In this current digital age, organizations are adapting and leveraging technological tools to gather and store data. However, collecting and storing data by itself has no meaning, as the data just exists as a figure and a statistic. It needs to be analyzed thoroughly through data visualization such as crafting out different dashboards containing a variety of charts and graphs.
This is where data analysts step in to indulge in data storytelling, which is essentially taking raw data, analyzing it and depicting meaningful information in the form of a story thereafter. Good data storytelling helps relevant stakeholders to understand and visualize the depicted information, enabling them to forge valuable insights and make key informed decisions based on the data.
Stories are regarded as a creative and effective way of conveying information as the audience uses their imagination to understand and relate to it to a certain degree, which helps in retaining key takeaways.
What is Data Storytelling exactly?
The aim of data analytics is to optimize business processes and improve decision making and results. This is attained by identifying patterns and trends in the data, where analysts would then generate actionable insights afterwards. Data storytelling is a form of engaging presentation that delivers the information effectively.
Data Storytelling contains three elements:
1. Data
In order to have an effective story, timely and accurate data is required. After collecting, storing and cleaning the data, it is then analyzed through algorithms to generate insights.
3. Visualization
Data visualization is a graphical representation of data, which includes graphs and charts. Examples are bar charts, pie charts, line graphs and more.
3. Narrative
The narrative is arguably the most important component of data storytelling as it is the story itself.
The Importance of Data Storytelling
There are a myriad of ways to communicate said insights. However, we strongly recommend data storytelling as there are plenty of benefits to it.
Having a compelling narrative accompanying the generated insights and visualizations makes the data meaningful and relevant to the targeted audience. It allows data analysts to emphasize the significance of key insights, such as particular metrics or changes in a way that resonates with the key stakeholders. It keeps their emotions and intellect engaged, resulting in a more intimate connection and understanding with the data. This further prompts them to inspire action and positive change.
On top of that, the audience does not need to possess specialized domain knowledge as the stories are comprehensive and easy to interpret.
All in all, data storytelling simplifies complex data while also providing context, insights and the ease of interpretation.
What is Tableau?
Tableau is one of the most widely used data visualization tools in the business intelligence industry. It excels in analyzing big data and aids in the creation of graphical representations where experts at every level in a company can easily interpret it.
Since data visualization is a core component of data storytelling, being proficient in Tableau is important. If you are a newbie reading this, fret not, as there are plenty of Tableau certification courses available online.
Stories in Tableau
Tableau stories are a series of collated visualizations that communicate ideas. It is used for various purposes, namely, data storytelling, providing context, portraying how decisions impact different outcomes or establishing a compelling case.
Since a story is a sheet, methods used to create, name and manage worksheets and dashboards are applicable to stories as well. This feature functions as a collation of sheets and arranges them sequentially. Each individual sheet in a story is known as a story point.
Tableau encourages interaction when you share these stories by publishing a workbook to Tableau Public, Tableau Server or Tableau online. Users are able to input their opinions and arguments, which value-adds to the process of generating valuable insights.
Types of Data Stories
- Change Over Time
- Purpose: Portrays a trend using time-series data.
- Potential discussions: Reasons for the occurrence of particular events, Suggestions for improvement to make or prevent it from happening.
- Drill down
- Purpose: Provides context for the audience to easily interpret what is happening within the chosen category.
- Potential discussions: Reasoning as to why this person, place or object is different and comparisons in terms of history and performance.
- Zoom Out
- Purpose: Describes how a topic important to your audience fits into the bigger picture.
- Potential discussions: How does something you care about fit into the bigger picture and possible effects.
- Contrast
- Purpose: Displays the differences between two or more subjects
- Potential discussions: The reasons for the differences of the subjects, identifying areas to be improved on.
- Intersections
- Purpose: Highlights important shifts when one category outperforms the other.
- Potential discussions: Causes of the shifts, whether the shifts are good or bad.
- Factors
- Purpose: Explains a particular subject by splitting it into types or categories.
- Potential discussions: Categories that should be focused on more, how much do these items
- Outliers
- Purpose: Highlight anomalies or where things are considered abnormal.
- Potential discussions: Reasoning as to why this person, place or object is different.
How do I make a Story?
You start off by selecting the New Story option.
A. Options to add new story point: To add a new point, select either ‘Blank’ to add a new point or ‘Duplicate’ to use the current story point as the initial place for the next point.
B. Story Pane: This pane is used to drag and drop dashboards, sheets and text descriptions into the story sheet. In addition, you can set the size of your story and choose to show or hide the title.
C. Layout Pane: You can select your navigator style and choose to show or hide the forward and back arrows.
D. Story Menu: In this menu, you can choose to format the story, or copy or export the current story point as an image. Furthermore, you can clear the story, and show or hide the navigator and story title.
E. Story toolbar: When your mouse scrolls over this navigation area, this toolbar appears. Within this toolbar, you can undo changes, update a particular story point, create a new story point or delete the current story point.
F. Navigator: Within this navigator, you can edit and organize your story points in order. The style can be changed by going to the layout pane.
Want to be an effective data storyteller?
As you arrive at the end of the article, you would have already learnt about the significance of data storytelling and realized how useful it can be when presenting to key stakeholders. This is especially relevant if you are an aspiring data analyst or data scientist.
In order to be an effective data storyteller using software like Tableau, you would first need to learn the basics of data visualization.
Tableau Course in Singapore
If you are interested in getting started on data visualization and storytelling, there are courses being offered which cover the fundamentals. For instance, an introduction to Tableau course in Singapore being provided by Vertical Institute. Vertical Institute is considered one of the best Tableau courses online with community reviews of 4.9 stars. Not only would you get to learn Tableau, you also stand to learn other in-demand data analytics skills such as Excel and SQL. Courses are beginner-friendly and no prior background knowledge is required. Want structured guidance on Basic? Explore the Basic Courses For Beginners at Vertical Institute.
Kickstart your journey to becoming a Data Analyst by joining our Data Analytics course in Singapore today!
