The major hurdle for software companies driving value from their machine learning investments is not a technological problem. The major challenge is the quality of the data used to train ML models and the product development strategies that are not adequate for ML-driven data products. This talk discusses the challenges in driving the ROI of ML-data products and provides a blueprint for product managers using actual examples in the Construction tech industry.
Alvaro is Director of Product, Data Platform & Products at Procore Technologies. He is responsible for Procore's customer data infrastructure and data products such as analytics, search, and recommendations that help construction companies manage their projects effectively and reduce risk. Before leading data at Procore, Alvaro led ML & Data products at IBM Watson and Figure Eight.