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Case Study: NASA Mars Weather Station

Background

This is not a client project; rather it is a concrete example of a typical Rezenent project. This project gathers data from several resources before concatenating them into a dashboard for end user consumption. The explantion is below the following dashboard image.

Today's Curiosity Mars Rover Image

Last UTC: 2020-09-10T17:28:00Z
Martian Season: Summer

Explanation

Data Sources

Mars Rover Photos (Summary | API)
Image data gathered by NASA's Curiosity, Opportunity, and Spirit rovers on Mars

InSight: Mars Weather Service API (Summary | API)
Mars Weather Service API

Storage

Amazon Simple Storage Service, or S3 (Service)
Store and retrieve any anount of data, at any time, from anywhere on the web

Process
  • Each night, a script runs against the Mars Rover Photo NASA API to find the latest Forward Hazard Avoidance (FHAZ) photo available from the Curiosity Rover on Mars, downloads the image, and then upload the image to S3 for storage.
  • The script then runs against the Insight: Mars Weather Service API from NASA to download the last seven days of weather date for Mars.
  • The script finally regenerates this webpage with the updated image and weather data.
Rezenent

This is a great example of some of the work that Rezenent performs, i.e. take 2 or more data sources, store in an intermediate location, change the data representation for the client's needs, and then routinely update a dashboard or other interface to inform decision makers.

This is commonly known as Extract, Transform, and Load - or ETL - in the data management field. Rezenent goes a step further by providing a client facing frontend for customer consumption.

Please reach out to us if you have this same business need. We would love to learn more about your business and find a way for Rezenent to help you define, collect, analyze, and make better business decisions.