How do you present engineering insights with data visualization software?

1 Why use data visualization software?

Data visualization software is a powerful tool for exploring, analyzing, and presenting data. It can help you to uncover patterns, trends, and outliers in your data, compare and contrast different scenarios and outcomes, as well as highlight key findings and recommendations. Additionally, data visualization software simplifies complex information and concepts to engage and persuade your audience with visual storytelling. Moreover, it can save you time and effort by automating tasks such as data cleaning, formatting, and exporting.

2 What are some common data visualization software for mechanical engineering?

When it comes to data visualization software for mechanical engineering, there are a variety of options to choose from. MATLAB, for example, is a programming environment that allows users to create and manipulate data, perform calculations, and generate various types of plots and graphics. Excel is a spreadsheet application that offers basic and advanced functions for data analysis and visualization such as charts, tables, and pivot tables. Tableau is a business intelligence platform that enables users to create interactive dashboards and reports with drag-and-drop features and data connectors. Power BI is a cloud-based service that integrates with Microsoft products and other sources to provide data visualization and analytics capabilities. Python, on the other hand, is a general-purpose programming language that has many libraries and packages for data science and visualization such as pandas, numpy, matplotlib, and seaborn.

3 How to choose the right data visualization software for your project?

Choosing the best data visualization software for your project depends on several factors, such as the type and size of your data, the purpose and audience of your presentation, the level of interactivity and customization you require, and the budget and resources you have available. To make sure you pick the right software for your project, ask yourself questions such as what are the main questions or problems you want to answer or solve with your data? What key messages or insights do you want to convey? What are the best ways to display your data to support your messages or insights? How do you want your audience to interact with your data, if at all? And how much time and money can you spend on learning and using the data visualization software?

4 How to design effective data visualizations for mechanical engineering?

When selecting data visualization software for your project, it's important to design your data visualizations in a way that is clear, accurate, and engaging. Consider choosing the right type of chart or graph for your data, like bar charts, line charts, scatter plots, pie charts, or histograms. Additionally, be sure to use appropriate colors, fonts, labels, legends, and titles to make your data visualizations easy to read and understand. To avoid clutter and distractions, such as unnecessary details or decorations, use consistent and coherent formats and styles across your data visualizations. You can also use annotations, captions, or narratives to explain your data visualizations and highlight the main points. Finally, make sure to test and refine your data visualizations with feedback from your audience or peers.

5 How to present your data visualizations with confidence and clarity?

Delivering your engineering insights with data visualization software requires confidence and clarity. To ensure a successful presentation, it is important to prepare and rehearse beforehand, and anticipate questions or objections from your audience. Additionally, create a logical structure for your presentation, using transitions and signposts to guide the audience through your data visualizations. Utilize verbal and non-verbal cues to emphasize and reinforce your points, as well as storytelling techniques to engage and persuade the audience. Invite feedback from the audience and thank them for their attention.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?