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How can you present hands-on training evaluation results with data visualization tools?

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Hands-on training evaluation is a crucial step to measure the effectiveness of your learning interventions and identify areas for improvement. However, presenting the results of your evaluation can be challenging, especially if you have a lot of data to share. How can you make your evaluation reports more engaging, clear, and actionable? One way is to use data visualization tools that can help you create and display graphs, charts, dashboards, and other visuals that can communicate your findings and recommendations in a compelling way. In this article, you will learn how to use data visualization tools to present your hands-on training evaluation results.

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Mark Johnson

LinkedIn Top Voice | AI & Google Cloud Architect | TechSnobs helps growing healthcare startups,| scale 5x faster with…

1 Choose the right tool

When selecting a data visualization tool, there are many factors to consider, such as the type and amount of data, the purpose and audience of your presentation, the features and functionalities needed, and the cost and accessibility of the tool. Popular options include Tableau, Power BI, Google Data Studio, Excel, and Canva. Exploring and comparing different tools can help you find the one that best meets your needs and preferences.

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Mark Johnson

LinkedIn Top Voice | AI & Google Cloud Architect | TechSnobs helps growing healthcare startups,| scale 5x faster with optimized Cloud & AI solutions,| boosting team efficiency by 50% Cutting operational costs by 45%
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When I think about selecting the right data visualization tool I believe what I'm presenting should tell a very clear story about the results. It's also a great idea to have an interactive tool that allows your audience to explore and manipulate the data at their own leisure.

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2 Prepare your data

Before you start creating your visuals, you need to prepare your data for analysis and presentation. This means cleaning and organizing your data by removing errors, duplicates, outliers, and irrelevant information, transforming and aggregating the data through formulas, calculations, filters, and groupings. Additionally, you should define and measure your key performance indicators (KPIs) using metrics such as completion rate, satisfaction score, knowledge gain, skill transfer, and business impact. It's important to analyze and interpret your data by looking for patterns, trends, correlations, and causal relationships. Doing so will help you ensure that your visuals are accurate, consistent, and meaningful.

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Mark Johnson

LinkedIn Top Voice | AI & Google Cloud Architect | TechSnobs helps growing healthcare startups,| scale 5x faster with optimized Cloud & AI solutions,| boosting team efficiency by 50% Cutting operational costs by 45%
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In my experience I would suggest having a standardized process for cleaning and labeling your data is very important as it allows your audience to understand the data that's being presented to them. Using colors and annotations also help add more context to explain unusual trends.

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3 Select the right visual

When selecting the right visual for your data and message, it's important to consider the type of data, level of detail, and intended effect. For example, bar charts are great for comparing categorical data or showing changes over time, while pie charts are good for showing proportions or percentages of a whole. Line charts are great for showing trends or fluctuations over time, scatter plots are good for showing relationships or correlations between two variables, and histograms are ideal for showing frequency distributions or ranges of values. Dashboards are also useful for displaying multiple KPIs or metrics in one place. Ultimately, selecting the right visual will help you communicate your message effectively.

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Mark Johnson

LinkedIn Top Voice | AI & Google Cloud Architect | TechSnobs helps growing healthcare startups,| scale 5x faster with optimized Cloud & AI solutions,| boosting team efficiency by 50% Cutting operational costs by 45%
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Since I like to make my visualizations simple to understand, I typically will try different options such as pie charts, bar charts and heat maps which allow me to get some feedback from my audience. I've also learned In some cases having a slide deck for live data will not add too much value for the team, So I'll end up creating a live dashboard to enable the team to have access to real-time data.

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4 Design your visual

The final step is to design your visual to make it appealing, readable, and understandable. This means using colors, fonts, shapes, and icons that are consistent, attractive, and appropriate for your data and audience. Labels, titles, legends, axes, and annotations should be informative, concise, and accurate. Additionally, scales, grids, and reference lines should be relevant, proportional, and aligned. Finally, filters, interactions, and animations should be useful, intuitive, and engaging. By doing this you can enhance your presentation and capture your audience's attention.

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5 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?

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How can you present hands-on training evaluation results with data visualization tools?

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5

1 Choose the right tool

2 Prepare your data

3 Select the right visual

4 Design your visual

5 Here’s what else to consider

Training

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How can you present hands-on training evaluation results with data visualization tools?

1

2

3

4

5

1 Choose the right tool

2 Prepare your data

3 Select the right visual

4 Design your visual

5 Here’s what else to consider

Training

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