How can you use animation to tell your data's story?

One thing I found helpful to remind myself is that we need to know who our audience is. In a room full of analysts and data experts, you can get your point effectively across with a simple table or static chart; animations may only be a distraction to the narrative. However, if your audience is unfamiliar with your data, or if it is complex and requires 'baby steps' to appreciate the data, then simple animation may be useful.

Avoid animations as much as possible. Simplicity is key. Especially when it comes to data visualization. There is one exception. If animation can help you tell a better story in a limited timeframe vs static images, use animation. For example, in my previous posts, I used animation to visualize how multiple variables have changed over a long period of time. If I didn’t use animation, they would have been multiple charts on a crowded dashboard.

Before presenting data: - Research your audience's background, knowledge, and preferences. - Balance simplicity and complexity to cater to different familiarity levels. During presentation: - Use animations purposefully; avoid distracting effects. - Prioritize clarity in your data storytelling with clear labels and context. After presentation: - Seek feedback to refine your approach for future presentations. Stay updated on data tools and ensure accessibility. Practice with visual aids and be flexible in real-time for effective communication.

Animation is a powerful technique in data visualization that involves the use of moving elements, transitions, and dynamic effects to enhance the understanding and engagement of data. It can be used in various data presentation contexts, including reports, presentations, and interactive dashboards. Animation helps in highlighting key insights, simplifying complex data, and guiding the viewer's focus. In today's data-driven world, effectively conveying complex information is crucial. Data visualization has become the go-to method for making data understandable and actionable, but to truly make an impact, consider incorporating animation into your data storytelling toolkit.

Showing a number on the screen doesn't tell you anything. If the data is visualized in charts or bars audience will have better perspective on the data and can interact with it for informed decisions.

Some practices that might be helpful here 1. Keep it simple. More complicated means more work for you and more work for your audience in understanding the story you're trying to tell 2. Take feedback early - Check in with your team and others. See what they think of your visualisation. Notice what noticed first, how did their attention travel through your visualisation.

Animating data involves using tools like data visualization software, coding languages (e.g., JavaScript or Python), or specialized animation software to add motion to data visuals. Here's how: Choose the Right Tool: Select a data visualization tool that supports animation. Popular choices include D3.js, Tableau, Power BI, and Python libraries like Matplotlib or Plotly. Data Preparation: Ensure your data is well-structured and clean. Define which aspects of your data will animate, such as time-based changes, transitions, or specific data points. Select Animation Type: Determine the type of animation that suits your data. Common choices include transitions (data smoothly changes over time), keyframe animations (specific data points move).

I believe using Animation should be approached cautiously, especially when presenting to senior executives. At the same time, it can accurately surmise insights if they're well utilised.

There are many tools available to animate data like Excel, PowerPoint, Google Sheets, Tableau, Power BI, Adobe Animate, Plotly, D3.js, Keynote, Prezi, Google Data Studio for animating data. But Power BI is one of the most common.

D3.js: A powerful JavaScript library for interactive data animations. Tableau: User-friendly tool with built-in animation features. Power BI: Microsoft's tool for data visualization and animation. Plotly: A Python library for creating interactive visualizations. Matplotlib: Python library with animation capabilities. JavaScript Animation Libraries: Libraries like GSAP for custom animations. Adobe After Effects: Professional software for polished animations. RawGraphs: Open-source tool for animated visualizations. Tumult Hype: Mac-specific app for creating HTML5 animations. P5.js: JavaScript library for creative coding and animation.

Tableau is an excellent tool for animation for the main reason that it makes it so easy. In the majority of use cases, there is only a requirement to switch animation on and your dashboard will then automatically show animations as you interact with it (such as when using filters). For more advanced animation you can also create calculations within the tool to achieve a certain effects but for most business dashboard use cases, this is unnecessary.

I've used these tools to create simple animations 1. Microsoft powerpoint - Very simple to pick up and offers advanced capabilities with few clicks 2. Matplotlib animation classes in python allow for animation to be easily created in Jupyter notebooks

Consider the 8-second rule: The average human attention span is 8 seconds. So, your animation should capture the user's attention within the first second and tell the key message in the following 7 seconds. Before finalizing, ask a colleague or someone unfamiliar with the subject: "Can you get the message in 8 seconds?" If the answer is "yes", then congrats! You're good to go!

Do multiple tests together with your colleague within your function or not. Gather feedback early on, stay ahead. Then improve before handing it over or show it. Still make sure that it has everything you need to show to your audience.

A random walk in the Science Centre Singapore gave me a fresh perspective: Let your audience experience data. Do you know how it feels like to be in an earthquake? Or inside a hurricane? Through experiences, theories and data visualization can give a more profound understanding in the minds of viewers.

If at all using animations, keep them simple. Too many moving elements may distract the audience and your data story may fail its purpose.

Don't animate everything. You can use animation for emphasis, for conveying information in a way that makes it easier to understand. Overusing it will only reduce its effectiveness. It's an important technique which, when used right can deliver a big impact in your data story.

It all depends on the context and who the audience are to use animation. Also if presentation requires a human touch then animation can be used to enhance it.

Consider the following things : Purposeful Narrative: Clearly define the story you want to convey, do not use animation for the sake of it. Use it as a means and make sure it does not distract from the story you're trying to tell Data Simplification: Animation can do wonders when you want to simplify complex data. Transition and Timing: Many beautifully crafted visuals go down the drain or struggle with diluted impact because of an out of sync transition, re-check your deliverables end to end before delivery, ask for time, assert your need for time. If you're pressed for delivering presentations within unreasonable timelines then make sure you take your talent to a place that values data and doesn't churn calibrated garbage.