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Introduction to Data Storytelling

  • Soumalya Bhattacharyya
  • Nov 22, 2022
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The practice of turning data analysis findings into a narrative that laypeople (ordinary business people) can comprehend and use when making decisions or taking actions in the workplace is known as data storytelling.

 

The most effective method to communicate is through storytelling since the human brain processes image the most easily of any media. The best approach to display data is therefore through data storytelling using visuals.

 

Many different items, including data visualizations, infographics, dashboards, data presentations, and so on, have been linked to the term "data storytelling." Data storytelling encompasses much more than just producing aesthetically appealing data charts, despite the fact that it is sometimes mistaken for simply excellent data visualization. Data, images, and narrative are used in the systematic technique of delivering data insights known as "data storytelling."

 

You must enter people's minds in a way that they can comprehend if you want them to use facts to make the proper judgments. Throughout human history, telling stories has been the method of doing that. Data from impartial areas in a database are transformed into views, arguments, and insights through data storytelling.


 

What is Data Storytelling?

 

The greatest approach to using data to generate new knowledge, new choices, or new actions is through data storytelling. It is an interdisciplinary profession that combines expertise and information from a number of fields, including communication, analysis, and design. It is used to solve a range of problems and is practiced in many different disciplines.

 

The majority of marketers have some experience with storytelling. When we discuss data storytelling, we are referring to narratives in which data serves as the focal point. The narrative is to explain the information and its significance. There are many different kinds of stories, and most of them may be told with the aid of images, but only a select few have this goal.

 

Data storytelling is a way of presenting facts with a gripping tale that is suited to a particular audience. It is, perhaps, the most significant component of your data analysis and comes in at the last ten feet. According to evolutionary theory, it is in our nature as humans to communicate knowledge through telling tales.

 

According to some theories, storytelling served as the main vehicle for the dissemination of information across huge populations, helping to shape civilizations as we know them today and promoting successful generational progression.

 

Now that we have access to so much data, the only way to present the increasingly complicated and dynamic world of the digital era from a human viewpoint is through data storytelling.


 

Fields of Data Storytelling:

 

Three major areas of knowledge are combined through data storytelling:

 

  • Data science:

 

This area of specialization is an interdisciplinary branch of research that draws information and insight from data and makes it accessible. In the last two decades, this fascinating discipline has significantly altered our way of life. This area of knowledge underpins all the technology we take for granted, however, there is one area in which data scientists lack a natural aptitude for Storytelling. 

 

Data scientists are frequently adept at gathering and presenting data, but they lack the ability to communicate a deep grasp of the potential concealed in the supplied data.

 

Also Read: 10 Data Science Applications in Real Life


 

  • Visualizations: 

 

The introduction of technological solutions like dashboards became a natural way to help us understand the massive volumes of data that have been gathered. We could view our data like never before thanks to the data visualizations, although they do have certain limits when used alone. 

 

They offered data snippets that could be quickly glanced at without providing the background necessary to comprehend what had transpired.

 

Also Read: 10 Types of Data Visualization


 

  • Narrative: 

 

The narrative is the third and, in a way, the most important component of a data tale. Narrative enhances our ability to fully comprehend new information by using language in a way that best meets our individual requirements. With visualizations and data serving as crucial proof points, a story is an essential tool for communicating ideas.


 

What makes up a good data story?

 

Data, narrative, and visualizations are the three main elements of a successful data story.

 

The data component is straightforward; in order to arrive at reliable insights, we need accurate data. We can identify trends and patterns in datasets that are difficult to detect in the rows and columns of spreadsheets thanks to the visual component.

 

The narrative elements that focus on the straightforward language used to convey the facts can be thought of as giving the data a voice. Each piece of data is a protagonist and a character in a narrative with a unique tale to tell. When combined, story, information, and images may produce data tales that spur corporate transformation.

 

The idea of data storytelling is not new. For many years now, businesses have tried it and have achieved success.

 

Also Read: Business Analytics and Data Analytics - How are they different?


 

Benefits of Data Storytelling:

 

While human storytelling is quite similar to data storytelling, the latter has the advantages of deeper insights and supporting data via graphs and charts. Through data storytelling, complex information is made understandable so that your audience will be more engaged and able to make important decisions more quickly and with more assurance.

 

A really effective tool is creating a data story that inspires someone to act. People and your business may benefit from effective data storytelling.

 

The following are some advantages of effective data storytelling:

 

  • Enhancing the worth of your data and insights.

  • Analyzing difficult material and pointing out crucial details for the viewers.

  • Providing your data with a personal touch.

  • Bringing value to your industry and audience.

  • Establishing credibility as a subject and industry thought leader.

 

Analyzing all the raw data you've obtained to support a hypothesis and, ideally, the specific change you'd like to see result from sharing your data narrative is what good data storytelling entails.

 

Start telling your tale after going through all the data. It might be easy to just consider data sets that confirm your idea in some cases, but it's important to consider the complete picture. Consider what the data is trying to tell you, then use the appropriate tools to deliver your team a clear data story. When you have a lot of data sets at your disposal, it might be intimidating, but structuring your story can assist.

 

How well-prepared your audience is to understand complicated material depends in large part on how well-presented the data is. Infinite quantities of data may be simplified and made easier to understand through data visualization. The images required to bolster your tale can be provided here.

 

A good data visualization can:

 

  • Give an unbiased account of patterns, trends, and discoveries.

  • Contextualize the data, analyze them, and express your conclusions.

  • Data should be made more digestible for your audience.

  • Boost interest in the audience.

 

A tool for information management and business intelligence (BI) is a data dashboard. Data dashboards help analyze complex metrics to make the audience comprehend the relationship between the data narrative and the story's premise by arranging and presenting crucial information in an easily understandable style in one place.

 

Making use of a dashboard for your data has the following advantages:

 

  • Improving the ability to see both historical and contemporary patterns.

  • Better accurately predicting future patterns.

  • Choosing important performance metrics from a variety of sources.

  • Real-time customer analytics capability.

 

The way that we consume data and analytics may change dramatically as a result of data storytelling. Data storytelling gives the sometimes-impossible numbers and statistics that raw data presents to us a human face. 

 

Building a narrative is an important step in the process, but telling a compelling story requires that you comprehend the facts and convey them from an objective viewpoint. You can convey that tale with the aid of Microsoft Power BI.


 

Steps to Create a Great Data Story:

 

How can you present a data story that encourages people to choose wisely? Let's explore what makes a data story powerful.


 

Steps to Create a Great Data Story:  1. Make relevant content 2. Trustworthy sources 3. Clear narrative 4. Target the audience 5. Emphasize on the important data 6. Minimum professionalism required

Steps to Create a Great Data Story



 

  1. Make relevant content:

 

This implies that the information (including copy and images) must be appropriate for the audience's present level of understanding and must aid them in achieving some sort of goal.

 

Your target audience can be internal, like in a presentation to leadership regarding the necessity to fund a certain method or plan. Alternatively, they might be external, like a campaign to get buyers to test your product.

 

In any case, consider what's important to them. The more precise a person is about who a story is speaking, the better.

 

Also Read: An Introduction to Content Analysis


 

  1. Trustworthy sources:

 

This means that the information should come from a reliable source and/or be gathered in a fashion that accurately captures what is required to offer a complete picture.

 

In addition to being more accessible, publicly available data from governmental bodies, intergovernmental organizations, university researchers, and recognized analysis leaders are also transparent and verified.

 

Since the focus is on the facts, these tales don't concern themselves with what you believe your audience should learn; rather, they share what the impartial data reveals. In comparison to other stories, we may tell, this one is rather different. The information used should assist you in telling the truth. It needs to be in line with the requirements of the audience and aid in discovering precisely what they require to make a crucial decision.


 

  1. Clear narrative:

 

We are all accustomed to a classic tale arc with a beginning, middle, and conclusion when it comes to storytelling. This often implies that before diving into the data for a data story, the topic has to be introduced. 

 

A data story must also end with a clear call to action, which is another factor that sets it apart from a basic report. Use clear English if your audience does not consist of professionals in order to avoid losing them in jargon or complicated acronyms.


 

  1. Target the audience:

 

To find out what matters to them most, their goals, what they already know, the decisions that must be made, and what information might be useful to them in making those decisions, you must first determine who they are. After that, you can speak with them and possibly conduct further research to learn more about who they are.

 

Also Read: Customer Segmentation: Types, Strategies, and Software


 

  1. Emphasize the important data:

 

Knowing your audience can assist you to decide what information to add and seek. You may either utilize qualitative data, such as procedures, systems, or quotations, or quantitative data, such as statistics on revenue, change over time, or the number of individuals impacted.


 

  1. Minimum professionalism required:

 

To convey a compelling data narrative, you don't need to be a skilled designer. You may draw on your existing skills (whether they be analytical, conversational, artistic, or relational) to produce data stories that will help your audience know better and act better as long as you pay attention to what matters most.


 

Conclusion:

 

A potent approach for involving stakeholders and motivating action is data storytelling. However, if done poorly, it may result in conclusions and facts that are inaccurate or incomplete. Data storytelling must never be deceptive, misleading, or inaccurate.

 

Data-driven storytelling is an effective tool for leaders at all levels to explain complicated concepts, win support, and guide smarter decisions. You can produce compelling data stories that inspire change by fusing the best practices for the visualization, data analysis, and storytelling.

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