Stratasan Blog

Know Your Customer Like Never Before, Part 3: Tapestry Segmentation and Wealthy Urban and Suburban Populations

As learned in the first and second installments of this blog series, it can be quite useful to use Esri's Tapestry Segmentation to target specific populations that your hospital, system, or physicians serve. Tapestry Segmentation was designed specifically to understand your customer’s lifestyle choices – what they buy and how they spend their free time. This information gives Stratasan, and our clients, insights that help identify facility’s patient types, optimal sites for hospitals, physician offices, FSERS, and urgent care locations. We use the Tapestry Segmentation dataset to help our clients get higher response rates, focus on the most profitable growth opportunities, and invest their resources in the best ways possible.

Confident Asset Deployments with Webpack & Django, part 4

  

In the previous post in this series, we've described how at Stratasan, we integrate our Webpack builds into our main Django application. By moving the specific links to our Javascript and CSS out of our Django templates and instead using django-webpack-loader to render these tags, our deployments become more stable and less error-prone.

We want to finish this series with a few niceties that we've built for ourselves to improve our process of delivering valuable software to our clients.

Confident Asset Deployments with Webpack & Django, part 3

In the previous posts in this series, we've explored why we've switched to delivering front-end assets with Webpack and how we configure our Webpack builds.

Here, we're going to cover how to integrate our Webpack builds into Django so that our site serves links to the newest version of our front-end assets.

An Intern's Insights: My Summer at Stratasan

Contrary to popular belief, software developers don’t hide behind their computers all day long and create ruthless memes. While I never subscribed to this line of thinking, to begin with, I got official confirmation of its inaccuracy this summer while interning at Stratasan.

Confident Asset Deployments with Webpack & Django, part 2

Project Layout and Webpack Configuration 

In the previous post, we introduced concepts around deploying front-end assets. If you haven't read it and are not knowledgeable in this area, we suggest you read it now.

In this post, we'll describe the basic file structure of our project and dive into our Webpack configuration.

Confident Asset Deployments with Webpack & Django, Part 1

 

A few weeks ago I had the pleasure to present to DjangoCon US 2016 about how the technology team at Stratasan delivers front-end assets. We've honed this process over the course of a year and are happy with the flexibility and simplicity it allows us. We believe providing concrete examples taken from our codebase will benefit the community.

You can find my slides here.

 

Load-Balancing in a PHI World

This is the first in a series of engineering posts where we take a deep look at the technical underpinnings of Stratasan's analytics platform. We hope you enjoy and perhaps learn something! This does assume a technical background—consider yourself warned :)

We've built Stratasan's analytics platform atop of Amazon Web Services and are big fans of the offerings AWS provides. Our application and worker servers are EC2 instances, application data is stored in an RDS Postgres database, Blackbird results and Canvas PDFs are stored in S3 and our considerable collection of healthcare data is stored and queried from a Redshift cluster.

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