This case concerns the development of an end-to-end geospatial pipeline that integrates curated spatial attributes with Husqvarna’s internal data to produce a coherent view of golf course environments. Developed in collaboration with Knowit Solutions, the pipeline establishes the technical foundation for geospatial analytics that drive business insights. Structured spatial indexing and robust metadata contribute to an annotated dataset that supports computer vision workflows in validating patterns and enriching geospatial analytics.
Husqvarna is further advancing its data-driven approach by using geospatial analytics to generate deeper insights into green spaces and understand regional variation. This evolving technical foundation is strengthening Husqvarna’s ability to combine visual and spatial information for more precise green space evaluation and identification, enabling more focused and informed decision-making across the organization.
Christos Marinos is a Data Engineer specializing in designing and building scalable, robust data platforms that enable analytics, AI, and machine learning products. He focuses on data extraction, transformation, and modeling, delivering reliable pipelines that support end-to-end AI and ML workflows. He is dedicated to creating data products that generate business value, working closely with stakeholders to align technical solutions with real needs. With a strong emphasis on data governance, scalability, and operational robustness, he builds maintainable platforms that support long-term, value-driven decision-making.
