In this book, we have covered the basic concepts of working with data that professionals working in the construction industry face today and will face in the future. We have learned how to collect data, create data requirements and check data quality. We have looked in detail at the main examples of how data is used in the construction industry and studied the issues of costing and job planning, as well as the operation of construction ERP systems, which are key to managing processes in companies in the construction industry.

We have learned about the main trends in data processing, which are already relevant in various industries and which are just on their way to being applied in construction. We learned how to visualize and analyze data using a variety of methods and tools. We also focused on automating processes using ChatGPT and Pipeline tools and we looked at the application of machine learning and predictive models on construction projects.

By learning the methods, principles, and tools presented in this book, you can start making data-driven decisions in your company instead of intuition. or you can run a chain of code modules in ChatGPT that will process data, generating the information you need in the format you want. And in the future, you can probably implement the scenarios described in this book to extract new information for your project, using machine learning techniques and data from past projects.

The willingness to take knowledge and put it into practice is key to success in the age of digital transformation.