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Synapse Case Study: IIoT Energy Management & Predictive Analytics

Synapse improves profitability and sustainability by enabling manufacturers to enhance their own proven methods – with capabilities built into SimplySnap to help reduce energy waste and maximize equipment uptime.

Challenge

There was an existing AWS data platform to support streaming data, but no support for 3rd party or historical data. The client’s development team was 100% committed to the current roadmap, but no resources to expand platform and add new capabilities. There were product requirements to add value through ML and custom data science algorithms, but no in-house expertise to execute.

Solution

Implemented a full featured Data Lakehouse on Databricks and AWS S3.  Leveraged serverless architectures to lower processing and storage costs while accelerating time to value for the overall platform. Now they can easily add new data sources.

Technologies

Some of the technology expertise used in this project include:

  • AWS S3 Data Lake
  • Databricks Lakehouse
  • Amazon Athena
  • GraphQL
  • REST APIs
  • 3rd Party Integrations

Result

This Data Lakehouse architecture allowed for the addition of an Analytics Engine for new data science algorithms as well as a plug-and-play platform for 3rd party integrations. This greatly increased the value of the Synapse offering.

 

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Visit Synapse's website to learn more.