From Insights to Recommendations: How SkyWatch Predicts Demand for Satellite Imagery Using Databricks
Overview
SkyWatch is on a mission to democratize earth observation data and make it simple for anyone to use.
In this session, you will learn about how SkyWatch aggregates demand signals for the EO market and turns them into monetizable recommendations for satellite operators. Skywatch’s Data & Platform Engineer, Aayush will share how the team built a serverless architecture that synthesizes customer requests for satellite images and identifies geographic locations with high demand, helping satellite operators maximize revenue and satisfying a broad range of EO data hungry consumers.
This session will cover:
- Challenges with Fulfillment in Earth Observation ecosystem
- Processing large scale GeoSpatial Data with Databricks
- Databricks in-built H3 functions
- Delta Lake to efficiently store data leveraging optimization techniques like Z-Ordering
- Data LakeHouse Architecture with Serverless SQL Endpoints and AWS Step Functions
- Building Tasking Recommendations for Satellite Operators
Type
- Breakout
Experience
- In Person
Track
- Data Lakehouse Architecture, Databricks Experience (DBX)
Industry
- Enterprise Technology, Public Sector
Difficulty
- Intermediate
Duration
- 40 min
Session Speakers

Aayush Patel
Data & Platform Engineer
Skywatch
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