{"id":4514,"date":"2023-04-28T11:23:57","date_gmt":"2023-04-28T18:23:57","guid":{"rendered":"https:\/\/www.springboard.com\/?p=4514"},"modified":"2023-05-08T04:37:01","modified_gmt":"2023-05-08T11:37:01","slug":"data-storytelling","status":"publish","type":"post","link":"https:\/\/www.springboard.com\/blog\/data-science\/data-storytelling\/","title":{"rendered":"Data With a Narrative: Understanding Data Storytelling"},"content":{"rendered":"\n

In the past few years, data has become an increasingly valuable resource for making business decisions. But cold, hard data doesn\u2019t always offer valuable insights right away. Data needs to be corralled into a cohesive narrative, and that\u2019s where data storytelling comes into the picture. <\/p>\n\n\n\n

Data storytelling is an underrated part of the larger data insights process. While most data professionals understand the importance of various data analysis techniques, not enough attention is paid to creating a compelling narrative from their findings. In this article, we\u2019ll find out why effective data storytelling is so important and how you can learn to do it well. <\/p>\n\n\n\n

What Is Data Storytelling?<\/h2>\n\n\n\n

Data storytelling is the process of narrativizing data analysis so that its insights can be understood by a wide audience. While not everyone can quickly comprehend data, most can follow a visual story that summarizes findings from the analytics process. <\/p>\n\n\n\n

Why Is Data Storytelling Important?<\/h2>\n\n\n\n

Let\u2019s take a look at an example to see why data storytelling is important. Here are some earth surface temperature data from a Kaggle dataset<\/a>.<\/p>\n\n\n\n

\"what<\/figure>\n\n\n\n

This is what your average dataset looks like\u2014several rows and columns with various data points. Analyzing this dataset can produce valuable insights, but it won\u2019t change what the output looks like. To the average viewer, it will remain a collection of rows and columns that don\u2019t make a lot of sense. <\/p>\n\n\n\n

And that\u2019s why data-driven storytelling is so important. It transforms complex data into universally comprehensible stories with a solid narrative. <\/p>\n\n\n\n

Essential Parts of a Data Story<\/h2>\n\n\n\n
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Source: Adverity<\/a><\/figcaption><\/figure>\n\n\n\n

Here are the components that contribute to an effective data story:<\/p>\n\n\n\n

Data<\/h3>\n\n\n\n

You can\u2019t have a data story if you don\u2019t have any data. So the bedrock of the data storytelling process is clean data that can be analyzed to produce actionable business insights. <\/p>\n\n\n\n

The places from where you source your data will depend on the nature of the project that you\u2019re working on. For example, if you\u2019re trying to use data analytics<\/a> to make better fantasy football picks, then you should use the Football Database<\/a>. There are various sites that offer data sets<\/a> that you can analyze for fun.\u00a0<\/p>\n\n\n\n

Now that you have your dataset, it\u2019s time to do some data analysis. That means that you connect your data to a specific business problem, clean the data so that there are no erroneous or missing entries, and carry out your analysis.\u00a0<\/p>\n\n\n\n

At the end of this process, you will find that you\u2019ve produced insights that weren\u2019t available when you started with a raw dataset. If you work in the professional world, this will contribute to the business decision-making process. But in order to convince your organization about your findings, you need something more than just those insights. <\/p>\n\n\n\n

Narrative<\/h3>\n\n\n\n

One doesn\u2019t usually associate a narrative with the data process<\/a>, but the two are more intertwined than you might first think. Here are a few elements that contribute to a good story, data or otherwise:\u00a0<\/p>\n\n\n\n

Setting<\/h4>\n\n\n\n

A setting is the foundation of any strong narrative, and data storytelling is no different. In this specific case, that means that you explain the context of your project, its business significance, and any specific problems that it is looking to address. <\/p>\n\n\n\n

Imagine that you\u2019ve been given data from various marketing campaigns to determine why there is a lag in the sales of a specific product during a certain time of the year. The setting is the problem statement as it has been outlined, the product, and the nature of the marketing campaigns (marketing channels, nature of creatives, ad spends, etc.).\u00a0<\/p>\n\n\n\n

Characters<\/h4>\n\n\n\n

You can\u2019t have a story without characters. The same goes for the story that you\u2019re trying to tell with data. The characters in this particular case are the subjects who contribute to your data and the various stakeholders who care about this particular data project. <\/p>\n\n\n\n

Let\u2019s return to the example of the marketing campaign. Our characters are going to be the target demographic of those campaigns. The list of characters might also include members of the marketing team who contribute to the creation of those campaigns. <\/p>\n\n\n\n

Conflict<\/h4>\n\n\n\n

Stories are driven by conflict. Every project that you will work on is driven by some kind of conflict, usually one that involves a pressing business problem. To further the example we\u2019ve been using, the conflict could be defined as ineffective marketing campaigns. In another case, it might be the need to explore new markets or enhance employee productivity. <\/p>\n\n\n\n

Describing the conflict helps your audience gain a clear understanding of the goals of the project. It tells them exactly what you\u2019re trying to achieve and what kind of impediments might be in your way. <\/p>\n\n\n\n

Resolution<\/h4>\n\n\n\n

The resolution is your answer to the conflict that you\u2019ve established in the previous step. This resolution must, of course, be backed by the data analysis that you\u2019ve already conducted. <\/p>\n\n\n\n

Remember that your resolution needs to tie in with all of the other elements of your narrative. It must work in the setting that you\u2019ve established, be relevant to your characters, and be appropriate to the conflict that you\u2019re dealing with. <\/p>\n\n\n\n

Returning to our example, we see that certain marketing campaigns aren\u2019t working as well as a company wants them to. Your data might reveal that the problem is that the specific marketing channels that have been chosen don\u2019t cater to the target audience. In that case, your resolution will be to select different marketing channels based on their ability to reach that demographic. <\/p>\n\n\n\n

Visuals<\/h3>\n\n\n\n

Visuals are an essential aspect of data storytelling, as they convey large amounts of information quickly and keep readers engaged. Here are a few things you should keep in mind when coming up with your visual elements: <\/p>\n\n\n\n

Appropriate Visualizations<\/h4>\n\n\n\n

The kind of data visualizations<\/a> you choose in each case will depend on the kind of data you\u2019re working with. For example, column charts are a good choice when you want to compare numerical values, whereas a histogram works better when you want to track a specific data trend over time. <\/p>\n\n\n\n

Colors in Moderation<\/h4>\n\n\n\n

There is a tendency to make visualizations colorful in the hopes of this leading to a more attractive appearance. But using too many colors can confuse readers and distract them from the broader story. So make sure that you use a few colors and choose neutral tones as much as possible. <\/p>\n\n\n\n

Familiar Formatting<\/h4>\n\n\n\n

The whole idea of using visuals is to make it easy for viewers to quickly glean the information they need. You can contribute to that goal by using familiar layouts and formatting throughout your story. For example, if you have multiple graphs in your story, use the same formatting and colors across them so that they\u2019re easy to parse quickly. <\/p>\n\n\n\n

Data Storytelling: Tips, Tricks, and Things To Remember<\/h2>\n\n\n\n

Just like the stories you watch on TV or read in books, a data narrative needs to have a structure. Where do you want your audience to begin? Where does the story end? How will you get them there? Here are a few veteran moves you can use to put all those things together in your data story:<\/p>\n\n\n\n

Include the Right Details<\/h3>\n\n\n\n

Don\u2019t overload your audience with information right off the bat. By keeping things succinct, you can guide users toward meaningful conclusions. For example, this table provides too many details about each sales opportunity, but the bar chart shows the metric the department truly cares about\u2014open opportunities\u2014in a more visual manner.<\/p>\n\n\n\n

\"what<\/figure>\n\n\n\n
\"what<\/figure>\n\n\n\n

Provide the Right Context<\/h3>\n\n\n\n

Everything you include in your data story should relate to your organization\u2019s larger goals, and your dashboard or data visualization should highlight the correlations between each metric and these KPIs. The chart below shows actual website traffic alongside the target numbers to provide important context. This is an example of how you can contextualize your data in light of larger organizational goals.<\/p>\n\n\n\n

\"what<\/figure>\n\n\n\n

Provide Actionable Information<\/h3>\n\n\n\n

Your audience should know why a specific chart or graph is important without any guesswork. Additionally, it should be easy for them to see how the data relates to their role in the organization. <\/p>\n\n\n\n

Let\u2019s look at an example based on the visualization below. Viewers can quickly figure out that the chart displays educational assessments across different subjects at Eisenhower Elementary. It\u2019s also easy to get an idea of the comparative performance between subjects just by looking at this visualization. That makes it a lot easier to take actionable steps based on the data. <\/p>\n\n\n\n

\"what<\/figure>\n\n\n\n

Data Storytelling Tools<\/h2>\n\n\n\n

There are various data visualization tools<\/a> that are used by data storytelling professionals. Let\u2019s take a look at the most popular ones out there.\u00a0<\/p>\n\n\n\n

Tableau<\/h3>\n\n\n\n

If you\u2019ve ever gone about researching data visualization tools, then you\u2019ve no doubt heard of Tableau<\/a>, a powerful tool that can integrate data from a myriad of sources. It\u2019s also a relatively intuitive software to learn. <\/p>\n\n\n\n

Infogram<\/h3>\n\n\n\n

Data storytelling is a domain that\u2019s not limited to just designers anymore, and that\u2019s thanks to tools like Infogram<\/a>. This is a piece of software with a simple drag-and-drop interface that you can use to build dashboards, infographics, and more. An added advantage is that you can use Infogram to produce interactive visualizations, which is a great way to create a more engaging experience for your audience.\u00a0<\/p>\n\n\n\n

Datawrapper<\/h3>\n\n\n\n

Datawrapper<\/a> is a visualization tool built specifically for news stories. You can easily copy and paste your data into the tool to create tables and maps that enrich news pieces. These visualizations can easily be embedded on news sites with an embed code and can also be exported as a PNG, PDF, or SVG. <\/p>\n\n\n\n

D3.js<\/h3>\n\n\n\n

D3.js<\/a> is a Javascript library that you can use to create visualizations in data-driven documents. Since this is a Javascript-based tool, you can also easily add transitions and transformations to bring your data to life. <\/p>\n\n\n\n

Data Storytelling Examples<\/h2>\n\n\n\n

Here are a few examples that you can use as inspiration to create your own data stories. <\/p>\n\n\n\n

We Feel Fine<\/a><\/h3>\n\n\n\n
\"Data<\/figure>\n\n\n\n

We Feel Fine is a large-scale experiment in visualizing human emotions. How does it do that? Well, the tool trawls blogs on the Internet every 10 minutes and conducts a sentiment analysis on them to figure out the dominant emotions of each post. The results visualizations are a visually rich, data-driven exploration of human emotions in real-time. <\/p>\n\n\n\n

Spotify Fan Study<\/a><\/h3>\n\n\n\n
\"Data<\/figure>\n\n\n\n

Given its position as one of the most widely used music streaming services out there, Spotify has vast amounts of data at its disposal. The company used some of that data to produce the Fan Study data visualization. This is a website where musical artists can get a data-driven insight into what Spotify has been able to gather about listeners\u2019 preferences and tastes. The site shows artists how they can expand their reach, make a splash with new releases, and improve merch sales. <\/p>\n\n\n\n

Data Storytelling Resources<\/h2>\n\n\n\n

Here are a few resources that can help you learn more about data storytelling: <\/p>\n\n\n\n

Online Courses<\/h3>\n\n\n\n