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ShinyProxy 0.6.0 released!

ShinyProxy is a novel, open source platform to deploy Shiny apps for the enterprise or larger organizations. Why is this needed? There is currently no valid open source alternative that offers this functionality. What does it offer? authentication authorization securing traffic with TLS/SSL usage statistics scalability This is free and open source, is there also a paying and proprietary version?

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Open Analytics @ UseR! 2015

The knarrs of Open Analytics have left the port of Antwerp on their way to Denmark. What will our delegation bring to Aalborg besides our loyal sponsorship? Tuesday For starters we’ve just released a Dockerfile Editor which may be particularly useful for Dirk Eddelbuettel’s tutorial on Docker on June 30. An overview of all tutorials can be found here. Wednesday On the first day of the conference Willem Ligtenberg will present at 16:00 on how to use databases in R without a line of SQL with Rango.

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Editing Dockerfiles with Architect

In the last two years, software development had taken a step forward with the advent of the Docker. For the uninitiated, a Docker is a tool that automates the deployment of applications by packaging them with their dependencies in a virtual container, eliminating the need for virtual machines. Docker has streamlined the process of application development on Linux servers, and Open Analytics has streamlined the creation of Docker files with Architect’s new Dockerfile Editor.

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All Aboard! The R Service Bus 6.2

As R has continued its growth in populary, it’s made some exotic friends. Friends who speak other (programming) languages. Friends who live on servers and virtual machines. Friends who sometimes need to set aside their differences and work towards a common goal. In the absence of a protocol droid or Babel fish, we have the enterprise service bus. For the uninitiated, an enterprise service bus is a software architecture model designed to interface between various software applications.

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Need for Processing Speed: data.table

The first time I discovered data.table it felt like magic. I was waiting on a process that was projected to take the better part of an afternoon. In the meantime, I followed the data.table tutorial, rewrote my code using the data.table structure, and fully executed said code, all while the data.frame equivalent was wheezing along. In the last year, data.table has gotten even faster. data.table’s Automatic Indexing For the uninitiated, data.

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Hypothesis Testing: Fishing for Trouble

Introduction “Can you check if this is significant?” It was a seemingly innocuous question from a dangerous source: a semi data-literate scientist. The kind who believed, deep in his heart, that small p-values were “good” and large p-values were “erroneous”. On this day, the man in question had come forth with a large, complex multivariate dataset. He’d manually combed the data, visually inspected it, and hand-picked a hypothesis. “Can you check if this is significant?

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