Data Visualization

“By visualizing information, we turn it into a landscape that you can explore with your eyes, a sort of information map. And when you are lost in information, an information map is kind of useful”

David McCandless

 “Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns (SAS).”

Interpreting large amounts of data can be a long and challenging process and with the evolution of the variety of data visualization tools businesses can interpret data much faster and easier. The way in which a human brain works is that it’s much easier for us to look at pictures and graphs and understand a variety of changing patterns in a data set, than looking at a large table with enormous amounts of number sets and trying to compare those numbers, interpret them and make the right business decisions. The goal of data visualization is to enable people to read and interpret a variety of correlations, patterns and trends much easier and faster by being able to see the data in a visual context.

Some of the most popular data visualization tools are:

 Tableau Software – one of the most popular software programs that enables people to see and understand their data and help business representatives to make faster and better decisions. It enables users to get fast insights about particular data sets, create presentations and share them easily with colleagues. Everyone can use this software- it’s offered in different versions including desktop and cloud versions.

   SAS Visual Analytics – it offers a plethora of reports that illustrate how visual analytics can be applied to questions and problems in a variety of industries. By utilizing a variety of visual graphs it enables business representatives to see the bigger picture and underlying connections.

  Qlik – allows you to create dashboards, visualizations and apps that helps company’s answer most important questions. 

  Microsoft Power BI – allows analyzing and visualizing data in order to make better business decisions.

 Oracle Visual Analyzer – a web-based tool that enables users to explore analytics data visually and on an individual basis. 

  Plotly, DataHero, Chart.js and many others.

There are a variety of charts and graphs that can be utilized to visualize and interpret data sets; some of them are:

•  Line Charts- illustrate the relationship between one variable to another and are commonly used to track trends over time. They can be utilized for tracking multiple data sets on the same chart to visualize correlations and trends.   

• Bar Charts – mostly used to compare the quantities of different categories of groups. Bars represent a category of a certain value. In order to provide visual variance we can utilize a variety of colors for a bar category (see picture below).  

• Scatter Plots – a two-dimensional plot chart that illustrates the joint variation of two data items (see an example below). They can be utilized for analyzing the relationship between different variables. They can be also utilized for applying statistical analysis with correlation and regression.

           

• Bubble Plots – a type of a scatter plot in which the dots or squares are replaced with bubbles and numerical value visualizations in the scale of its circular bubbles. It enables users to illustrate the relationship among at least three data series. They can be utilized to interpret medical, economical, and other scientific relationships.

  

  Pie and Donut Charts – utilized to compare the parts of a whole.

Pie Chart

                          Donut Chart

                                                       

   

•       Heat maps – illustrate the data in which values are represented by colors. There are a variety of colors that can be utilized to illustrate the heat map. One on the most recognizable way of utilizing a heat map is the presidential election. A geographic heat map is marked with two colors (blue represents a democrat candidate and red represents a republican candidate) and therefore the heat map illustrates which states or regions each candidate has won. 

               Find more information about Data Visualization on Kayli Tarcy's blog.