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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
A straightforward, full-color guide to showcasing data so your audience can see what you mean, not just read about it Big data is big news! Every company, industry, not-for-profit, and government agency wants and needs to analyze and leverage datasets that can quickly become ponderously large. Data visualization software enables different industries to present information in ways that are memorable and relevant to their mission. This full-color guide introduces you to a variety of ways to handle and synthesize data in much more interesting ways than mere columns and rows of numbers. Learn meaningful ways to show trending and relationships, how to convey complex data in a clear, concise diagram, ways to create eye-catching visualizations, and much more! * Effective data analysis involves learning how to synthesize data, especially big data, into a story and present that story in a way that resonates with the audience * This full-color guide shows you how to analyze large amounts of data, communicate complex data in a meaningful way, and quickly slice data into various views * Explains how to automate redundant reporting and analyses, create eye-catching visualizations, and use statistical graphics and thematic cartography * Enables you to present vast amounts of data in ways that won't overwhelm your audience Part technical manual and part analytical guidebook, Data Visualization For Dummies is the perfect tool for transforming dull tables and charts into high-impact visuals your audience will notice...and remember.
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Veröffentlichungsjahr: 2014
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Data Visualization For Dummies®
Published by: John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030-5774, www.wiley.com
Copyright © 2014 by John Wiley & Sons, Inc., Hoboken, New Jersey
Published simultaneously in Canada
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Library of Congress Control Number: 2013949065
ISBN: 978-1-118-50289-1 (pbk); ISBN 978-1-118-50292-1 (ebk); ISBN 978-1-118-50293-8 (ebk)
Manufactured in the United States of America
10 9 8 7 6 5 4 3 2 1
Data Visualization For Dummies®
Table of Contents
Introduction
About This Book
Foolish Assumptions
Icons Used in This Book
Beyond the Book
Where to Go from Here
Part I: Getting Started with Data Visualization
Chapter 1: Introducing Data Visualization
Understanding Data Visualization
Understanding the importance of data viz
Discovering who uses data viz
Recognizing the Traits of Good Data Viz
Embracing the Design Process
Ensuring Excellence in Your Data Visualization
Chapter 2: Exploring Common Types of Data Visualizations
Understanding the Difference between Data Visualization and Infographics
Picking the Right Content Type
Appreciating Interactive Data Visualizations
Observing Visualizations in Different Fields
Using Dashboards
Discovering Infographics
Examining different types of infographics
Taking advantage of online infographic tools
Chapter 3: Knowing What You Must about Big Data
Defining Big Data
Seeing How Big Data Changes Business
Getting to know your customers
Discovering the Four V's
Collecting structured and unstructured data
Ensuring the use of quality data
Avoiding Dying by Tool Choice
Tableau
Part II: Mastering Basic Data Visualization Concepts
Chapter 4: Using Charts Effectively
Deciding Which Charts to Use and When to Use Them
Understanding where newbies should start
Choosing simple and effective charts
Using gauges and scorecards to monitor
Finding online tools for chart making
Dipping Into Less-Common Charts
Chapter 5: Adding a Little Context
Making Text Useful
Adding text labeling
Considering text positioning
Choosing text fonts
Choosing text color
Exploring Text Analysis
Determining what makes text analysis so important
Building a text analysis statement
Chapter 6: Paying Attention to Detail
Uncovering How People Digest Data
Presenting Common Visual Patterns
Z and F patterns
Pattern design
Deciding to Use a Template
Achieving Consistency across Devices
Embracing responsive design
Following app design standards
Part III: Building Your First Data Visualization
Chapter 7: Defining an Easy-to-Follow Storyboard
Business Intelligence Overview
Delving Into Your Story
Uncovering storyboard content
Identifying your audience
Documenting Goals
Documenting KPIs
Building Your First Storyboard
Section 1: Current State
Section 2: Trends
Section 3: Forecast
Section 4: What-if
Chapter 8: Developing a Clear Mock-Up
Getting Started with Your Mock-Up
Sticking to black and white
Using good ol’ pencil and paper
Using web-based or desktop tools
Building Template Layouts
Chapter 9: Adding Effective Visuals to Your Mock-Up
Recognize the Three Traits of an Effective Visual
Data is clear
Visual fits the data
Exceptions are easy to spot
Focus on Insight, Not Hindsight
Add Visuals to Your Mock-Up
Section 1: Current State
Section 2: Trends
Section 3: Forecast
Section 4: What-If
Chapter 10: Adding Functionality and Applying Color
Recognizing the Human Components
Humanizing your visualizations
Thinking mobile first
Adding functionality
Choosing navigation by using rules
Identifying the most popular menu types
Dipping Into Color
Taking advantage of company branding guidelines
Choosing colors without guidelines
Using RAG colors
Chapter 11: Adding Some Finishing Touches
Choosing Useful Links
Introducing six mandatory links
Including a last updated timestamp
Adding Legal Stuff
Embracing the copyright
Delving into terms and conditions
Discovering Visual Cues
Adding Location Intelligence
Chapter 12: Exploring User Adoption
Understanding User Adoption
Considering Five UA Measurements
Marketing to Data Viz Users
Ensure data availability and accuracy
Use buy-in and ownership to engage users
Give each data viz the right name
Use internal social media platforms and intranets
Go live on internal platforms
Do away with training
Make sure that the data viz looks great
Provide 24/7 accessibility
Provide speed and reliability
Speed the delivery of your data viz
Part IV: Putting Data Viz Techniques into Practice
Chapter 13: Evaluating Real Data Visualizations
Analyzing Data Visualizations by Category
Big-picture considerations
Color
Design issues
Text formatting
Menus
Interactivity
Design for mobile
Evaluating Data Visualizations
Data visualization 1
Data visualization 2
Data visualization 3
Data visualization 4
Data visualization 5
Data visualization 6
Data visualization 7
Data visualization 8
Data visualization 9
Data visualization 10
Data visualization 11
Data visualization 12
Chapter 14: Recognizing Newbie Pitfalls
Going Overboard with Data
Falling into the One-Shoe-Fits-All Trap
Focusing on the Tool Instead of the Story
Building Mobile Last
Abusing Pie Charts
Using Green for Alerts
Ignoring Basic Statistics
Knowing the probability that an event will occur
Applying variance to show the magnitude of change
Forecasting the future
Not Mastering User Engagement
Part V: The Part of Tens
Chapter 15: Top Ten Data Visualization Resources
Edward Tufte
Visual.ly
The Functional Art
Visualizing Data
Chart Porn
The Excel Charts Blog
FlowingData
Datavisualization.ch
GE Data Visualization
#dataviz and #bigdata
Chapter 16: Top Ten Fears of New Data-Viz Creators
Telling the Wrong Story
Creating an Ugly Data Viz
Picking the Wrong Things to Measure
Alienating Other Stakeholders
Misunderstanding the Audience for Your Data Viz
Forgetting about Copyrights and Legal Matters
Selecting the Wrong Tool
Making the Wrong Chart Choices
Picking Bad/Noncomplementary Colors
Using Too Much Data
About the Authors
More Dummies Products
Guide
Table of Contents
Begin Reading
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Introduction
Data visualization (also known as data viz) is a hot topic. With the development of more data sources, such as social media platforms, photos, and customer reviews, Big Data has become a concern for small businesses and large corporations alike. Data is coming from all parts of the business like finance, customer service, and sales, and using it effectively helps you gain a competitive advantage.
It's no longer sufficient to use a multiple-page spreadsheet to present findings about your data. You need to tell visual data stories that produce important insights. This book shows you some ways to create and display data visualizations, including infographics, dashboards, and business intelligence (BI) graphics.
Many experts in the field have created inspiring data visualizations that dazzle the eye. You should be inspired by them, rather than humbled. Not every data viz can — or should — be a devastating work of art. Some visualizations just need to get the job done. But you do want to give yourself every opportunity to create something special. We believe that reading this book will put you on the right path.
About This Book
This book was written to provide you all the information you need to get started creating high-value data visualizations. Use it as a reference guide when you're trying to select the right data, charts, text, and menus to add to your creations.
Data visualizations can be visually creative, such as infographics, or straightforward, such as dashboards. The key to creating the right one for you is to follow the Business Intelligence Dashboard Formula (BIDF), outlined in Part III of this book, and apply it to the different types of visualizations you need to create. It is suggested that you go through Part III in the order in which it is written so that you can follow the progression of the data viz from start to finish.
Within this book, you may note that some web addresses break across two lines of text. If you're reading this book in print and want to visit one of these web pages, simply key in the web address exactly as it's noted in the text, pretending that the line break doesn't exist. If you're reading this as an e-book, you've got it easy; just click the web address to be taken directly to the web page.
Foolish Assumptions
We assume that you're a highly intelligent person who is both creative and business-minded, with a flair for presenting visually appealing graphics — you wouldn't be reading this book if you weren't, right? — but you may be making your first foray into the world of data viz. So we also assume that you're reading this book for any of the following reasons:
You want to demonstrate to your colleagues that you can make data more useful by displaying it visually.You need to gain more direct knowledge about how your customers feel about your products.You're tired of using a spreadsheet program to create all your data visualizations and want to try other techniques.Your manager wants to use BI dashboards, and you've been chosen to make that happen.You want to provide your customers with useful data visualizations that help raise your company's visibility when it is shared by others.Icons Used in This Book
We packed this book with all sorts of tips, warnings, and other good hints so that you can benefit from our experience. They're identified by the following icons:
This icon lets you know about a way to make things easier, faster, or just plain smarter. Who doesn't want to be smarter?
This icon calls out something you need to remember, so take note. You may even want to write down the information.
We don't want to scare you, but we certainly want to warn you about things to avoid at all costs. Take heed.
This icon points out things that are more technical in nature. If geekiness isn't your thing, don't worry; the technical information is here for your edification if you want it.
Beyond the Book
We wrote extra content that you won't find in this book. Visit www.dummies.com/extras/datavisualization to find the following:
A handy list of “Ten Unbreakable Rules for Using Text in a Data Visualization”Additional information on using the Business Intelligence Dashboard Formula (BIDF) BlueprintA downloadable worksheet to help you determine what to include in your data vizA Part of Tens called “Top Ten Blunders to Avoid When Creating a Data Visualization”Where to Go from Here
You can travel at least two paths when reading this book: You can start at the beginning and wend your way around the topics to familiarize yourself with each one, or you can skip right to the juicy parts that interest you. It's up to you. Either way, we want you to feel confident that you've chosen the right path for yourself. We hope that this book will get you where you want to go. Enjoy the journey!
Part I
Getting Started with Data Visualization
For Dummies can help you get started with lots of subjects. Visit http://www.dummies.com to learn more and do more with For Dummies.
In this part . . .
Find out why data viz is important, who uses it, and how the design process affects the creation of a data viz.Recognize the traits of a good data viz and become familiar with the common types of data visualizations.Understand Big Data and find out how to identify and use structured and unstructured data.Chapter 1
Introducing Data Visualization
In This Chapter
Delving into data visualization
Deploying data visualizations for your audience
Embracing the data visualization design process
If you're reading this book, you're probably interested in finding better ways to visualize your information. When you help people visualize the meaning of data, you add tremendous value to any organization. In this chapter, we look at what data visualization is and what it means to different groups.
When it comes to gaining valuable insight in a company setting, the use of data visualization is critical. Companies are desperate to view and learn from their Big Data. Data visualization, however, is a growing field with a critical shortage of true experts.
Big Data refers to the voluminous amounts of information that can be collected from social media data as well as internal company data. Analyzing and extracting insights from it is the goal.
After reading this book, you'll be able to help fill that role for your company, whether you're building your first data visualization or your hundredth one.
Understanding Data Visualization
Here's a simple definition of data visualization: It's the study of how to represent data by using a visual or artistic approach rather than the traditional reporting method.
Two of the most popular types of data visualizations are dashboards and infographics, both of which use a combination of charts, text, and images to communicate the message of the data. The practice of transforming data into meaningful and useful information via some form of visualization or report is called Business Intelligence (BI).
Understanding the importance of data viz
Data visualizations (you can call them data viz for short) are widely used in companies of all sizes to communicate their data stories. This practice, known as BI, is a multibillion-dollar industry. It continues to grow exponentially as more companies seek ways to use their big data to gain valuable insight into past, current, and future events.
With the recent popularity of social media and mobile apps, the amount of data that's generated on a moment-to-moment basis is astounding. For this reason, many companies find that making sense of that data requires the use of some form of data visualization. It's virtually impossible to view 1 million rows of data and try to make sense of it!
Imagine going out to your garage every morning, jumping into your car, and then heading to work blindfolded. Chances are that you wouldn't make it past the driveway without having an accident. The same is true for a company that lacks insight into what its data is telling it. This lack of insight is dangerous, and its ramifications could be quite costly, both short- and long-term. Therefore, it's critical that companies use their data to gain insights about their performance.
This book focuses specifically on data visualizations that contain intelligent data (data that is actionable) and that provide some value to a company by enabling a person or group of people to make faster decisions based on that data.
Discovering who uses data viz
Data visualizations are for everybody. All of us use them, whether or not we realize it. If you use apps on your smartphone, for example, chances are that you depend on data visualizations to make critical decisions on an almost daily basis. Do you ever use a weather app to determine how to dress for that day? If you open the app and see a cloud with lightning at the top of the app, you have a good idea that it's going to be a stormy, rainy day without having to read any data about temperature, barometric pressure, and humidity.
This example shows you how a simple visual helps you gain quick insight and make a quick decision (in this case, to wear a raincoat and carry an umbrella). Believe it or not, you just consumed a good data visualization!
Recognizing the Traits of Good Data Viz
Good data visualizations come in all shapes and sizes, but all of them have certain traits, which we discuss in this section.
Mico once worked with a talented graphic-design expert named Natasha Lloyd to deliver a well-received presentation called “How to Build a Successful Business Intelligence Dashboard” at a major global conference. When she was asked what she thought was important about creating visualizations, Natasha said her focus wasn't on what was pretty versus ugly; her focus was on the end-user experience. Table 1-1 shows the key items discussed during the presentation.
Table 1-1 Traits of a Good Data Visualization
Trait
Description
Useful
People use it on a regular basis and can make relevant decisions by viewing all the information they need in one place.
Desirable
It's not only easy to use but also pleasurable to use.
Usable
People who use it can accomplish their goals quickly and easily.
Although these traits sound more like descriptions of a new car than descriptions of business data, focusing on these three traits for all your data visualizations should ensure that you produce something that's not only great to look at but that also provides value and deep insight to those who use it.
Although the information in Table 1-1 may seem to be simple, we advise you to use it the way we do: as a tool to measure every data viz against, to ensure that you're focusing on the most important items. Your main goal should be to develop a data visualization that provides key insights to its users.
Embracing the Design Process
One of the main goals of this book is to guide you through the process of scoping, designing, and building your first data viz utilizing intelligence data.
Many methodologies and best practices are available in the marketplace. The ones described in this book are based on Mico's experience in building more than 400 enterprise-grade intelligent data visualizations, first as a consultant and then as founder of her company (BI Brainz). The methods in the book have been tried and tested not only by Mico's team but also by thousands of people at some of the biggest companies in the world.
Although our recommended approach has been tested around the globe with lots of success, you may find that you can improve on or tweak it to better match your current environment or situation. Treat it as a starting point and solid foundation.
This book uses a methodology that Mico developed, called the BI Dashboard Formula (BIDF). To help you understand the process, we provide access to some of the templates and openly discuss our proven approach to developing these very powerful intelligent data visualizations. This method shows you the “what” (as in what data to display) as well as the “how” (as in how to add the right visuals to derive a powerful and compelling data viz).
Think of the data viz development process as being like building a house. First, you need to ensure you have the right location. Then you must develop a clear blueprint that shows exactly how the house will look. Last but not least, you lay the foundation and build the house. BIDF teaches you how to develop a visualization from start to finish.
We advise that you read this book from start to finish and avoid skipping any chapters, especially in Part II. Although the sky is the limit when it comes to building fancy data visualizations, creating useful data viz that provide true value by displaying intelligent data does require some background and a well-outlined process. A step-by-step process is explained in this book.
Ensuring Excellence in Your Data Visualization
Before you move on to the basics of building your data visualization, you should have some idea of what criteria make a data visualization excellent. An excellent data visualization has the following qualities:
It's visually appealing. The advent of more sophisticated visual creation tools and the high quality of mobile apps have raised the bar very high on the user experience. It's only going to get higher with the evolution of technology such as Google Glass. Your visualization will go unused if it looks like it was designed with old technology.It's scalable. If your data viz is successful, others will want to use and leverage it. Be sure to build your visualization on a system that's scalable for accessibility and for future maintenance and modifications.It gives the user the right information. It's a problem when users focus on the visual or a particular feature and not on what they really need. Before creating a visualization, define exactly how it will be used, such as for self-service, drill-down, deep analysis, or executive overview.It's accessible. An accessible visualization is easy to use and can be modified easily when necessary. Also, the data must be accessible on any device, at any time, at any place. This feature is critical to user adoption.It allows rapid development and deployment. Gone are the days of waterfall (chart-type) projects and drawn-out data-viz deployments and builds. Users need their information today, and if you can't provide it in a timely fashion, they'll find other ways to get it.Chapter 2
Exploring Common Types of Data Visualizations
In This Chapter
Understanding interactive graphics
Selecting content for visualizations
Looking at how different fields use visualizations
Using cool infographics
We've all seen impressive visualizations that make us feel humble. You may ask, “Could I do something like that?” Chances are that if you're creating a data visualization for the first time, the answer may be “not yet.” Creating data visualizations, like anything else, requires you to acquire some basic information and build your knowledge over time.
This chapter presents different types of visualizations so that you can familiarize yourself with the many options you have for creating data visualizations of your own.
Understanding the Difference between Data Visualization and Infographics
To simplify the process of understanding visualizations, we focus on the two most popular types: data visualizations and infographics. Because the use of graphical data visualizations is growing quickly, there is a bit of disagreement about how to define a data visualization versus an infographic. You may believe that the definition is clear, but when you get into more complex visualizations, you can start to wonder.
In their book Designing Data Visualizations (O'Reilly Media), Noah Iliinsky and Julie Steele use the following three criteria to determine whether to call a graphic a data visualization or an infographic:
Method of generation: This criterion refers to what goes into creating the graphic itself. If a lot of original illustrations are created to explain the data, for example, it's likely to be an infographic. You often see infographics with beautiful, elaborate images created to explain the information. Figure 2-1 shows an example created by Coleen Corcoran and Joe Prichard. You can see the original image at http://thumbnails.visually.netdna-cdn.com/carland-a-century-of-motoring-in-america_50290aaca56d5.jpg.Figure 2-1: Carland displays history in an easy-to-follow way.
We have another criterion to help you determine the difference between a data visualization and an infographic: whether the graphic is interactive or static.
An interactive graphic tells a different story each time new data is inserted. An interactive visualization helps you determine what the data is telling you. A static visualization depicts a data story that you want to explain to others. Figure 2-2 shows how coffee choices reflect one's personality. You can see the original image at http://img7.joyreactor.com/pics/post/comics-thedoghousediaries-coffee-672107.png.
Figure 2-2:A static visualization (infographic) isn't updated with new data.
You can use the information in Table 2-1 to determine whether you're working with an infographic or a data visualization. This table becomes useful when you want to decide what type of visualization to create for specific information and/or low-quality graphics.
Table 2-1 Data Visualizations versus Infographics
Data Visualization
Infographic
Method of generation
More numbers used
Original images created
Quantity of data
More data
Less data, more conclusions
Degree of aesthetic treatment
Less artful, more focused on information itself
More artful
Interactive versus static
Interactive (data changes)
Static (data remains fixed)
Read on to find out what types of content you can put in an infographic or data visualization.
Picking the Right Content Type
When you're creating a data visualization to tell the story of your data, you can use many content types other than text and numbers. The key is to select visuals that are not only attractive but that also match the data you have. This is not an insignificant task. Your data viz will benefit from careful consideration of a variety of different content types.
Following are several to consider:
Graph: An x and y axis is used to depict data as a visualization.Diagram: A visual that shows how something works.Timeline: A chronology is depicted on a graph to show how something happens or changes.Template: A guide for something that a user needs to fill in or develop.Checklist: A list of tasks to be completed that can be crossed off when they have been accomplished.Flow chart: A sequential set of instructions that show how something works.Metaphor: Comparisons of two dissimilar things for the purpose of making a vivid description.Mind map: Maps that enable you to show the big picture and the details of a topic on one sheet of paper. The main topic is in the center and the subtopics radiate out from it. Figure 2-3 shows an example of a mind map about the best-selling book Brain Rules by John Medina (Pear Press). It was created using the MindMeister software (https://www.mindmeister.com/100879355/brain-rules-12-principles-for-surviving-and-thriving-at-work-home-and-school).Figure 2-3: A mind map is one content type you might use for a data viz.
When you see a visualization that contains interesting content types, you should clip the image and save it to a file for future reference. That way, you'll always have images that really inspire you. You can also refer to Chapter 15, which provides a list of hand-picked resources to keep you informed and inspired.
One caveat: Make sure that your data fits the visualization that you choose. Don't try to shoehorn data in just for the sake of art.
Appreciating Interactive Data Visualizations
Sophisticated software allows people to do analysis today that they only dared dream about five years ago. Couple this with mounting data stores, and you have an interesting choice. You can put your head in the sand and hope that the data stops multiplying, or you can work at making it a valuable asset.
