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Power BI Tutorial .Rmd

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+---
+title: "Power BI Tutorial"
+author: "Ellen Chen"
+date: "3/10/2021"
+output:
+  html_document: default
+  pdf_document: default
+---
+
+## Quickstart Tutorial to Microsoft Power BI 
+
+### Preface
+A month ago, I received an invitation to a data assessment of an internship position, which asked me to create a Power BI dashboard with given dataset and subject. To be honest, I have never touched on Power BI before that. As a Statistics student, I played around with ggplot2, r shiny, plotly, and seaborn a lot at school. But I never used Power BI before. I thought it would be hard to grasp a new tool in a short time. While, it turned out to be OK. After I got the internship offer, my supervisor asked me a question, *“Did you use Power BI a lot before? How did you make such an outstanding dashboard?”*
+
+I am writing this blog to the whole 5702 class to give a quickstart guide to Power BI and shared the dashboard that sent me to the internship position. Hopefully my blog could help some of you who are also applying for internships and jobs and who may also face an assessment of using it. 
+		                            --- Ellen Chen, Master in Statistics student at Columbia University
+
+### What is Power BI?
+```{r, echo=FALSE}
+knitr::include_graphics("powerbi_logo.png")
+```
+
+**BI** stands for **Business Intelligence**. Power BI is a business analytics service by Microsoft. It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for **end users** to create their own reports and dashboards.  (*Wikipedia*)
+
+### Power BI v.s. R
+```{r, echo=FALSE}
+knitr::include_graphics("powerbi_r.jpeg")
+```
+
+Compared to **ggplot2**, which is also a data visualization tool in r, Power BI is more user-friendly. While Power BI is better in user self-service, R guarantees reproducibility and version control. PowerBI doesn’t have an accessible source code. You can only edit fields in WYSIWYG mode, which makes PowerBI easy to start but difficult to maintain. Having no source code makes it nearly impossible to have proper version control, automatically test logic, or collaborate on large projects.
+  + Power BI **pros**: EASY to start = R **cons**
+
+  + Power BI **cons**: HARD to reproduce & collaborate = R **pros**
+
+### Different Versions of Power BI
+  + **PowerBI Desktop** — an application you can download and install on your computer. Available only for Windows. It has powerful data analysis capabilities and can connect to many data sources. It is used to perform analysis, create visualizations, and to create reports.
+
+  + **PowerBI Service (Pro)** — web application. It is used to create visualizations and reports. The biggest selling point is dashboards -and they are easy to make. Also, it’s easier to share results thanks to the collaboration mode.
+
+  + **PowerBI Mobile** — mobile application for both Android and iOS. It is used only to access your data from anywhere, not to perform analysis.
+
+### How to Download Power BI Desktop? 
+Power BI Desktop is free to download on your computer. Check out the link to download Microsoft Power BI: https://powerbi.microsoft.com/en-us/downloads/
+
+For Mac users: Sadly : (  Power BI Desktop cannot be downloaded on Mac. You can either install and run Power BI on a virtual machine (as I did) or use Power BI Service online: https://powerbi.microsoft.com/en-us/landing/signin/
+
+###  Power BI Connectivity
+```{r, echo=FALSE}
+knitr::include_graphics("powerbi_connectivity.png")
+```
+
+PowerBI comes with many built-in connection types categorized into Files, Databases, Power Platform, Azure, and Online services. 
+
+```{r, echo=FALSE}
+knitr::include_graphics("getdata.png")
+```
+
+### Power BI Chart Types
+PowerBI provides basic visualization options — bar, line, area, scatter, and pie charts, with a couple of fancier types such as maps, treemaps, funnels, and ribbon charts. Refer to the image below for a full list:
+
+```{r, echo=FALSE}
+knitr::include_graphics("charttype.png")
+```
+
+Also, you might have noticed these “R” and “Py” icons. This means you can use R and Python charts in PowerBI, with just one caveat — the source code of these charts is not under version control. PowerBI can handle its own charts and Python/R-generated ones.
+All the visualization options are pretty easy to handle and very user-friendly. 
+
+To me one function I prefer Power BI over R is the different mapping options. In my recent project, I used Power BI to create a **heat map** of the number of violent events that happened in *Democratic Republic of the Congo*.
+
+```{r, echo=FALSE}
+knitr::include_graphics("heatmap.png")
+```
+
+It is fairly easy to use Power BI to create maps as long as your datasets contain **address, zip code, latitude or longitude**. 
+
+```{r, echo=FALSE}
+knitr::include_graphics("heatmap_source.png")
+```
+
+### What is a Power BI dashboard?
+```{r, echo=FALSE}
+knitr::include_graphics("layout.png")
+```
+
+A Power BI **dashboard** is a single page that uses multiple visualizations to serve for a main purpose. 
+```{r, echo=FALSE}
+knitr::include_graphics("dashboard.png")
+```
+
+Asked to give a dashboard to analyze the violent events happening in DRC (Deocratic Republic of the Congo), I combined the bar chart, line chart, pie charts and heat map to make a neat and easy-to-understand Power BI dashboard. 
+
+### More Power BI Dashboard Examples
+You could use Power BI to make all sorts of dashboard with colorful charts and aesthetic layouts. Following are three dashboard examples that I really like:
+
+```{r, echo=FALSE}
+knitr::include_graphics("example1.png")
+```
+
+Example 1: Customer Analysis Dashboard
+
+```{r, echo=FALSE}
+knitr::include_graphics("example2.png")
+```
+
+Example 2: Sales ScoreCard Dashboard
+
+```{r, echo=FALSE}
+knitr::include_graphics("example3.png")
+```
+
+Example 3: Team Performance Dashboard
+
+### Reference
+https://towardsdatascience.com/powerbi-vs-r-shiny-two-popular-excel-alternatives-compared-b58d4ba1e0d1
+