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Case Study
The Challenge
When we got started, our client:
- Had determined the objectives of the analysis
- Knew the kind of metrics they wanted to calculate
- Was stymied by hundreds of millions of records of raw data that was only semi-structured
![People Talking](/static/assets/video.jpg)
To handle the large number of records, we used Amazon Web Services Redshift, a compressed-column store MPP database that allowed us to realize orders of magnitude better performance over a traditional PostgreSQL implementation at a much lower cost. To handle the semi-structured data, we worked with the client to identify and extract the target metrics and identify cases that needed manual review.
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Case Study
The Solution
Enplus designed and implemented the cloud and data architecture on Amazon Web Services. We delivered a custom-built, lightweight workflow library in Python with several command-line utilities for running different jobs on a recurring basis to keep the models up-to-date. Our client receives daily reports as data moves through the system from raw feeds to actionable analytics.