Data Visualization: Doing it The Right Way

June 20, 2022

Graphical depiction of information and data is known as data visualization. Data visualization tools make it easy to examine and comprehend trends, outliers, and patterns in data by employing visual elements like charts, graphs, and maps. These tools and technologies are critical in the Big Data environment to analyze enormous volumes of data and make data-driven decisions. It is a practical and straightforward approach to conveying information to a broad audience using visual data. This practice can also assist businesses in determining which factors influence customer behavior, identifying areas that need to be improved or given more attention, making data more memorable for stakeholders, and forecasting sales volumes.

Effective data visualization is the decisive step in data analysis; key insights and messages are lost without it. While it is easy to make fun of erroneous or misleading charts, they can have dire consequences. Bad data visualizations cause audiences to misinterpret the true data, leading to poor business decisions. As a result, it is critical to always keep the best practices in mind when creating visualizations.

Best practices for data visualization:

There a mainly 6 best practices for data visualization, they are:

  1. Knowing the Audience
  2. Using the right type of chart
  3. Choosing the layout carefully
  4. Adding comparison values
  5. Being careful with colors
  6. Being consistent with labeling and data formatting
  • Knowing the Audience: Dashboards must begin with a target audience in mind. Who is the dashboard’s intended audience, and what information do they require? Understanding the dashboard’s users will help us create a product they enjoy using. A dashboard that shows data analysis should bring value. For example, a user should not have to perform additional computations to obtain the required information because everything he needs will be displayed on the charts. One should always strive to put themself in the audience’s shoes and create dashboards. The fact that most dashboards have several viewers adds to the complexity. Serving a diversified audience is difficult. As a result, one should strive to prioritize the audience so that disagreements may be managed more effectively. A CEO requires a dashboard that summarizes key performance indicators to make business choices. In contrast, a social media manager needs a dashboard that emphasizes critical metrics from social media platforms like LinkedIn, and Facebook, to assess campaign performance and gaps. Before beginning, it is necessary to understand the dashboard’s context to ensure it supports the user’s goals and objectives.
  • Using the Right Type of Chart: The importance of selecting the appropriate data visualization types cannot be overstated. It is critical to know what kind of information we want to convey before choosing a data visualization suitable for the job. A missing or wrong chart type might sabotage all the work that has been done.
      • Bar charts help display discrete data or the relationship between parts and the total. A bar chart should be used to compare categories or make broad conclusions about the data swiftly. Such charts are easy to understand, clear, and compact.
      • A stacked bar chart is a graph that employs bars to display comparisons between categories of data while also breaking down and comparing parts of the total. They effectively highlight the total while also indicating how the total for each category value is broken into parts.
      • Line charts are an excellent tool for communicating changes over time. Data should be connected using line charts on an interval scale to show how data changes at equal time intervals.
      • Scatter plots to see outliers easily. Correlation is found between two variables. When the data is shown on a graph, the correlation is positive, negative, or nonexistent.
      • Maps visualization is a technique for analyzing and visualizing spatially connected data and presenting it as maps. This type of data presentation is more straightforward and intuitive. The distribution or proportion of data in each region can be seen visually.
      • A tree map is a data-visualization technique for large, hierarchical data sets. They capture two types of information in the data, the value of individual data points and the structure of the hierarchy.
      • Box plots help in examining the distribution of data. Each attribute element has its box plot. The minimum, first quartile, median, third quartile, and maximum values are displayed in each box plot.
      • Sparklines works well when you have a lot of metrics, and we want to show only the trends. They are rapidly scannable and very compact.
      • Waterfall Chart shows how an initial value is increased and decreased by a series of intermediate values, leading to a final cumulative value shown in the far-right column.
  • Choosing the layout carefully: People naturally tend to look at the upper-left corner of a page first. The usual rule is that the essential information should be displayed first, in the upper left-hand corner of the screen. The placement of charts on a dashboard is the next step. Users will readily discover the information they require if the dashboard is visually structured. Poor layout causes users to think more before grasping the point, which causes a lot of trouble. At a glance, the main trend should be evident. After this eye-opening first look, one can move on to more detailed charts. We should never forget to organize the charts by theme and set comparable metrics close to one another. In this way, the users do not need to diverge their attention while looking at the charts.
  • Adding comparison values: By comparing current statistics to historical values or aims, comparison values provide context for them. In visualizations, comparison values distinguish between good and bad performance at a glance. To elicit a response, the viewer must be able to see how the performance compares to something concrete, such as a goal or a previous period’s standard. To help the audience better understand the statistics they are seeing, we will want to provide metrics in contrast to dynamic thresholds in our data visualization. The more context they have, the easier it will be to determine where the action is needed.
  • Being careful with colors: This is one of the most significant best practices for dashboard design. When it comes to color, there is an option of staying true to the company’s identity, for example- the same colors, logo, or fonts. Experimenting can also be done with a completely alternative palette. The crucial thing is to keep things consistent and avoid using too many distinct colors. One can explore with gradients after selecting two to three colors. Most colors should always be toned down. Across all charts, we should utilize the same color for matching items. As a result, consumers’ amount of mental work is reduced, making dashboards more understandable. There are multiple color types that can be used to convey specific information through visuals.
    • Sequential Colors
    • Divergent Colors
    • Categorical Colors

Sequential color is used to show the scale. They are also a wonderful technique to make the dashboard look more attractive. A simple gradient may refresh a design, emphasize components, and give an otherwise flat image the feeling of depth.

Divergent Colors pair sequential schemes based on two different hues so that they diverge from a shared light color, for the critical midpoint, toward dark colors of different shades at each extreme.

Categorical colors help users map non-numeric meaning to objects in a visualization. These are designed to be visually distinct from one another.

  • Being consistent with labeling and data formatting: The primary goal of a dashboard is to help the user extract critical information immediately. It is vital to ensure that the labeling and formatting of KPIs and metrics are consistent. It will generate confusion and raise the risks of making mistakes if the formatting or labeling for KPIs is drastically different. To create dashboards that succeed, one must be completely consistent. Key points to keep in mind:
    • Text aligned to left
    • Numbers aligned to the right
    • No digits after the decimal
    • Adding suffix & prefix where required (e.g.- %, $ etc.)


An effective data dashboard should be visually appealing while remaining visually balanced and astute while remaining simple, accessible, user-friendly, and targeted to the goals and the audience. It should always be strived to develop a nice and tidy dashboard that aids visitors in gaining better comprehension of facts and aids in decision-making.

About Viz-CoE

With an intention to lead the way in exploring and adopting new technologies, tools, techniques, or practices in the area of visualization, RoundSqr has kick-started a new initiative called “Viz-CoE”, Visualization Center of Excellence. Contributions from our subject matter experts, clients, partners, industry leaders, colleagues, and interns through perspectives, training courses, success stories, and opinions bring this initiative to life.