By thinking through the
how of a story, you are putting yourself in position to craft better data-driven stories. Looking at your data objectively and considering factors like how it was created helps you to discover interesting insights that you can include in your story. Also, knowing how to quickly find stories in potential data sources helps you to quickly sift through the staggering array of options.
And, how you present your data-driven story determines much about how well that story is received by your target audience. You could have done everything right — really taken the time to get to know who your audience is, boiled your story down so that it says exactly what you intend, published it at just the right time, crafted your story around what you know about why people care, and even published it to just the right venue — but if your data visualization looks bad, or if your story layout makes it difficult for readers to quickly gather useful information, then your positive response rates are likely to be low.
Integrating how as a source of data and story context
You need to think about how your data was generated because that line of thinking often leads you into more interesting and compelling storylines. Before drawing up a final outline for your story, brainstorm about how your source data was generated. If you find startling or attention-grabbing answers that are relevant to your story, consider introducing those in your writing or data visualization.
Finding stories in your data
If you know how to quickly and skillfully find stories in datasets, you can use this set of skills to save time when you're exploring the array of stories that your datasets offer. If you want to quickly analyze, understand, and evaluate the stories in datasets, then you need to have solid data analysis and visualization skills. With these skills, you can quickly discover which datasets to keep and which to discard. Getting up to speed in relevant data science skills also helps you quickly find the most interesting, relevant stories in the datasets you select to support your story.
Presenting a data-driven story
How you present your data-driven story determines much about whether it succeeds or fails with your target audience. Should you use an infographic? A chart? A map? Should your visualization be static or interactive? You have to consider countless aspects when deciding how to best present your story.
