Review: Excel TV’s Data Science with Power BI and R

October 12, 2018
By

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I have had a long history with Excel TV and, like Excel TV (and Excel itself) the channel has changed over the years.

Gone are their regular live-streaming interviews with leading Excel authorities. Excel TV’s main product is now online courses. These are pre-recorded classes taught by the same caliber of talent as that of the interviews.

Excel TV’s first course on dashboards remains among my favorite and I was thrilled to learn that in its latest course Excel TV turns its attention to the world of Big Data and the Microsoft BI ecosystem writ large.

The course, entitled “Data Science with R and Power BI,” is a well-researched course on combining these applications to deliver insight from data.

Course basics

Course instructor Ryan Wade.

This course is taught by Ryan Wade who has over 20 years of experience in business intelligence. It is delivered on Excel TV’s easy-to-use course platform; if you are a student of its other courses, it is easy to navigate between them.

Lectures are delivered over screenshot video with crisp audio and visuals and include a link to download all source code. Ideally this would include source data as well to reproduce the results, but I have been able to modify the supplied code to apply to my own data.

Understanding R’s place in Microsoft’s World

Probably the biggest strength of this course is how it clearly positions R as a tool to use within the Microsoft ecosystem. This pairing should serve as no surprise to astute Microsoft watchers as Microsoft has for years maintained its own distribution of R with Microsoft R Open and for some time has made R visuals available in Power BI.

Ryan makes full use of the Microsoft BI stack from using its R distribution to using the R Tools for Visual Studio development environment to using SQL Server to store data to (obviously) Power BI to present it. There is a lot going on between these various applications and an outside primer on SQL Server and Power BI might be useful.

Pain points defined and accounted for

Every application has its strengths and weaknesses and it appears that by incorporating R so handily into its BI stack Microsoft has tacitly noted some places where R can fill in some gaps.

Ryan does a great job at explicitly identifying and providing examples of these “pain points.” For example, much of the course focuses on mining unstructured text data from the web and on using regular expressions to clean text, weaker points in Power BI.

The course also includes solid introductions to the popular ggplot2 package for data visualization and the dplyr package for data manipulation.

Of course R itself is not without its problems one of which is memory management and capacity. For this Ryan shows how to use Microsoft’s SQL server to overcome this pain point and soon enough you will have integrated R with SQL Server, Power BI and Visual Studio on your computer. This is a very sensible and well-constructed BI stack.

Meeting in the middle

 

As alluded to before, this course’s curriculum lies at getting you started in data science at the intersection of R and Power BI. I illustrate this with the above Venn Diagram. What I hope to show is that this course is not best suited as an introduction to R or Power BI but rather an introduction to using these tools together (plus SQL Server, I would add). While the course does go into some basic data types in R, novices might have difficulty comprehending the videos and code. This holds true to a lesser extent for Power BI.

At the risk of a shameless plug, for a more comprehensive introduction to R for the Excel user, I suggest (wait for it) my own course, “R Explained for Excel Users.” Here you will get a more brass-tacks introduction to R which will leave you in a better position to tackle more advanced courses such as Excel TV’s.

On the whole, I recommend Excel TV’s Data Science with R and Power BI. The ability to construct data science application using a combination of applications such as in this course is quite powerful and impressive, and the course does a nice job at tailoring a curriculum based on this specific use case.

Ready to get started? Learn more about the class here.

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