Our Data Visualization Basics
A Data Visualization Primer
Let’s look at some data visualization basics. In today’s technologically advanced age, we are overwhelmed with data every day – not all of it necessarily useful. Having a hold of data is a treasure, but what is treasure if you can’t invest in it?
The process of data visualization aims to make sense of information, which in turn can be used to shape and direct future decisions. Molding that information into something comprehensible and legible can be difficult, requiring precision and analysis that comes with experience and general know-how.
So you want to dive deep into the data viz world – where to start? Let’s break it down into its simplest elements, shall we?
What are the Basic Types of Charts and How Do I Use Them?
A dashboard is made out of charts of various types, each has its own use cases. Think of a chart like a canvas – the right one can enhance your data, depending on what sort of message you want to convey. Below is a general guideline for different chart types and their best practices.
Used to show comparison over time or amongst different items. It is simple, succinct, and to the point. Use consistent colors throughout the columns to avoid confusing readers, utilizing accent colors to highlight meaningful data points. To reflect the values appropriately, start the y-axis at 0.
A line graph reveals continuous data, showing trends and progress over time. Multiple data sets can be shown through different plots, differentiated through contrasting coloured lines. Avoid having too many data sets/lines as it can be confusing to read.
Think of dual-axis chart as the love-child of line and column charts. This type of chart allows you to plot based on two y-axes figures and a single x-axis, meaning you can visualize a correlation – or lack thereof – between three data sets. For best practice, use contrasting colors and different graphic styles between data sets to distinctly differentiate them.
Stacked Bar Chart
A cousin of the column chart, stacked bar charts are like a column chart, with the addition of showing the variables that make up a column. This illustrates a part-to-whole relationship for each data sets over time. Use contrasting colours for each variable for clarity.
A mekko chart, also known as Marimekko chart, is similar to a stacked bar, except the x-axis can capture numerous dimensions, rather than just a progression of time. Each bar can contain multiple composite values. For best practice, use a color gradient for each stacked bar to represent its correlation to one another, and organize the placement of sets in such a way to expose a relevant trend.
Who’s never heard of a pie chart? Pie charts are best to show how categories represent part of a whole – a 100%. For best practice, ensure that all slices adds up to 100% and segment slices according to their size. Avoid illustrating too many categories to ensure differentiation between each slice.
What’s a Dashboard?
In a nutshell, a dashboard displays aggregated information in a visual and digestible way. There are basic types of dashboards:
This type of dashboard is used to monitor a business process and track its performance against a set Key Performance Indicators (KPIs). Its data changes frequently, sometimes on a minute-by-minute basis, and is designed to be viewed multiple times a day. An example is Google Analytics that tracks website traffic.
Strategic dashboards are often used by C-level executives to track the status of the organization against KPIs. Updated on a recurring basis, it gives an overview of the business’ top-line performance in one neat page.
Analytical dashboards are smart. They analyze large volumes of data, allowing its users to forecast future trends and discover insights. An analytical dashboard is a powerful reporting tool, meant to help organizations make better informed, data-driven decisions based on insights into historical data. This type of dashboard can often be found in business intelligence tools, typically designed by seasoned data analysts.
Phew – not too complicated is it?
To get started on your data viz journey, it is important to look at the data present and define the need. Only then we can decide what type of charts and dashboard is needed to best represent the desired outcome, adding in narrative, interactivity, and analytical calculations into the mix.
Keep to the basics in data visualization and you’ll never go wrong.