End-to-End Data Analytics Solution Using AWS




The company is a leading provider of Solar Energy solutions like Solar EPC, Solar Rooftop, Operations, and Management Solutions in the Solar sector.
About The Client
The company is a leading provider of Solar Energy solutions like Solar EPC, Solar Rooftop, Operations, and Management Solutions in the Solar sector.
Industry
Renewable


The Business Need
- As a leading provider of solar energy solutions, the company’s ongoing offline reporting system did not meet the modern requirements. On top of it, as data exponentially increased it also became obsolete.
The Approach
- After evaluating the short & long-term goals and technical needs of the company, Scalex recommended taking advantage of the Internet of Things (IoT) as well as Big Data Analytics while leveraging AWS for global availability, scalability, and security.
- To deliver a scalable analytics solution, Scalex used Big data lambda architecture as a guiding principle and implemented it by leveraging AWS IoT and Data Analytics Services. Big data lambda architecture is a data-processing design pattern to handle real-time and batch processing capabilities. It offers three layers – Batch, Speed, and Serving.
The Impact
- With the delivered solution using AWS, the company was able to create a new way to govern the data by processing and storing large volumes of data in real-time coming from solar devices and performing real-time & historical analytics.
- The company has reported that with the new solution they can swiftly analyze and monitor the performance and efficiency of Solar farms with live data and intuitive dashboards. Not only that, but the modern system allowed them to measure net energy generation and diagnose alerts and faults in real-time.
Tech Stack






Proposed Architecture


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Client Name
John Doe
Category
Data Analytics
February 28, 2020
Location
3690 Brownton Road, Mississippi