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Story Considerations

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Creating Dashboards and Storytelling with Tableau

Université de Californie à Davis

4.6 (411 notes) | 14K étudiants inscrits

Cours 4 de 5 dans Data Visualization with Tableau Spécialisation

Visualiser le programme de cours

Leveraging the visualizations you created in the previous course, Visual Analytics with Tableau, you will create dashboards that help you identify the story within your data, and you will discover how to use Storypoints to create a powerful story to leave a lasting impression with your audience. You will balance the goals of your stakeholders with the needs of your end-users, and be able to structure and organize your story for maximum impact. Throughout the course you will apply more advanced functions within Tableau, such as hierarchies, actions and parameters to guide user interactions. For your final project, you will create a compelling narrative to be delivered in a meeting, as a static report, or in an interactive display online.

Compétences que vous apprendrez

Storyboarding, Tableau Software, Data Virtualization, Data Visualization (DataViz)

Avis

4.6 (411 notes)

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RM

Apr 23, 2018

Its a good Course to get understanding regarding Tableau Story telling ,This course covers start to end aspects of story telling with Tableau.Its a very good course to move forward in Tableau

MM

May 24, 2018

Great course with amazing teachers and material! I especially liked the amount of technical tutorials that are given in this course. I would recommend this to anyone starting out in Tableau.

À partir de la leçon

Tell the Story of Your Data

Welcome to Module 4. Although this course focuses on Tableau, we will look at a wider range of examples and techniques to help you become a better data storyteller. By the end of this module, you should be able to leverage concepts and techniques designed to help you become a more focused and compelling storyteller with data as the foundation. We will discuss ways to avoid unintentionally creating false narratives with good data. You will also learn about what neuroscience research tells us about stories, audience engagement, and decision drivers. You will use structural story elements to help improve the relatability of the story and explore ways design and textual elements can affect the emotional tone of a story. Lastly, you will learn how to frame and format the data story based on your design checklist. Let's get started!

Tell the Story of Your Data Introduction1:37

The Art of Storytelling (Past, Present, and Future)3:27

Storytelling and the Human Brain5:28

Bringing Data to Life: Emotions and Data Storytelling7:14

Emotion Modulators: Color, Language, and Other Design Elements8:24

Framing and Format4:11

Framing, Conventions, and Priming8:12

False Narratives and Data Storytelling6:51

Telling the Stories within the Story (Part 1)5:29

Telling the Stories within the Story (Part 2)4:45

Story Considerations6:27

Preparation of the Story Points11:07

Setting Up the Story14:24

Creating Points in the Story16:18

Interactive Story6:36

Create a Data Story in a Static Presentation20:20

Enseigné par

Govind Acharya
Principal Analyst
Hunter Whitney
Sr. Consultant, Author, Instructor

[MUSIC]

Welcome back.

Before we dive into screen cast demonstrations of telling the story of

your data using Tableau,

I'd like to set the stage by reminding you of five important story considerations.

These will apply to all your data stories.

There may be more, but these are the five that I think are essential.

The first is trends, the second is rank ordering, the third is is comparisons,

the fourth is counter-intuition, and finally, the fifth is relationships.

After this lesson, you will be able to recall these five essential story

considerations, and use them to guide you whenever you have a data story to tell.

So let's get started.

First, trends are almost always time-based.

So one of the fields or variables should be also time-based.

Since it is time-based, it is often depicted in a line or a bar graph,

depending on the data.

If it's non-continuous data, and you're doing counts,

sometimes you may want to do a bar graph.

But sometimes you may want to do a line graph.

Here is an example.

This is from the sale Superstore data set.

And it's an example of a trend in a story.

The second way to tell stories with data is rank ordering.

As you see in this bar graph.

You've done something very similar to this.

This tells you who had the most sales.

Here I hovered over this to give you an example.

We can see that Ken Lonsdale is at a sales rank of six.

So he is ranked sixth from the top.

If you count down you see one, two, three, four, five and

the bar with the outline representing Ken Lonsdale's sales is indeed

the sixth bar down in this bar graph.

That's an example of rank ordering.

The third way to tell stories with data is comparisons.

This is an example from earlier in 2016 showing the comparison between

the two major presidential candidates in the United States in 2016.

This example should be somewhat familiar to most people,

even outside of the United States.

The example shows both a trend and

a comparison to see how the trend of each candidate across time is.

And also comparing them against each other.

The fourth way to tell stories with data is the counter-intuitive visualisation.

Here is an example.

In that category, you also have the unusual outlier.

This example is a classic one, so you may have seen this around.

It's the incarceration rates in the OECD, or

the Organization for Economic Cooperation and Development.

Looking at these incarceration rates you'll notice that the Unites States has,

by far and away, the highest incarceration rate.

It's so high that, in fact, if you took that out it

is actually higher than many of the other countries' incarceration rates combined.

It's 266 for Chile, the next biggest, and 710 for the United States.

That's a very good example of an unusual or an outlier.

So we can go and see why that might be.

Why is it that the United States has a higher incarceration rate?

It may be difficult to answer but at least you have that baseline to work with.

Finally, the last and fifth way to tell stories is through relationships.

This is a classic scatter plot which you actually did in the course earlier.

Here, the scatter plot reveals that there is a relationship between sales

and profit.

And that's going to be our story.

Why is that relationship not as firm as it could be?

Why are some people who are doing high sales not earning profit?

We're going to go back and look at these outliers and see why these exist.

Finally, as we're wrapping up the course and

as you get into the real world, let me share some data driven storytelling tips.

Let's start with the first.

Check your facts.

This is the biggest one of all because you're going to spend so

much time actually doing a lot of the data analysis ahead of time,

that the story itself turns out to be very straightforward in the end.

It's the preparation beforehand that often takes a lot of time.

Before you start crafting the story design, check to make sure the facts

of the story are based on reality, and that they are right.

The second tip I offer is to focus on one key statistic, and

that's what we're going to do.

How do we drill down to find that one piece of information that might

be very interesting or intriguing for

people to figure out within the bounds of what we've been asked to do?

While doing analysis be on the look out for

that one key statistic that can become a focal point.

The third tip is to use visuals.

I mean, this is, of course, a data visualisation course so, of course,

the visuals are very important.

To tell the story well, it often makes it a lot easier to be able to tell that story

through a visualisation.

The fourth storytelling tip is to make the presentation of your data insightful.

If it brings insight to your audience then that's interesting.

You should give the information in a way that makes your

insight obvious to the viewer.

Don't leave them guessing, just tell them the information and

tell it in an insightful way.

Finally, make it relatable.

Oftentimes you will use a representative person, a representative piece of data or

a representative category to tell a story of the data.

Facts and figures have more impact when they are presented as a person or

situation in a story that has relevance for your audience.

So those five data driven storytelling tips are the types of things you should

should think about as you move through your process to tell your data story.

And that concludes this lesson.

In our next lesson we will dive into the story itself.

Thanks.

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