Hosting a Shiny App in Tableau

Hosting a Shiny App in Tableau

Graphics in both Tableau and Shiny have their pluses and minuses. Tableau is good for drag and drop graphics that is easy to change the types of graphs given the situation with little to no coding. R/Shiny graphics are completely customizable from 3D graphics to violin plots, which is a boxplot that incorporates a probability density function. Also, with Shiny you can get summaries of the data and perform many other advanced statistical methods; beware of running analyses in Shiny without checking the proper diagnostic tests related to the data at hand (this is my statistics background speaking). Where Tableau … Read More

Tips on Developing Shiny Apps in RStudio Server

Tips on Developing Shiny Apps in RStudio Server

Development from the RStudio Server is seamless to its desktop counterpart with the only difference being that you access it through your web browser. In fact, RStudio Server has some advantages because all you need is a computer that can connect to the internet and you’re using all of the server’s resources for computations rather than your local machine. This means that you can develop R code using a chromebook or tablet, in fact, I connected to my RStudio server on my iPhone and could code if I wanted but quickly found that it would be more of a hassle than it’s … Read More

Valentine’s Day Word Cloud using Oracle’s Distribution of R

Red Rose

We hope you had a great Valentine’s Weekend! Whether you did or not, we knew people on twitter were talking about the big day so we thought we’d do some analysis. Check out how we made this word cloud using Oracle’s Distribution of R to pull Valentine’s Day tweets from Twitter. Once you have Oracle’s Distribution of R running, you must first install the necessary packages. > install.packages(c(“devtools”, “rjson”, “bit64”, “httr”)) > install_github("twitteR", username="geoffjentry") Then, you must load the correct libraries. > library(devtools) > library(tm) > library(wordcloud) > library(twitteR) If you do not have a twitter app already, you will need … Read More

What I Learned From Oracle’s BIWA Summit 2015 (Perspective from a Consulting Intern)

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Our Big Data Team, here at M&S, packed up their bags and headed to San Francisco last week for the 2015 Oracle Business Intelligence Warehousing and Analytics Summit. Some of the major topics discussed included: Internet of Things (IoT), Big Data, and Advanced Analytics. The Internet of Things (IoT) is at the peak of Gartner’s Hype Cycle. It is becoming increasingly talked about and there are predictions of billions and billions of sensors by 2020. But what exactly is IoT? IoT involves embedded computing devices interconnected with existing internet infrastructure, such as, wearables and connected cars. Why the hype right … Read More

Presidential State of the Union Sentiment Analysis

State of the Union Speech Analysis 2015 Barak Obama

Sentiment analysis is a hot technology in marketing. This analysis parses comments and feedback left on corporate and social media sites and attempts to discern the tone or attitude expressed by the commenter. For example, reviews and comments about a company’s product such as “I love these shoes” represent a strong positive statement about how the customer feels about that product. The challenge is that the comments are just free-form text in English which computers traditionally had a hard time deciphering. M&S Big Data thought it would be interesting to apply this sentiment analysis to our Presidents. As a start … Read More

A Commentary of Dual Axis Graphics

A Commentary of Dual Axis Graphics

My philosophy of visualizing data is keep it simple, you want the audience to look at a graph and know within a few moments what it is showing. The key is for accuracy in interpreting the graph and speed; we need to be careful of potentially distorting the data because we don’t want the audience to misinterpret the graph too quickly.  An easy way of distorting the data is changing the range of the axis which can cause the audience to believe there are more extreme changes in the data when there actually isn’t and the data is overall stable. … Read More