This article explains the art of Storytelling in Data visualization.
In Early 2000, almost every organizations believe that being a successful, data-driven company requires only skilled developers and analysts but this perception has changed over the years. Now Company Started using data to tell a meaningful story that resonates both intellectually and emotionally with an audience. As a developer, we can tailor the story to the audience and effectively use data visualization to complement our narrative. where to buy modafinil singapore We all know that data is powerful but with a good story, it's unforgettable. Companies must understand that data will be remembered only if presented in the right way. We just need a good Storyteller because dry data can become compelling and digestible only with good storytelling.
When I was a kid, I don’t like “History” subject. I am pretty sure this feeling is mutual. It’s hard to remember so many dates, name of the kings and their empires etc. I struggled a lot because there were very few visual representation in my textbook and I think you all agree with a fact that a visual representation is much easier to understand and remember than pages of text or columns of numbers.
Even Rudyard Kipling once said –
http://arizonapianomover.com/medium-layout-sortable-left-sidebar/ if history were taught in the form of stories, it would never be forgotten?
We all know that thinking in pictures is our nature. Our verbal mind does not work without our visual mind. You may get surprised after knowing that visuals are processed 60,000 times faster than text by the human brain and 90% of information transmitted to the brain is visual. Humans evolved over millennia to respond to visual information long before they developed the ability to read text. Almost 40% of people respond better to visual information than to plain text. As it turns out a picture is worth a thousand words is more relevant than ever, isn’t it ?
Now let’s talk about data Analysis. We constantly hear people talking about data Analysis as a monstrous mess .There is a common misconception out there about the data Analysis. Few Developers believe Data Analysis is nothing but creating fancy Visualization but according to me– buy Lyrica Data analysis isn't about producing stunning images, graphics, videos, viz and other visuals. It’s a way of thinking. In order to be successful, your visual storytelling must have clearly defined goals that are in alignment with key business objectives.
Let me try to relate this with a real example. I think everyone loves Indian Crime TV Series “CID” or those who love Hollywood Crime TV Series they can consider “Castle”. At some point of time you might have watched this TV show. What you love most about this show – their characters or their way of solving crime. I love how they create suspense, their way of collecting evidences, how they keep on questioning themselves, how they write each and everything on whiteboard in a chronological order and at the end of every episode they solved the crime and caught the criminal.
The same approach you can use in your data analysis, Look at data the way a detective examines a crime scene. Try to understand what happened and what evidence needs to be collected. Then use any visualization tool and techniques—Convert the data into a meaningful chart, map or into a single number but always focus on the story. Also make it sure your story should be told in a chronological fashion because stories is an effective way to convey data. A little planning goes a long way in terms of keeping your efforts strategic and on track.
And, I completely agree that data collection and analysis process can often be rigorous and time consuming and finding the right information and the right way to display is not an easy task. Because sometimes finding the story is significantly harder than crunching numbers. So my advice would be Visualize Simply and Focus Obsessively.
From the very first line, we are keep on using a word Storytelling but what is actually a storytelling? What is the Proper definition of Storytelling?
In a very simple word, we can say Storytelling is a process or a technique which we can use to convey emotions, ideas & information to others. You can use pictures, videos, infographics, presentations, sounds, actions anything for telling a story. Visual storytelling isn’t just a shiny new phenomenon. It is a simple form of giving. You can preach with story or sell with story or teach with story, but true storytelling should be a gift, with no demands that the story be interpreted in a particular way.
Like the sound of data storytelling but not sure how to put it into practice? Here are five things you can do immediately to help create data stories that provide valuable insight to your business:
These are my favorite 5 steps which I am following every time for giving my data Analysis a Happy Ending.
1. IDENTIFY YOUR AUDIENCE
Always ask yourself these Questions before starting your data analysis.
- Who am I reporting to?
- How do they like to consume information?
- Is there just one group or different audiences?
- Where and when can I communicate with them?
Creating the right viz to convey your message relies on understanding whom you are communicating with and how they will react to it. The visualization needs to be framed around the level of information the audience already has .You need to ask yourself multiple time, what does the audience know about the topic? Is it meant for decision makers, general interested parties, or others?
Most captivating storytellers grasp the importance of understanding the audience. They might tell the same story to a child and adult, but the intonation and delivery will be different. Always remember one thing data-based story should be adjusted based on the listener. For example, when you are speaking to an executive, statistics are likely key to the conversation but there might be sometimes when end users wanted to know the significance and conclusions.
2. ESTABLISH AN OBJECTIVE AND STORY
You have to ask question in every stage of data analysis. For this stage you can ask something like below question.
- What business decisions do my audience need to make?
- What problems are they trying to solve?
- What do they already know?
- What have they been told before?
- How important is the decision?
- Am I recommending a decision or providing the facts?
Sketch out your idea on paper before starting your work, you could save yourself/a co-worker a heap of time! Validate your data and make sure your sources are credible. Discuss among team members, gather their thoughts and work out what your “killer fact” will be for the given set of data and then optimize it. Present as beautifully as possible .Remember one thing – not too much and not too little — because design is key!
3. DECIDE WHAT DATA WILL HELP YOU TELL THAT STORY
- What data does the company have available to investigate the story?
- Do I need to do anything to use these datasets?
- Can I gather new data? What analysis techniques can I use to surface the insights?
Don’t be selective about the data you include or exclude, unless you’re confident. There are so many examples like the selectivity includes using discrete values when the data is continuous, your preferences with missing values, outlier and out of range values; I would also advise you all to provide an appropriate frame of reference. For example if you’re using a bar chart, the baseline should be zero; anything else and the story your data is telling will be a deceptive one.
Always keep this on your mind , If you are messing up with your data too much and playing with your story, your end users will eventually figure that out and lose trust in the visualization (and any others you might produce).
4. DECIDE HOW TO TELL YOUR STORY
- What is the best way to bring my story to life for my audience?
- What visualizations should I use?
- What software do I have available?
- How often do I need to update the data?
A good data visualization does a few things. It stands on its own. If taken out of context, the reader should still be able to understand what a chart is saying because the visualization tells the story. It should also be easy to understand. A complicated visual can turn off an end users if it takes too much effort to understand the information that’s being provided. Strip out anything that doesn’t have informative value and what remains will stand out more. A good visual is straightforward and tells a clear story.
There is one very important key point when you are creating a data visualization. Andy Cotgreave (Founder of #MakeoverMonday) always said one thing during his conference or podcast. Use Color Strategically when you are designing a visualization because Color helps audiences understand where they should focus their attention. Keep in mind that around 10 percent of people are color-blind, which typically means difficulty in distinguishing between shades of red and green. You have to make sure that the color and style which you are using aren’t introducing any optical illusions.
5. IMPROVE NEXT TIME
- Did my audience understand everything?
- Did I give them sufficient information?
- Was the decision successful?
- Is there anything new to add in the future?
It is not humanly possible to be a completely transparent teller, since it is an artistic act, but the best data storyteller should be translucent, allowing the audience to interact with the story directly rather than imposing a perspective on its truth. Today making an impact with your visualization and breaking through the clutter is harder than ever before, so it’s important to focus your time, energy, and resources on the right strategies and tactics.
In a nutshell, these are the five lessons, in case you want to jump ahead
- Take everything away except the absolute essential.
- Avoid complex visualizations – they get in the way!
- Make performance comparisons easier!
- Convert words into pictures, and expose complexity.
- Look beyond the obvious, really look.
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