dashboards
• Report validation
• Automated exception handling

Module 10 – Challenges of Digitalization in the Industry 

• How to justify investment in data
• Stakeholder concerns
• ROI examples
• Failure risks

Audit of your data landscape 

We'll review how data is stored and shared in your company and identify key improvement areas.

Select a process for automation 

We'll pick one process in your company that can be automated and outline a step-by-step plan.

Strategic roadmap planning 

Together we’ll map your digital transformation priorities and build a realistic roadmap.

CAD (BIM) - IFC/Revit model review 

We'll review your Revit/IFC/DWG data and show how to convert it into clean, structured datasets.

Mapping integrations across tools 

We’ll identify your main data sources and define how they could be connected into one workflow.

Plan a pilot pipeline (PoC) 

We'll plan a pilot pipeline: where to start, what tools to use, and what benefits to expect.

ROI and stakeholder alignment