Data Storytelling Predictions for 2022 and Beyong
In this episode, we are going to be talking about data storytelling predictions for the coming 5 years. I thought this was a good topic to discuss right now since it will be the beginning of 2022 when this episode is published and live for you to hear.
There are two particular predictions that have stuck out to me and grabbed my interest. So I’ll focus on these two for this episode.
What You’ll Learn in this episode
- The role of AI and ML in data storytelling
- How the metaverse can impact data storytelling
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If you enjoyed this episode, check out this episode where I talk about the different types of data communication skills.
In this episode, we're going to be talking about data, storytelling predictions for the coming couple of years to five years. I thought this was a good topic to discuss right now, since it will be the beginning of 2022. When this episode is published and live for you to hear, there are two particular predictions that have stuck out to me and grabbed my interest. All focus on these two for this episode. The first one is using AI to generate data stores. Communicating an effective story involves emotion, context, and understanding of who your target is in order for you to create a relevant and engaging narrative. And this is already a complicated and often misunderstood task, even for humans. And I think our technology with AI is not there yet to do this effectively. So we'll see tools come out that can claim. That they can generate data stories automatically, but I am skeptical if they're good enough in quality to use out of the box, meaning I think even if they can give you outputs, you may have to actually adjust and tweak them in order for you to create an effective data story for your target audience. And later in the season of the podcast, I'll talk more about why you should be creating a data story that is customized for your target audience. Now I've been exploring a tool that uses open AI, GPT three technology, and I've looked at the outputs and I think they provide a good starting point for crafting data stories. I am new to this technology, but from others who have used it, and they've used it much longer than. They say this technology has actually come a long way and has improved significantly. So we will see what happens in the next few years. The tool. I tested out, provides the option of giving you multiple versions and it encourages you to edit and tweak the content. So, you know, I've just started to play around with this though. By the way you'll see, this is used not only in the data space, but also in other contexts, like generating books, plays scripts, and so on. I really doubt the quality of this AI generated content will be good enough to win awards, at least for the next five years. Maybe. So, you know, this is the time here that we're focusing on for this. However, I do think there's room for AI to automate other parts of the data process, like structuring, analysing data, you know, other things like that that can help free up more of a data practitioners time so that they can focus on selecting the relevant insights and crafting a story with. Particularly if AI can help find deeper insights about your target audience or customers. I think it can help you make an informed decision and inspire you to craft a narrative that will resonate with your audience because you understand that. This is called augmented intelligence. And in the context of data analytics, it's called augmented analytics. And this is when humans are involved, aiding and reviewing the outputs of AI to work together, to make a better product. According to Gartner, they predict that by 20 25, 70 5% of data stories will be automatically generated using augmented intelligence and machine learning rather than generated by data analysts. The next trend you probably saw coming. And I talked about this a bit with Sadie on her podcast, data bites. When she asked me about my predictions for the upcoming year, and that is doing data storytelling in the. Digital augmented and virtual reality. I'm particularly excited by this opportunity to immerse our audience into our stories. A big concern with data storytelling and presenting data in general is how to captivate our audiences, limited attention and engage them. You probably already have noticed even during in-person presentations, that your audience may be distracted. They may be on their phones or on their laptops. Multitasking while they're listening to your presence. Now with virtual presentations, the likelihood of that happening is even higher. They may not even be at their computers. Are very likely multitasking and not paying attention now with the metaverse, we have this opportunity to immerse, engage and captivate our audience even more. This will hopefully make this a more memorable experience for our audience. Not because the metaverse is novel and exciting, but also because more of their senses are engaged in the data storytelling experience, they are less likely to be multitasking and they're more likely to be paying attention. So data storytelling in the metaverse will require some skill and thought to craft an effective and engaging one. And it's going to be really exciting to see what people come up with in the metaverse.