9:00 am Chair’s Opening Remarks

Data Management

9:10 am Building a Data Lake to Set Up Non-Standard Reporting

  • Richard Hiers Data & Analytics Architect, McCarthy Building Companies


  • Explaining the main differences between a data warehouse and a data lake
  • Getting started: exploring how to set up your data lake effectively
  • Learning how to set up your data lake for non-standard, analytic reporting

10:05 am Overcoming Technical Roadblocks to Maintain a Data Lake & Data Warehouse Simultaneously

  • Joe Dib Head of Data Management, Skanska


  • Explaining the main benefits of maintaining a data lake and a data warehouse
  • Addressing the main challenges of setting both up and how to overcome them
  • Deciding whether to hire a third party to aid with the initial set-up

10:45 am Morning Refreshments

Data Collection

11:20 am Creating Robust Verification & Data Cleaning Processes to Ensure Consistency of Data


  • Creating a good verification process to verify the truth in your data
  • Assessing the importance of the digital asset lifecycle to produce reports and graphs
  • Mitigating gaps in data and unclean data with AI and cameras on the job site

12:00 pm Finding the Best Data Collection Technologies


  • Deciding on whether to work with an external vendor and how to find the best fit
    for your company
  • Highlighting the pros and cons of using drones and robots to capture onsite data
  • Identifying common challenges when incorporating new technologies to prevent
    them happening within your organization

12:40 pm Networking Lunch

Analytics Applications

1:40 pm Case Study: Using Analytics to Uncover Unexpected Data

  • Chris Heger Vice President, Chief Innovation Officer, OAC Services


  • Examining how to uncover unexpected data
  • Exploring an example of discovered unexpected data and what this data means
  • Looking at how to interpret interesting correlations

2:30 pm Going Beyond Visualization to Provide Knowledge in a Manner That Gives People Enough Space to Use Their Expertise to Draw Their Own Conclusions


  • Learning how to analyze data with all outliers to have the ability to see the whole picture
  • Evaluating the tools that are available to provide experts with all the data necessary to visualize large data effectively
  • Presenting your data in a manner that gives the experts space to interpret the data using their own expertise

3:10 pm Audience Discussion: Exploring the Future of Analytics in the Construction Industry


  • Where do we want to be as an industry in ten years and what needs to be done
    to achieve those goals?
  • What are the biggest foreseeable challenges to this ideal future and what can
    we do to overcome these challenges?
  • How and what can we learn from other, more advanced, industries?

3:50 pm Chair’s Closing Remarks

4:00 pm End of Conference