Data Storytelling for Beginners

Data Storytelling for Beginners
Data and context
Categories
Data Strategy
Keywords
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Author
Benjamin Hinz
Reading time
9 min

Get creative with data and design compelling dashboards

Working with data can be so incredibly creative. Data is, of course, first and foremost something rational and sober. But if we put it in the right context and prepare it so that we can read it like a story, we breathe life into it and assign it a concrete meaning. This method is often referred to as data storytelling. It sounds interesting, but also somewhat lyrical. What's behind it?

First of all, facts are best understood and interpreted when they are placed in context. This is because context creates a link to a specific situation and resolves previously asked questions. We create this framework by, simply put, telling stories. Data storytelling provides us with a way to generate comprehensive and fast information from our data.

By processing data visually, we make a lot of work easier for our brains (and the brains of everyone else who is searching for meaningful information with us). If we combine dry information with interesting images, we are able to translate this content into meaningful added value more quickly (or at all). Only the interplay of intellect and emotion leads to sustainable decisions.

Data storytelling as a creative controlling method

Nun könntest du denken, Geschichten zu erzählen sei nicht so dein Ding. Dafür fehlt dir die kreative Ader. Vielleicht magst du Geschichten auch gar nicht so gern und du hast immer schon lieber mit Zahlen und Statistiken gearbeitet. Und wie soll das überhaupt aussehen, den Es-war-einmal-Ansatz für Daten zu nutzen? Ein bisschen riecht der Begriff Data Storytelling nach Buzzword, oder? Als hätte hier jemand versucht, aus einer seriösen und sachlichen Methode in der <a href="https://www.taod.de/services/bi-und-data-analytics-consulting“ data-webtrackingID="blog_content_link" > Datenanalyse </a> eine Geschichte zu kreieren.

We come up with stories that our target group can easily consume.

Well, I think so too. And I think that's good. Because if things have a name that generates attention, we can start to understand and adapt them with interest. One thing is clear: we can engage our listeners much faster with exciting stories than with dryly presented facts. That's why PowerPoint was invented at some point. How much more enjoyable is it to listen to interesting and well-founded presentations when they are accompanied by illustrated and interactive slides, sound and video? I'd argue that we've all presented something with PowerPoint at some point in our lives and created a common thread that gave the audience an interesting story. That's what data storytelling is all about. We come up with stories that our target group can easily consume in order to interpret them according to their own needs. This form of creativity also, and especially, works with data.

"I'm not creative."

What does this sentence mean? Understatement? Everyone is creative. You and me. If only because we deal with new technologies and methods every day in our jobs. Creativity refers to the ability to generate new ideas, concepts, connections or solutions that are original, useful and of value. It is a cognitive process that allows a person to combine existing knowledge, experience, skills and imagination to create something new or use existing things in an innovative way.

Creativity is a multifaceted quality and can be expressed in various areas, be it in art, design, science, writing, technology or other areas of human endeavor. It can take place on an individual level or in the context of collaboration and teamwork. So, do you find yourself in this description? Creativity is certainly something you use every day in your work. Working with data allows you to take your creativity even further.

What is data?

Let's quickly jump to the basics. Data is information that exists in a structured or unstructured form. It can include numbers, facts, text, images, videos or any kind of symbolic representation. Data is used to capture, store, organize, analyze and communicate information.

Data can be generated and collected in different contexts. For example, it can come from measurements, observations, surveys, experiments, business activities or social media. Data is often collected and stored in electronic form, but it can also exist in physical form, such as printed documents or records.

Daten sind von entscheidender Bedeutung, da sie die Grundlage für Informationen und Erkenntnisse bilden. Durch die <a href="https://www.taod.de/services/bi-und-data-analytics-consulting“ data-webtrackingID="blog_content_link" > Analyse von Daten </a> können Muster, Trends, Zusammenhänge oder Abhängigkeiten entdeckt werden, die es ermöglichen, fundierte Entscheidungen zu treffen, Probleme zu lösen oder neue Erkenntnisse zu gewinnen. Daten allein haben noch keine Bedeutung. Erst wenn sie interpretiert und in einen Kontext gesetzt werden, können sie Informationen liefern und einen Mehrwert schaffen. Und hier haben wir schon den Knackpunkt. Neben Kreativität brauchen wir Kontext.

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Requirements, business questions and context

Before we can do anything at all with our data, we have to think about what we actually want to find out from it. So we formulate our requirements. The best way to do this is to think about so-called business questions. These are questions that are asked in a business context in order to obtain information, support decisions or improve business processes. These questions can relate to different areas of a company, such as strategy, marketing, sales, finance, human resources or operational processes. For example, they can relate to the market, customers, finances, processes, personnel or technologies. At the same time, they shape the context in which the data is placed. We need this in order to create convincing stories from it. This is when the data becomes relevant.

Context makes data relevant.

Data context helps to determine the relevance of data. By defining the context, data can be selected that is relevant to a specific question or decision. It makes it possible to define data sources, parameters or variables that are relevant to the specific context and to exclude irrelevant information. It also ensures that data is interpreted in relation to the underlying question or problem. For example, the context can explain whether a particular data value is good or bad, whether it represents a positive or negative result or whether it lies within a certain norm or benchmark.

Context also helps to establish connections between different data points. It makes it possible to recognize and understand patterns, trends or dependencies. Data without context could lead to inaccurate or misleading conclusions, as important correlations or cause-and-effect relationships are not taken into account.

The context also enables clear and effective communication of the data. By adding contextual information, data can be presented in an understandable form. We can share data much more easily with others to create a common basis for discussion, analysis or decision-making. With context, we create a framework that is summarized and communicated convincingly through a good story.

What is a story?

Here's a very dry definition: A story is a narrative representation of events, characters or actions that have a certain structure and narrative progression. It serves to convey information, provide entertainment, evoke emotions or pass on knowledge. For a good story, you usually need one or more protagonists (identification!), a plot, conflicts (suspense!), a resolution and an overarching theme with a message.

And then there are various forms of presenting a story, including books, films, plays, fairy tales, legends, poems and songs. They serve to stimulate the imagination, arouse emotions, create connections and impart knowledge. Stories have a long tradition in all cultures and are an essential part of human communication. Why? You may remember: because the human brain is excellent at absorbing and processing information when facts are linked to images.

Now, of course, it makes no sense to present your data in poem form. (Unless you or your recipients have a strong lyrical streak). The questions on which the data storytelling method is based are these:

  • How do I bring people who are not so data-savvy closer to the topic of data?
  • How do I turn my business questions and KPIs into understandable answers?
  • How do I create measurable content?
  • How do I convince stakeholders of the value of the information I have discovered with data?

Die Antwort auf alle vier Fragen lautet: Durch Visualisierung, zum Beispiel in <a href="https://www.taod.de/tech-beratung/power-bi“ data-webtrackingID="blog_content_link" > Power BI </a> oder <a href="https://www.taod.de/tech-beratung/tableau“ data-webtrackingID="blog_content_link" > Tableau </a>. Denn Bilder sagen mehr als tausend Worte. Wir können es schaffen, unsere Daten in Bilder zu verwandeln, um mit ihnen eine Art von Geschichte zu erzählen. Data Storytelling ist die Kunst, Daten in eine fesselnde und aussagekräftige Geschichte zu verwandeln. Es ist eine Methode, um komplexe Daten und Informationen visuell und narrativ zu präsentieren, sodass sie für ein breites Publikum verständlich und ansprechend sind.

How data storytelling works

Data storytelling is about embedding data in a narrative structure and providing it with context and meaning. Rather than just presenting numbers, charts or tables, data storytelling seeks to capture the audience's attention and connect to the data by telling a story.

With the help of data storytelling, you formulate the individual story of your daily business, which you communicate via meaningful dashboards.

A good data story usually comprises several elements. First, there is an introduction that arouses interest and provides the context of the data. This is followed by the actual story, in which the data is presented and interpreted. Visual elements such as diagrams, infographics or interactive visualizations are often used to make the information easier to understand. Finally, there is a conclusion that summarizes the most important findings and possibly offers recommendations for action or implications.

With the help of data storytelling, you formulate the individual story of your daily business, which you communicate via meaningful dashboards. You use these dashboards to answer your business questions with the help of graphics that summarize your KPIs and make them interpretable. You compare areas, time periods, results or forecasts. You do everything you used to do in Excel - only much more efficiently, easily and impressively.

The perfect dashboard

Daten sind erst einmal nüchtern (manche würden sagen, langweilig), deshalb ist eine überzeugende Darstellung so wichtig. Die darf gerne auch einmal etwas verspielter ausfallen. Erlaubt ist, was informiert und begeistert. Tatsächlich haben künstlerische und spielerische Aspekte, wie sie manche Tools zur Datenvisualisierung anbieten, z.B. <a href="https://www.taod.de/tech-beratung/tableau“ data-webtrackingID="blog_content_link" > Tableau </a> oder <a href="https://www.taod.de/tech-beratung/power-bi“ data-webtrackingID="blog_content_link" > Power BI </a> im Unternehmensalltag weniger Raum. Hier dürfen sich Data Analysts ruhig mehr trauen und den Data-Artist aus sich herausholen.

Initially, however, the focus in companies is usually on the pure presentation of previously defined KPIs. The calculation is based on clear specifications and visualizations are used, which are always used in the same way. All relevant information is consolidated and communicated visually in this way and is understandable at first glance and in the long term. There is no point in distracting the data consumer from the actual content through excessive visualization or fancy effects.

Bei der <a href="https://www.taod.de/services/bi-und-data-analytics-consulting“ data-webtrackingID="blog_content_link" > Gestaltung eines Dashboards </a> muss berücksichtigt werden, welche Fragestellungen die Zielgruppe mitbringt. Die mitgebrachten Fragen müssen ausnahmslos beantwortet werden. Jede Person soll ihren Mehrwert aus dem Dashboard ziehen können und es noch dazu gerne anschauen. Idealerweise sind die Informationen so visualisiert, dass die Betrachtenden das Gefühl haben, ihr Unternehmen ist im neuen Zeitalter angekommen. Deshalb sind eine moderne Optik, personalisierte Funktionen und eine intuitive Nutzung elementar für Dashboards. Dashboards sollten immer selbsterklärend sein.

Good dashboards tell your story at a glance. This is where you knit the common thread for the content, this is where your story is created. Because your dashboard follows a logical sequence of key figures, tables and diagrams, illustrates them, provides an immediate overview of the data situation and enables a deeper insight into complex data situations.

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Data storytelling in daily life

I think we now agree that data is pretty exciting - if we give it an exciting background, package it nicely and relate it to each other. Anyone who looks at our data on a dashboard will immediately understand what messages it conveys and what lessons we can learn from it. That is our data story.

You might even manage to present your data in a particularly situational way. Then you dive deeper and deeper into the information, jump from macro level to micro level and end up explaining in minute detail why this one figure on your dashboard is the most important figure for the overall business success of your company. Or you use a number to prove why a single person in your company has ensured exceptional sales success, which could be rolled out to all areas as an example. Or imagine this: Every single person working with your dashboards no longer just reads consolidated columns of numbers, but recognizes the context relevant to them and tells their own compelling story based on a single number. That would be a beautiful story.

Want to build dashboards that bring your data to life?

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