Data dashboards are like compasses for data analysts and businesses, guiding them to informed decision-making. In a world awash with data, creating a dashboard that’s not only informative but also visually appealing is an art infused with science. At Data School, we kick off our journey by exploring the realm of dashboard design, setting the stage for our venture into data visualization. Here are three essential questions to ponder:
1. Know Your Data Types
Before you start on your data viz, it’s essential to understand the nature of the data you’re dealing with. Data comes in various format, from time-series data painting trends and patterns over time to geospatial data enabling comparisons across regions, much like maps. Additionally, some interesting categorical fields can serve as filters for your dashboard. The key takeaway here is that the type of data often dictates the suitable visualizations. For instance, geospatial data may find its ideal canvas in maps, while time-series data may shine through line charts and tells trend overtime. Each data type brings its own format and structure, so before diving into analysis, it’s vital to acquaint yourself with the dataset you’re working with.
2. Choosing the right visualizations
Visualizations are the heart and soul of data dashboards. Basically, there are four types of visualizations:
Comparison: Ideal for comparing values over time or across categories, common visualizations include Column/Bar Charts, Clustered Column/Bar Charts, Data Tables/Heat Maps, Radar Charts, Line Charts (for time series), and Area Charts (also for time series).
Composition: This type focuses on breaking down the components of a whole. Here, you can make use of visuals like Stacked Bar/Column Charts, Pie/Donut Charts, Stacked Area Charts (for showing composition and trends over time), as well as others like Waterfall Charts (for gains and losses), Funnel Charts (for depicting stages), and Tree Maps/Sunbursts (for hierarchies).
Distribution: To illustrate the frequency of values within a series, Histograms are the good choice. Alternatively, you can consider Density Plots, Box & Whisker Charts, Scatter Plots, Data Tables/Heat Maps, and Map/Choropleth (for geospatial data).
Relationship: When your goal is to reveal correlations between multiple variables, turn to Scatter Plots, Bubble Charts, Heat Maps, and Correlation Matrices.
After presenting those choices of visuals, the bottom line here is to keep dashboards simple and neat. While the hundreds of or thousands of visuals to choose from, the basic options like bar chart, line chart and scatterplots often did good job that convey idea. There is an interesting concept called “2 seconds rule” means nowadays designers would only have 2 seconds to grab audience’s attention. With this being said, the visualize like bubble chart, tree maps might not be the best choice since it requires longer time for audience to understand what is going on. So don’t be afraid to use same kind of visuals in dashboard.
3. Who is the target audience?
Your data story should be tailored to your audience, and there are four potential groups to consider:
The Analyst: Typically pay attention to detail and need to understand what is going on. Those analytical appreciate simple table or combo chart.
The Manager: This level of audience requires the dashboard with more summaries data to help businesses operates. They typically need some detail but only for specific insight.
The Executive: Time-strapped executives prefer high-level, clear Key Performance Indicators (KPIs) to track business processes. Introducing “BAN” (Big Ass Numbers) or presenting simple charts with minimal details is a wise choice.
The General audience: For those seeking a touch of elegance, there are two types of dashboards to consider. There are two types of dashboards which are explanatory dashboard with more text embedded within to tell them the whole story behind data and the idea of this dashboard. While the exploratory dashboard that with more interactivity that allows them to find out what the underlying relationship within dataset.
In the world of data visualization, understanding your data, choosing the right visualizations, and catering to your audience’s needs are the pillars of success. So, as you embark on your data visualization journey, remember these three key considerations to create impactful and meaningful data dashboards.