# Data Challenge - Technical Considerations¶

Please take into account the following technical considerations as you prepare for the Data Challenge!

## Data¶

Your input files will comprise a a few hundred MB of numerical and textual data. In general, we believe common laptop configurations will be able to handle the data.

## Outputs¶

Outputs from this challenge will include code, visualizations (static and / or interactive), and narrative explanations of how your tool works and what you discovered from it

## Software¶

Solutions that require purchase of a software license or purchased access to data will not be accepted regardless of whether or not we use said software or data. Abide by all applicable laws and regulations regarding the use of software and external data sources. If you have questions about a particular software package, please contact your recruiter immediately.

Here are some example platforms you should feel free to use. By no means are you limited to this list, and our solution review team will be able to evaluate solutions in most languages. If you really do have a question about the platform you would like to use to solve the problem, please contact your recruiter with the exact setup you’d like to use (including OS and specific versions when applicable), your secondary choice, and they can seek verification for the platform

Software | Notable packages
--- | ---
Anaconda Python Distribution | IPython, Jupyter IPython Notebooks, pandas, matplotlib, bokeh
R | RStudio, Shiny, plyr, ggplot
Javascript | D3, nvd3, node.js
Other open software packages with which you are familiar | Please let your recruiter know prior to the start of the challenge

You are not limited to choosing a single package and if you find a combination or packages is most effective - go for it!

Lastly, we recommend that you use a recent or near-recent version of your packages.

## Platform¶

We believe we're equipped to handle most reponses that run on Windows, Linux, or Mac OS X.