Data Visualization Series — 1. Principles for Accessible and Inclusive Data Visualization
Introduction
Data visualization is the study of creating visual representations of data. It’s not just about “making graphs”, but about transforming this information into visual elements that are quicker and easier to interpret and consume.
Data can generate different interpretations, and how it is presented — especially in dashboards — has been crucial for organizations to understand their scenarios better. In business, data visualization supports technical and business teams by identifying trends, monitoring KPIs (Key Performance Indicators), and translating complex patterns quickly and efficiently.
Benefits of Data Visualization in Business
- Operational Efficiency: Reduces the time needed for analysis by providing data that is already organized, interpreted, and easy to understand.
- Accuracy and Quality: Reduces the need for manual manipulation of data, reducing errors and improving the quality of information.
- Identification of Relationships and Patterns: Complex data starts to make sense when presented in graphs and other visualizations.
- Trend detection: Reveals trends that can be exploited for competitive advantage.
- Improved Decision Making: Facilitates the understanding and rapid absorption of information, improving the quality of decisions.
Consequences of Not Using Data Visualization
On the other hand, the absence of effective visualization can result in:
- Increased labor costs: More hours are needed to build indicators and perform analyses.
- Manual failures: Disconnected and erroneous interpretations of data can occur more frequently.
- Delays in decision-making: Important decisions can be delayed due to incorrect interpretations and delays in data analysis.
Data Visualization Tools
There are many tools on the market today to support data visualization — Looker Studio, Power BI, Tableau, Qlik Sense, and QuickSight are just some of them. However, in addition to knowing how to use these tools, it is essential to understand how to organize data and tell the story it reveals. This is the only way to define the essential elements and choose the most appropriate graphics.
In advanced analytics, Data Science professionals develop machine learning algorithms to better compile essential data into visualizations that are easier to understand and interpret, allowing for deeper and more accurate insights, and further enhancing the benefits of data visualization.
Fundamentals of Good Data Visualization
1.1 The way to good data visualization
As you can see, data visualization facilitates more objective decision-making by providing an effective, fast, reliable, understandable, and accessible view. Its role is to transform complex data into clear and intuitive visual representations, so that a wider audience, regardless of their level of technical expertise, can explore the information and identify trends, patterns, and discrepancies more quickly and accurately.
But to ensure that the data does not generate doubts and that it dialogues with the audience, a data visualization needs to be guided by the right questions, such as: What is the purpose of the visualization? Will it guide the strategy? What business questions will it answer? Will it be a dashboard with automated and objective updates, or would a more periodic detailed analysis be more useful?
Several other factors also have an impact on the format, the organization of the data, and the structure of the tools used. For example, it is important to determine whether the visualization will be designed to be displayed on a screen, whether it will be exploratory or static, and how often the data will be consulted.
In addition, it is essential to consider who the visualization will be aimed at. Different audiences, such as the board of directors, project management, and operations, have different needs. Understanding who will be using the information will allow you to adjust the form of language and the appropriate level of detail.
1.2 Essential Elements of a Graph
Although there are countless ways to present data, it is essential to understand the specific needs of your audience and the message you want to convey. Choosing the right type of graph ensures that the information presented is clear and accurate. To achieve this, some essential elements must be present in any chart:
- Title: This should be clear and descriptive, telling you exactly what the graph is about.
- Axis of Abscissas (Horizontal): Must be labeled with a title that clearly describes the variable shown.
- Ordinate axis (Vertical): Like the abscissa axis, it must have a clear title describing the corresponding variable.
- Legend: Fundamental when there are multiple data series or categories, helping to visually differentiate the elements of the graph.
- Data source: Ensuring the credibility of the information presented is essential. Always indicate the source of the data.
Example: Combination chart
The graph above combines two types of graphs, columns, and lines, which is why it can show one or two axes, as in the image, so when designing a graph, it is necessary to examine and ensure that all the information is covered. Good graphics are powerful tools for conveying information quickly and clearly. They guide decision-making by making it easier to understand the data presented. On the other hand, bad graphs are difficult to interpret and can lead to erroneous conclusions, distorting the veracity of the data. In the next post, find out how to choose the type of visualization best suited to your needs.
Profile of the Author: Mariana Brandão | With a degree in Bioprocess Engineering and Biotechnology from UFPR and a passion for numbers, I seek to transform the way decisions are made through the power of data. I’m currently a Business Analytics Consultant at DP6.
Profile of the Author: Andressa Viana | With a degree in International Relations from UFF, I work professionally as a Business Analytics Consultant at DP6. I believe that data visualization plays a key role in understanding the world and the times in which we live.
Profile of the Author: Luana Moura | I have a degree in Library Science from UDESC and a Master’s in Information Science from UFSC. I’m dedicated to collecting, analyzing, and structuring data to enable smarter decisions. I’m currently a Business Analytics Consultant at DP6.
