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Know Your Audience(s)

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Essential Design Principles for Tableau

加州大学戴维斯分校

4.5（907 個評分） | 19K 名學生已註冊

課程 2（共 5 門，Data Visualization with Tableau 專項課程）

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In this course, you will analyze and apply essential design principles to your Tableau visualizations. This course assumes you understand the tools within Tableau and have some knowledge of the fundamental concepts of data visualization. You will define and examine the similarities and differences of exploratory and explanatory analysis as well as begin to ask the right questions about what’s needed in a visualization. You will assess how data and design work together, including how to choose the appropriate visual representation for your data, and the difference between effective and ineffective visuals. You will apply effective best practice design principles to your data visualizations and be able to illustrate examples of strategic use of contrast to highlight important elements. You will evaluate pre-attentive attributes and why they are important in visualizations. You will exam the importance of using the "right" amount of color and in the right place and be able to apply design principles to de-clutter your data visualization.

您將學習的技能

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

審閱

4.5（907 個評分）

5 stars
554 ratings
4 stars
256 ratings
3 stars
74 ratings
2 stars
15 ratings
1 star
8 ratings

AH

May 30, 2017

It is an excellent course!!! very well designed and very proficient talk on most difficult and most important skills related to data visualization....Enjoyed it sooo much!!!

ES

Apr 19, 2017

I found this course extremely useful as it helped me better understand design principles which can be put into good use in other visualization tools as well.

從本節課中

Design for Understanding

Making sense of large, multi-dimensional data sets can be a challenge for anyone. Your task as a designer is to make good decisions about encoding, arranging, and presenting data to reveal meaningful patterns and stories for your audiences. After completing this module, you will be able to design your visualizations for a target audience and with purpose. You will be able to identify the connection to between data, relationships and good visual design. You will implement additional design tools and tips into your visualizations.

Design For Understanding Introduction5:15

Know Your Audience(s)5:18

Design For Purpose7:20

Data, Relationships, and Design5:45

Static Versus Interactive Visualizations8:23

Multiple, Connected View4:32

Language, Labeling, and Scales5:03

Visual Lies and Cognitive Bias11:26

教學方

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

[MUSIC]

Welcome back.

As you've seen, data visualizations come in a wide and expanding range of forms,

have many different purposes and have diverse sets of potential audiences.

Are they analysts who need to comb through data to find interesting patterns, trends,

and anomalies?

Or are they executives who need quick, clear, and

reliable summaries of about some initiative or campaign?

One size definitely does not fit all.

In this lesson, I'll present a basic framework for thinking about audiences,

purposes and context for your data visualizations.

The more you can understand, empathize and anticipate the needs

of your intended audience and assemble the right elements from your toolkit,

the more successful your designs will be.

The same applies for understanding the purpose,

the visualization, and the types of data being used.

Good visualization design means effective communication with your audience.

It helps to think about the interests, needs, skills, and knowledge, and

goals of the people who will be engaging with your visualizations.

There are a few fundamental questions to keep in mind at the outset,

including, one, what are the interests, needs, and

goals of your target audience that your visualization can address in some way?

For example, this can range from general curiosity about an issue such as

the relationship of life expectancies and

personal income levels in different parts of the world.

To a specific need such as seeing a real time alert

about a potential hacker intrusion to a network.

Two, what is the audiences expected level of familiarity and

subject matter expertise with the material?

The level of prior knowledge and

expectations can have a big impact on how they view your visualization.

Prior knowledge can sometimes help, and

other times hinder, the ability and usability of your design.

We will examine the role of prior knowledge, mental models,

and bias further in a future lesson.

Three, what is the appropriate level of information density and detail that

will fit with your target audience's subject matter knowledge and needs?

Realize that providing too much, or too little, detail can sometimes be

counterproductive, depending on who's looking at the visualization.

Four, how much or

how little control do users have in interacting with visualization?

A potential trade-off here is that control can require more effort and

knowledge from the user.

You should recognize that simplicity can be relative for different types of users.

If for example, your design in meant for retail analysts, they may

need a tool that can help them uncover meaningful patterns and trends in data.

In this instance, the emphasis is on facilitating the process of exploration.

If on the other hand, the user is a sales person presenting quarterly returns

to executives, the goal is for the presentation to convey specific

relevant information as concisely as possible.

It's also important to think about the level of detail and

scope of information that different audiences may need.

In the case of the analyst,

she may need the ability to easily view data in various time scales from say,

days to years, whereas a salesperson may only need to show quarterly results.

These factors can all help guide your design strategy.

One common technique for keeping different kinds of

audiences clearly in mind is by using what I refer to as personas.

These are descriptions of user types that capture characteristics,

goals, and needs of different types of users.

For example, there can be a persona that represents a retail analyst, and

another that represents a salesperson.

While personas may not be useful for

every design project, they can provide useful summaries of important types

of people that can help sharpen your thinking about targeted design.

As we have seen, great data visualizations are designed with the needs of their

intended audience at the forefront.

There are many considerations that can guide your design choices when aiming for

that target audience.

We have touched on some important considerations in this lesson.

It's all about asking good questions at the outset.

Now the direction of a design may change and evolve over time, but

the good questions at the outset can result in great results at the end.

Creating a persona document can be a useful exercise and

adjunct for capturing the needs of your audiences.

The more you can understand and anticipate those needs, and

draw from your data visualization toolkit, the better off you're going to be.

See you next time.

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