How do you stay current with data storytelling best practices and standards?

For me, data storytelling encompasses three key elements: data, narrative, and visuals. Because the field of data storytelling is still relatively new, I like to follow experts and influencers in each of these three areas. I have learned good practices and concepts from many of the data viz experts listed here. Nancy Duarte's books (Slide:ology, Resonate, Data Story) place more emphasis on presentations and business communication, which is a great complement to these other data viz experts. The narrative element and the psychology behind it is often overlooked, and that's what I focused on in my own book, Effective Data Storytelling (Wiley).

For me its a matter of understanding the customer and audience. There is no magic script of formula to generate an amazing data storytelling output. The way is understand the context and feel the audience. Some insights and ideas you can correlate with books and your personal research library, but in the end of the day this all falls into the Chief Attention Officer (the guy who can generate more attention through stories)

You can follow experts and influencers to learn perspectives but stay away from blindly copy-pasting and always relying on second-hand sources. You develop expertise by trying, failing, toiling and succeeding. So, get to work and build data stories!

As a data storyteller, one needs to be aware of FAD (Flow, Audience and Data). Missing out on any of these segments could prove to be disastrous. Latest trends, increased focus on Purpose, Narrative and using contemporary examples help in connecting with the audience. Personalize your message to the audience. Using social media or professional networking site like (LinkedIn) to understand the sample profile of the audience and see how best you can customize. Practice the talk-track and allow spaces to customize.

In data storytelling, there always is a hidden story thread with all the pools of data and research. So when you slowly unravel information from different sources, find that common hidden thread, sometimes it’s obvious and sometimes it isn’t. When it’s obvious look for information and data that others have missed, add a perspective, and in the less obvious ones, unravel the elements that stand out and you have your story. The more you dig the more you get something unique for your story.

One tip I recommend is to go back and re-read some of these key books and articles. As you advance in your data storytelling abilities, you’re going to find different techniques and concepts jump out at you. A tip you overlooked in your first pass of the content will become more significant as you become more ready for it. I have been told by many readers of my book, Effective Data Storytelling, that they have re-read it and picked up new insights and strategies. Your evolution as a data storyteller should be dynamic, not static.

Reading is definitely one of the best ways to stay up to date with the changes that you come across in your data. Storytelling and reading are inseparable. The more you read, the better you get! Also, the re-reading advice shared by Bren Dykes is something I recommend myself. I've done it before, it's life changing.

Reading relevant books definitely helps. Though along with data storytelling you should also read books on data analysis as it helps in knowing how you can add data to your stories effectively. Also to stay updated with current trends, you can read latest blogs on data storytelling by prominent experts. Reading research based on data storytelling can also give comprehensive insights on what resonates the best with the audience.

I am sharing my personal story/approach on how to become a self taught data storyteller. - Create a library of data storytelling books such as Data Story- Nancy Duarte, Winning the room - Bill Franks, Beyond Bullet Points - Cliff Atkinson, Everyday Business Storytelling- Janine Kurnoff and Lee Lazarus , HBR guide to persuasive presentations-Nancy Duarte and The power of data storytelling- Sejal Vora. - Create snippets/ blogs to explore your understanding about data storytelling - Try to volunteer in your capacity to share/ teach your learning’s that makes you an data storytelling expert

Books and articles are a great start to get the basics and fundamentals. However, there is a pitfall to this approach if you continue to academic ONLY in your approach. Apply the concepts you learn and find out what works and what does not. Success on the field will depend on application and contextual knowledge then general best practices that are offered in books and blogs.

Watch and learn from the experts and then incorporate what connects with you. With the advancements in AI things change fast and what was cutting edge last week may be old and so yesterday tomorrow.

Taking courses is one of the best ways to upskill. Make sure that you vet the credentials of your instructors as the last decade has been the rise of FAKE Gurus! Take the knowledge and get started with building something that is actually useful to people. you can take 100 courses and read a thousand books but you will get good only BY DOING!!!!

I am a huge believer in continuing to expand your knowledge through courses, workshops, and writing groups. The beauty of storytelling is that it is universal. You need to solve a problem—it doesn't matter if it's for a fiction book, an article, or data storytelling. If you decide to take a course in storytelling, don't limit yourself to just data courses—one of the best things I did for my writing career in business, marketing, and tech was to take a course on book writing!

We never stop learning and we never stop upscaling. courses and workshops are one way of doing them, but you must also first and foremost identify your needs and which trainer meets them best because these courses are time consuming, and some workshop might be a financial investment to some. Know your needs then meet them.

As one of the facilitators at StoryIQ's Data Storytelling for Business, I'm truly honored to see our course featured among the recommended options. At StoryIQ, we prioritize practicality, ensuring that our courses equip participants with knowledge and skills that can be immediately applied in real-world work environments. Through hands-on workshops and activities, we create an environment for immediate practical application of learned concepts. Thank you for acknowledging our commitment to valuable, real-world learning experiences. We look forward to continuing to empower individuals with the skills they need to excel in data storytelling.

Looking for a way to make an impact? Get in touch with local charities or non-profits and seek to help them visualize how donation dollars turn into impact. Many NPOs would LOVE to have you volunteer to tell unique and meaningful stories with a surprising amount of creative freedom and low stress. Build your portfolio and practice with purpose!

When it comes to data storytelling, one thing that’s always essential is understanding your audience. If you observe the current trends that resonate with the audience and curate the data story accordingly, you can ask specific questions while seeking feedback from your audience. For example if at present videos are trending more than blogs then you can curate a visuals focused interactive data story based video and then seek feedback. Your audience can tell what they liked, was the data easy to understand and did they find the story interesting! Based on the feedback, keep practising to ace data storytelling!

I highly encourage you solicit constructive criticism for your work and have the appetite to tolerate opposing viewpoints. Take them into consideration with logic and avoid responding to them via emotions.

An easy way to elicit feedback is to work on what the people need but don't know they did so. Look and ask around to find out what kinds of solutions people are awkwardly cobbling together, and if they can be solved through enhanced data visualisation approaches.

Practice does make perfect! And we can never evolve without feedback, so build the story/image you want of yourself, and try to modify it until it meets your needs. That is exactly like writing a draft - you need to re-read and edit until you reach the result you want. Sharing can be online and offline, luckily for us nowadays.

Something often missing in the world of data storytelling is humour! Data can be dry, charts can be cold, and statistics can be snooze-worthy. Storytelling brings the data to life, but storytelling with a dash of humour can turn the data tale into a captivating, unforgettable journey! No data dullard me. Humour doesn't mean making fun of the data; it means finding the human element within it. I try to share relatable quirks, celebrate data victories, and laugh at the occasional data blunder! ?? I always try to add a pinch of humour to the data storytelling recipe. I can see my audience leaning forward to listen, and they usually seem to recall what I present!

There are two important things to keep in mind to make the experimentation pay off. Is the new technique, methodology, or style appropriate for the audience? Does is speak their language and is it something that will stick with them. Is it memorable? Secondly, does it fit your style and can you deliver it well? It is disappointing to see someone try something different and not deliver it well.

After you read, explore and apply the DS principles and techniques, feel free to share your expertise through presentations, training’s at colleges/ community and act as a mentor to evangelise this new soft skill globally. It’s no more luxury but a mandate to be a data literate for democratising data through storytelling. #lets data storyteller

I've always believed that great examples are some of the best teachers. Working backward to see how a data story is put together, be it a narrative or a visualization, can be inspiring. Browse collections like the Sigma Awards or Information Is Beautiful and see how nominees or winners are telling visual stories with data. Look for examples in your local news media. And don't hesitate to ask how it's done. You might be surprised by the generosity of your fellow storytellers.

Connecting with the broader storytelling community is vital to stay up to date with storytelling. Remember the world is wide enough for all storytellers and aim to support over snuffing out the light of others. You can be an expert in your own right, and still appreciate different approaches by others. I follow a LOT of people but some immediate names that come to mind are Mico Yuk (The OG data storyteller for BI), Brent Dykes, Bill Shander, Phil Brunkard, Cinny Little and many more. Follow the followers to find other like-minded storytellers.

Data story telling is about telling a compelling story that people care about. The easiest way to find relevance through your data story if you have ideally hit one of these three user objectives. 1. Making/Saving money $$$ (This is why 67% of the dashboards are financial dashboards. Money management is a core tenet to economics and business and your audience will listen to you attentively) 2. Saving time. Time===Money. This is why the second category of data stories that find relevance is how people can optimize processes and save time. 3. Alignment of interests. When you build any analytical story you will find a compelling audience for it if you base it from an emotional relevance and how it interests/engages the audience.

Data can be acquired by many different means: Specialists, research institutes, and social analysis, for example. But for me, the real magic lies in how to turn this data into stories. Data is a powerful thing to base your insight on, as it shows the idea came from a real tension, but data is nothing but numbers until we turn that into something that connects to our audience. We're all humans, we live by telling and listening to stories, so treat all the data as human insights. Look for the feeling they display, what can they bring to a human level? Search deep into what your story makes you feel and it's more than likely that it will make others feel the same.

While the data provides the foundation, the narrative weaves it all together. Strive for a balance between analytical rigor and creative storytelling. Limit the use of visual aids. While your story can become more captivating if you use charts and heat maps to highlight key data points, too many graphics quickly turn it into a yawnfest and will dilute your main message (and yes, even with plenty of data points, there should still be a main message.)