something, it has to be something that will generate enough revenue to cover data warehousing costs: either through digital marketing, fee for service, or have some research value academically speaking.

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I decided to release the source code, under a GNU General Public License, for my Hire Edge app for three reasons: first of all, I'm not entirely sure I can monetize this and it's by far the most basic concepts of the two apps I'm working on - it's a chance to get better at the machine learning aspect of the other app I'm working on. Second, by releasing the source code users can produce their own inputs locally on their own machine and I don't have to buy SQL warehousing yet.

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Third and finally, most of my coding experience has been in R - a world I was introduced to in graduate school. This does make a ton of sense when you realize that my masters degree is in Data Analytics/Digital Marketing. If there is a better platform for customer/user data management than R, or a better GUI than RStudio, I'm unaware. However, for web applications... this is not so true. (Better stuff is still to come - I have a team of fantastic developers for an entirely unrelated project for the culinary artist in you, which I hope to have public by the end of 2017). 

 

But for Hire Edge, R just might be the ticket since this involves quantitative data inputs, and the final results are useful graphical models. I discovered a fantastic framework for web implementation in R called Shiny... HOWEVER, providing this software open source allows developers - software devs, web devs - who know HTML5 and Python better than I do to make user-friendly improvements.

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I expect process improvements over the next couple of weeks, with the help of the Git community, but it's also a functional app that anyone can use - you just have to have R installed on your machine to do so.  Windows users will need to download R. Luckily for Mac users R is already pre-installed in their terminal. I will provide a youtube video later this week for stepwise demonstration.

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For those of you - like me - that understand about development enough to get by, but aren't necessarily a full on developer, you can easily use what I have available... it's just a little bit different for platforms.

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For Mac Users, just open the Terminal app (should be I your applications folder), type "R" in the terminal. Download all the R and Excel tables and drop them into a folder. You can cut-and-paste the scripts in this order: Tax_Bracket_State.R, Tax_Bracket_Federal.R, Salary_Negotiation_Monte_Carlo.R, Inputs.R

 

The lines of code that set the wording directory [setwd('filepath']will have to be changed to your machine, as I haven't connected SQL while still in beta.  

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For Windows users, or Mac users who are using RStudio: download the same packages, but open the R image file titled "Salary_Workspace.Rdata" - this SHOULD open the scripts in the order above, but double check anyway. 

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Then put whatever inputs you want on the final 24 lines of code and go to town 😉

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Click here for the GitHub Repository