- Storage and analysis of large geospatial raster data e.g. Satellite imagery
- Focus on high throughput computing (HTC) limited by data loading
- Array with dimensions e.g. lon, lat, and time, instead of a list of points in vector data
- Cloud optimized to access particular slices of the data (e.g. Bounding box or timespans)
- Importance of data compression for cloud-optimized workflows
- Workflow specific optimization using chunking
- Lazy computations on large data and making data cubes AI-ready
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