Where scoping hits the road…
Take scoping rules one step further – to applications in Shiny! You need to understand the three main scopes in a Shiny application to save yourself headaches as you expand from one to many users of your apps.
Leadership for Technical Team Success
Understand how a technical leader ensures timely delivery, quality targets, and readiness for a competitive and ever-advancing technology landscape
Don’t run afoul of Scoping Rules in R!
If you use R eventually you will have to worry about scoping – we enumerate the basics and two major “gotcha’s” to keep you safe from the most common stumbling blocks.
How BIG is your big data?
Data has exploded recently, and our world is filled with more and more data, data capturing devices, data analysis, etc. But why do we care so much about categorizing the data into “Big” data buckets?
Getting to Innovation Faster
Guest Post by Rosemary Hossenlopp on 3 Different Types of Analytics Project Teams and 3 Questions for How to Get to Innovation Faster
Intelligence, Life, and …Perception
Computers, and computing networks, are considered “artificial” systems, which means they are created by humans instead of occurring naturally. An important question might be whether these systems are alive?
Categorizing Data Scientists Visually
In this post the visualization of the categorization of types of data scientists is explored as a a way to gain actionable insights on personal or team data science skills.
Testing in R
You can establish solid tests in R with a little planning and practice – we walk step by step through testing a function in R and even setup an easy-to-use framework for repeatability that you can download and start using right away.
DSC Challenge: Data Video
Data Science Central issued a challenge May 28th for readers to create a professional looking data video using R that conveys a useful message.
Small Data Inspiration
I’m thrilled to share a critical thinking post about Big Data that really came to the forefront of my consciousness while I, with great pleasure, read Martin Lindstrom’s new book “Small Data” this week (published Feb 2013 – ISBN 9781250080684).
R vs Python (or …What’s the Big Deal?)
Ok, let’s tackle this one head on – it’s the ubiquitous R vs Python cage match on the WWW! In the world of Data Science and Analytics, this is the equivalent of the Jeep vs hatchback debate! R and Python are both heavily leveraged tools, each with a very firm foothold in the analytics space.