Geospatial Company Problem
A geodata company wanted to do analytics at scale on massive amounts of time-series GPS data but needed help overcoming data ingest problems, normalizing incompatible data formats, and developing algorithms specific to their customers’ needs.
Solution
OpenTeams Open Source Architect built an open source, cloud-based data science platform to allow them to scale their work, including a stable, reliable, automated workflow to preprocess new data each day, algorithms to feed various data sources into a single dataset, and algorithms to analyze the data according to their customers’ needs.
Outcome
The outcome was an example of MLOps best practices for all of their teams to adopt. It reduces ETL and modeling errors and makes scaling, model experimentation, and production deployment easy.
