Data visualisation and data visualisation literacy is increasingly becoming an essential skill both for creators and consumers of data visuals, enabling businesses to make high level decisions based on complex data sets. By transforming raw data into visually appealing and easily digestible formats, data visualisation allows for better understanding and communication of business insights. If you’re new to the world of data science and data visualisation, this article will detail how Power BI training can help you visualise your data while sharing five data visualisation best practices for this business intelligence tool.
Select the Right Visualisation Type
The first step in creating effective data visualisations is choosing the appropriate chart or graph type for your data. Each type of visualisation serves a unique purpose and communicates specific information, making it essential to match the visualisation with the data at hand. For example, bar charts are ideal for comparing categorical data, while line charts are best for displaying data trends over a nominal period of time. If in doubt, there are plenty of free resources on Power BI chart types to determine the most suitable visualisation for your data. Power BI training also sets you up for easy success when it comes to selecting the right visualisation type, as you’ll learn basic visualisation and data methodologies throughout the course.
Focus on Simplicity & Clarity
It can be tempting to create complex and intricate visualisations to showcase your Power BI expertise. However, the primary goal of data visualisation is to convey information in a clear and concise manner, usually to inter-disciplinary demographics who may not all have the same skill sets. Avoid using unnecessary elements, such as excessive colours, shapes or patterns, as these can cause confusion and distract the viewer from the main message. Instead, strive for simplicity in design while ensuring all relevant information is accurately represented and easily understood.
Prioritise Readability & Accessibility
As data visualisation aims to communicate information effectively, it’s vital to ensure your visualisations are readable and accessible to a wide audience. This involves using legible fonts, appropriate font sizes and high-contrast colour schemes to promote clear visibility. Depending on the audience or organisation you’re presenting your visualisation to, you may also need to consider the needs of colourblind users by avoiding colour combinations that may be difficult for them to distinguish. Power BI offers colourblind-friendly palettes that can enhance the accessibility of your visualisations for colourblind individuals.
Employ Consistent Design Principles
Consistency in design plays a crucial role in the overall effectiveness of data visualisations. When creating multiple visualisations for a report or dashboard, it’s important to maintain a consistent style so your data presentation appears seamless throughout. This includes using similar fonts, colours and formatting across all visuals, as well as adhering to general design guidelines such as proper alignment and spacing. By adhering to a cohesive design language, your visualisations will not only appear more professional, but also be more easily interpreted by the viewer.
Tell a Compelling Story with Your Data
An essential yet underrated aspect of best practice in data visualisation is storytelling. Beyond merely presenting data, your visualisations should tell a compelling story that engages the viewer and highlights relevant insights. Achieving this involves considering the context and purpose of your data, as well as the audience you’re addressing. Ideally you should try to craft a narrative that highlights key trends, patterns or outliers and guides the viewer through the data in a meaningful and insightful manner.
By following these data visualisation best practices and seeking out Power BI training, you can create insightful, engaging and effective visuals that enable better decision-making for your organisation. When visualising data, always strive to select the right visualisation type, prioritise simplicity and clarity, ensure readability and accessibility, employ consistent design principles and try to tell a compelling story with your data.