Cover
Introduction
1. Who Should Read This Book
2. What You Will Learn
3. How This Book Is Organized
Part I: Data Studio Basics
1. CHAPTER 1: Data Studio and the Data Citizen
  1. Data, Data Everywhere
  2. The Role of Data Studio
  3. Where to Go for Help
  4. Time to Get Started!
2. CHAPTER 2: Cooking with Google Data Studio
  1. Our First Example
  2. Summary
3. CHAPTER 3: Enhancing Basic Graphs
  1. Static Report Design
  2. Before Getting Started: Things You'll Need
  3. Summary
4. CHAPTER 4: Data Exploration with Interactive Elements
  1. Building Our Workbench Example
  2. Adding Chart Components and Graphic Elements
  3. Adding and Configuring Filter Controls
  4. Tips for Using Interactive Filters
  5. Find the Answers: Filter Challenge
  6. Summary
Part II: Business and Marketing Applications
1. CHAPTER 5: Web Data Visualization with Google Analytics
  1. Google Services for Websites and Business
  2. A Brief Primer for Google Analytics
  3. Modifying the Charts
  4. Working with the New Report
  5. Now for a Side Dish: Adding a Page and Using Filters
  6. Summary
2. CHAPTER 6: Using Google Search Console for Audience Insights
  1. Search Console and Search Results Pages
  2. Creating a Search Console Report with Data Studio
  3. Bon Appetite! Using the Search Console Report
  4. Summary
3. CHAPTER 7: Viewing Local Organization Data from Google My Business
  1. Google Search and the Local Organization
  2. Step 1. Selecting the Dish to Prepare
  3. Step 2. Let's Go Shopping and Assemble the Ingredients
  4. Step 3. Setting the Table
  5. Summary
Part III: Beyond the Office
1. CHAPTER 8: Getting Personal
  1. Creating Your Own Data
  2. Curating Data from Other Sources
  3. Working with Data Generated for You
  4. Bringing It All Together
  5. Summary
2. CHAPTER 9: Going Public
  1. Shared Data Sets
  2. Searching for Data Sets
  3. Getting Data from Kaggle
  4. Bringing It Home: Real Estate in Your Neighborhood
  5. Sharing Your Dish: Embedding Reports
  6. Summary
3. CHAPTER 10: Where Do You Go from Here?
  1. Helping Your Audience See the Light
  2. Exotic Ingredients and Your Pantry
  3. Summary
Index
End User License Agreement

List of Illustrations

Chapter 1
1. Figure 1.1: Data Studio Gallery
Chapter 2
1. Figure 2.1: The finished product
2. Figure 2.2: Using the date range selector
3. Figure 2.3: Exporting bank account data
4. Figure 2.4: Typical Google Drive structure
5. Figure 2.5: Creating a new folder
6. Figure 2.6: Opening a CSV file with Google Sheets
7. Figure 2.7: Removing descriptive rows from the sheet
8. Figure 2.8: Removing unneeded columns
9. Figure 2.9: Credit and debit columns
10. Figure 2.10: New Transaction Amount column
11. Figure 2.11: Data Studio home page
12. Figure 2.12: Welcome To Google Data Studio screen
13. Figure 2.13: Starting with a blank canvas
14. Figure 2.14: Find and select the Google Sheets connector.
15. Figure 2.15: Authorizing connector
16. Figure 2.16: Google Sheet selection options
17. Figure 2.17: Set the field type and aggregation method for the Transaction A...
18. Figure 2.18: Setting the report name
19. Figure 2.19: Setting the size of the page canvas
20. Figure 2.20: Edit mode menus and toolbar
21. Figure 2.21: Selecting the simple table chart
22. Figure 2.22: Table chart and Data control panel
23. Figure 2.23: Setting the Sort field
24. Figure 2.24: Adjusting column sizes
25. Figure 2.25: Unchecking the Row Numbers and Show Pagination settings on the ...
26. Figure 2.26: Selecting Scorecard from the Add A Chart drop‐down menu
27. Figure 2.27: Setting the Scorecard metric
28. Figure 2.28: Editing a metric label in a chart
29. Figure 2.29: Changing a field label
30. Figure 2.30: Positioning the scorecard
31. Figure 2.31: Changing the background color
32. Figure 2.32: Copying and positioning the original scorecard
33. Figure 2.33: Setting the Max Aggregation type
34. Figure 2.34: Positioning the copy of the Max Balance scorecard
35. Figure 2.35: Min Balance field settings
36. Figure 2.36: Report with scorecards added
37. Figure 2.37: An abstract time series
38. Figure 2.38: Chris Cooper's checking account balance chart
39. Figure 2.39: Selecting Smoothed Time Series Chart
40. Figure 2.40: Setting the time‐series chart metric
41. Figure 2.41: Placing the time‐series chart on the page
42. Figure 2.42: Selecting Linear Interpolation to fill in missing points
43. Figure 2.43: Placing the header bar
44. Figure 2.44: Setting text box styles
45. Figure 2.45: Text box for the header
46. Figure 2.46: Image added to header
47. Figure 2.47: Adding a Date Range control
48. Figure 2.48: Setting the default date range
49. Figure 2.49: Selecting Get Report Link
50. Figure 2.50: Clicking Change Sharing Settings
51. Figure 2.51: The link icon creates a shareable link.
Chapter 3
1. Figure 3.1: The finished product
2. Figure 3.2: Click the copy icon.
3. Figure 3.3: Copy This Report data source options
4. Figure 3.4: Changing the new report title
5. Figure 3.5: Selecting the data source for the page
6. Figure 3.6: Available data sources
7. Figure 3.7: Setting the default date range
8. Figure 3.8: Copying and updating the new text box
9. Figure 3.9: Setting the comparison date range
10. Figure 3.10: Updated style settings
11. Figure 3.11: Changing Show As to display months
12. Figure 3.12: Setting up the table visualizations
13. Figure 3.13: Setting the PDF options
14. Figure 3.14: Password protection on PDF files
Chapter 4
1. Figure 4.1: The workbench (default view)
2. Figure 4.2: The workbench in action
3. Figure 4.3: Sharing a link to a Google Sheet
4. Figure 4.4: Starting a new report
5. Figure 4.5: Naming the report
6. Figure 4.6: Selecting the URL option
7. Figure 4.7: Setting up the fields
8. Figure 4.8: Creating the Transaction Type field
9. Figure 4.9: Creating the ABS Amount field
10. Figure 4.10: Selecting Open Link In New Tab
11. Figure 4.11: Selecting header elements and copying them to the clipboard
12. Figure 4.12: Our new header
13. Figure 4.13: Placing the pie chart
14. Figure 4.14: Selecting the bar chart
15. Figure 4.15: Adjusting the label area in the bar chart
16. Figure 4.16: Effect of adding the breakdown dimension to the bar chart
17. Figure 4.17: Removing the legend from the bar chart
18. Figure 4.18: Dimension Value Colors panel
19. Figure 4.19: Selecting the standard line chart
20. Figure 4.20: Adding a filter control component
21. Figure 4.21: Sharing the report for editing
22. Figure 4.22: Using the Only setting on a filter
23. Figure 4.23: Searching for entries in the filter
24. Figure 4.24: Largest expenditure answer hidden at bottom of table
Chapter 5
1. Figure 5.1: A typical Google Analytics view
2. Figure 5.2: The example template on the home screen
3. Figure 5.3: The Acme Marketing template
4. Figure 5.4: This data control allows any analytics to load.
5. Figure 5.5: Copying a report with current settings
6. Figure 5.6: Copying elements from existing reports
7. Figure 5.7: Top of report customized
8. Figure 5.8: Changing the default date range
9. Figure 5.9: Adjusting the donut hole
10. Figure 5.10: Geographic Zoom Area options
11. Figure 5.11: System error on the map chart
12. Figure 5.12: Removing the dimensions restores the map.
13. Figure 5.13: Selecting an analytics view from the data control
14. Figure 5.14: Scorecards for last 28 days
15. Figure 5.15: Scorecards for January to June 2019
16. Figure 5.16: Time series for January to June 2019
17. Figure 5.17: Isolating Spain and Social sessions
18. Figure 5.18: Viewing traffic from cities in Spain
19. Figure 5.19: Isolating the traffic spike period
20. Figure 5.20: Finding the source: a beach party in Spain!
21. Figure 5.21: Applying an age and gender filter from the stacked bar chart
22. Figure 5.22: Duplicating the main report page
23. Figure 5.23: Setting the page navigation position
24. Figure 5.24: Left and top page navigation compared
25. Figure 5.25: Adding a filter from the Current Page Settings panel
26. Figure 5.26: Configuring a filter for Spain
27. Figure 5.27: Setting Zoom Area to Spain
28. Figure 5.28: Completed update for map configuration
29. Figure 5.29: Completed Spain page and report navigation
Chapter 6
1. Figure 6.1: Selecting a property to view in Search Console
2. Figure 6.2: Search Console Overview screen
3. Figure 6.3: Search Console query view
4. Figure 6.4: Search results for the example query
5. Figure 6.5: Query metrics for a single page
6. Figure 6.6: The completed Search Console report
7. Figure 6.7: Creating a new data source
8. Figure 6.8: Creating a new data source
9. Figure 6.9: Formula for the Search Type field
10. Figure 6.10: The CONTAINS_TEXT() help box
11. Figure 6.11: The Target page hyperlink setup
12. Figure 6.12: The Query‐Search hyperlink setup
13. Figure 6.13: The fields setup completed
14. Figure 6.14: Setting the default date range
15. Figure 6.15: Moving the pie chart legend to the top
16. Figure 6.16: The Data tab setup for the time‐series chart
17. Figure 6.17: Switching Clicks to the right y‐axis
18. Figure 6.18: Drilling down to investigate my search view spike
19. Figure 6.19: Using the hyperlink to investigate SERPs
20. Figure 6.20: Filtering out noisy data using the Filter control
21. Figure 6.21: Finding questions to answer
22. Figure 6.22: Soul Synergy initial view
23. Figure 6.23: Investigating another spike
24. Figure 6.24: Looking for clues in the SERPs
25. Figure 6.25: Simulating a Mobile Phone Changes the Search Results
26. Figure 6.26: Brand search performance
27. Figure 6.27: Crystal‐clear interest
28. Figure 6.28: Exporting the crystal‐related terms
Chapter 7
1. Figure 7.1: A search for churches with location listings
2. Figure 7.2: A typical GMB church listing
3. Figure 7.3: An active GMB listing
4. Figure 7.4: GMB locations view
5. Figure 7.5: GMB home screen
6. Figure 7.6: Queries and date range selection
7. Figure 7.7: Breakdown of search types
8. Figure 7.8: Search and Maps views
9. Figure 7.9: Customer Actions area chart
10. Figure 7.10: Directions Requests map
11. Figure 7.11: Customer photo views
12. Figure 7.12: Posts for events
13. Figure 7.13: The completed report—Actions page
14. Figure 7.14: Without the Cumulative setting
15. Figure 7.15: The completed report—Reviews page
16. Figure 7.16: The completed report—Search page
17. Figure 7.17: Starting the new data source setup
18. Figure 7.18: GMB connectors
19. Figure 7.19: Jepto connector setup screen
20. Figure 7.20: Link to access the Jepto connector
21. Figure 7.21: Accessing the Jepto connectors
22. Figure 7.22: The fields setup screen
23. Figure 7.23: The Jepto report template
24. Figure 7.24: Using the location selector to filter results
25. Figure 7.25: Creating the Replied field
26. Figure 7.26: Creating the Replied Rate field
27. Figure 7.27: Adding the data source to the report
28. Figure 7.28: Adding the header logo
29. Figure 7.29: Setting the default date range
30. Figure 7.30: Setting Date Range picker to report level
31. Figure 7.31: Changing page names
32. Figure 7.32: Background, Border, and Padding configuration
33. Figure 7.33: Clicking the insert link icon
34. Figure 7.34: Setting the link for the Actions page
35. Figure 7.35: Removing the link for the Actions page
36. Figure 7.36: The Actions Page with Money Metrics
37. Figure 7.37: Setting the chart layer order
38. Figure 7.38: Setting the location filter
39. Figure 7.39: Copying a search charts row
40. Figure 7.40: Bullet chart below goal target
41. Figure 7.41: Bullet chart Data tab settings
42. Figure 7.42: Bullet chart Style tab settings
43. Figure 7.43: Mobile view with and without the report header
Chapter 8
1. Figure 8.1: A task list in Google Sheets
2. Figure 8.2: A form for logging writing tasks
3. Figure 8.3: Feedback form and Comments table
4. Figure 8.4: Dog Walk report with embedded form
5. Figure 8.5: Selecting Google Forms
6. Figure 8.6: Adding a date selector for the first question
7. Figure 8.7: Setting a numeric validation for a question
8. Figure 8.8: Setup for the Time Of Day drop‐down menu
9. Figure 8.9: Setup for the Temperature question
10. Figure 8.10: Setup for the Dog Happiness Rating question
11. Figure 8.11: Setup for the Walker Happiness Rating question
12. Figure 8.12: Create a Sheet for data collection
13. Figure 8.13: Previewing the form
14. Figure 8.14: Completed form entry
15. Figure 8.15: Copying the Link URL for the form
16. Figure 8.16: Creating a new data source
17. Figure 8.17: Connecting to Google Sheets
18. Figure 8.18: Creating the Total Happiness field
19. Figure 8.19: Setting the field types and aggregation methods
20. Figure 8.20: Setting the URL in the URL Embed Properties
21. Figure 8.21: Data tab settings for Chart 1
22. Figure 8.22: Style Axis settings for Chart 1
23. Figure 8.23: Data settings for Chart 2
24. Figure 8.24: Linear trendline for Chart 3
25. Figure 8.25: Exponential trendline for Chart 3
26. Figure 8.26: Polynomial trendline for Chart 3
27. Figure 8.27: Data tab settings for Chart 3
28. Figure 8.28: Setting the trendline in the Style tab for Chart 3
29. Figure 8.29: Data tab settings for Chart 4
30. Figure 8.30: Style tab axis settings for Chart 4
31. Figure 8.31: Bubble details for Walker Rating 2
32. Figure 8.32: Bubble details for Walker Rating 5
33. Figure 8.33: Bubble details for Dog Rating 1
34. Figure 8.34: Data Studio collection example
35. Figure 8.35: Authorizing Twitter to work with IFTTT
36. Figure 8.36: Starting the new IFTTT applet building process
37. Figure 8.37: IFTTT Twitter triggers
38. Figure 8.38: IFTTT Twitter search terms
39. Figure 8.39: Click the plus button.
40. Figure 8.40: Configuring action fields
41. Figure 8.41: Checking IFTTT applet activity
42. Figure 8.42: Adding headers to the Sheet
43. Figure 8.43: Connecting to Sheet for tweets
44. Figure 8.44: Creating the Tweet link field
45. Figure 8.45: Checking the field types
46. Figure 8.46: The Data Studio Twitter search report
47. Figure 8.47: Filter control Data tab configuration
48. Figure 8.48: Scorecard Style tab configuration
49. Figure 8.49: Time‐series configuration error
50. Figure 8.50: IFTTT Alexa triggers
51. Figure 8.51: Configuring Alexa action fields
52. Figure 8.52: Checking IFTTT Alexa activity
53. Figure 8.53: Adding headers to the Alexa Sheet
54. Figure 8.54: An Alexa listening workbench
55. Figure 8.55: Bar chart sorting and drill down
56. Figure 8.56: Enabling sorting on the bar chart
57. Figure 8.57: Setting Opacity in the image Style tab
58. Figure 8.58: Setting points and trendline in the time‐series Style tab
59. Figure 8.59: Formula for Search field for Songs
60. Figure 8.60: YouTube results for Search link
61. Figure 8.61: Tab A—the Google Fit source folder
62. Figure 8.62: Tab B—the Developer Hub page
63. Figure 8.63: Tab B—starting a new project
64. Figure 8.64: Tab A—copying appsscript.json code
65. Figure 8.65: Tab B—pasting the appsscript.json code
66. Figure 8.66: Tab A—copying the Connnector.js code
67. Figure 8.67: Tab B—pasting the Connnector.js code
68. Figure 8.68: Tab B—all JavaScript files replicated from Tab A
69. Figure 8.69: Tab B—Deployments screen with link
70. Figure 8.70: Connector authorization screen
71. Figure 8.71: Unverified app screen after you click the Advanced link
72. Figure 8.72: Final authorization screen
73. Figure 8.73: Selecting data for Google Fit
74. Figure 8.74: Google Fit Dashboard from Datasaurus Rex
75. Figure 8.75: Google Data Studio Resources—main page
76. Figure 8.76: The GDSR Submit A Resource To The Guide form page
77. Figure 8.77: The GDSR Twitter Feed page
78. Figure 8.78: The GDSR historical tweets page
79. Figure 8.79: The GDSR report Analytics page
80. Figure 8.80: Google Analytics Sign Up page
81. Figure 8.81: Google Analytics Property Details
82. Figure 8.82: Copying the tracking ID code for Data Studio setup
83. Figure 8.83: Pasting the tracking ID into Report Settings
Chapter 9
1. Figure 9.1: Searching for data sets related to first names
2. Figure 9.2: Exploring the search results
3. Figure 9.3: Create Kaggle Account page
4. Figure 9.4: Your Kaggle home page
5. Figure 9.5: Data set search results for UFO
6. Figure 9.6: Detail for the scrubbed data set
7. Figure 9.7: Clicking the View In Data Studio icon to connect
8. Figure 9.8: Opening your account information from the confirmation pop‐up
9. Figure 9.9: Creating a new API token from the Kaggle account page
10. Figure 9.10: Choosing an account to use with the Kaggle connector
11. Figure 9.11: Submitting your Kaggle credentials to connect
12. Figure 9.12: Complete connector setup
13. Figure 9.13: Completed fields setup
14. Figure 9.14: U.S. UFO Sightings Workbench
15. Figure 9.15: Pivot table used to filter selections
16. Figure 9.16: USA ONLY report filter settings
17. Figure 9.17: Pivot table dimensions and metrics
18. Figure 9.18: Pivot table totals and sorting settings
19. Figure 9.19: Remove Null Month filter
20. Figure 9.20: Where is the Extract Data Connector?
21. Figure 9.21: Starting the copy process
22. Figure 9.22: Clicking the current data source
23. Figure 9.23: Selecting the Extract Data Connector
24. Figure 9.24: Selecting the source for the extract
25. Figure 9.25: Fields set up for the Extract Data Connector
26. Figure 9.26: Saving settings and extracting data
27. Figure 9.27: Updating the name and field types for the data source
28. Figure 9.28: Removing the original data source
29. Figure 9.29: data.world result in Google Dataset Search
30. Figure 9.30: Makeover Monday data sets
31. Figure 9.31: The challenge page at data.world
32. Figure 9.32: Clicking Connect To Third‐Party Apps
33. Figure 9.33: Clicking the Open In App Icon
34. Figure 9.34: Activating Google Data Studio
35. Figure 9.35: Selecting Google Data Studio for integration
36. Figure 9.36: Removing Limit 5000 from the SQL query
37. Figure 9.37: Creating the Series Name field
38. Figure 9.38: A finished report for Makeover Monday
39. Figure 9.39: Changing the sharing settings
40. Figure 9.40: Selecting Anyone On The Internet Can Find And View
41. Figure 9.41: Using a thumbnail URL for a report
42. Figure 9.42: The column chart from the report
43. Figure 9.43: Same data in a 100% stacked area chart
44. Figure 9.44: Same data in a standard stacked column chart
45. Figure 9.45: The treemap chart from the example
46. Figure 9.46: The treemap chart with branch levels exposed
47. Figure 9.47: Selecting the year 2008 for drill‐down to Series Name
48. Figure 9.48: Treemap for drill down to 2008 Series Name
49. Figure 9.49: Treemap for the 2008 Women's Murder Club Series book titles
50. Figure 9.50: Sketch of the housing report
51. Figure 9.51: Downloading data from Zillow
52. Figure 9.52: The main data selector on Redfin
53. Figure 9.53: Selecting Neighborhood for Region Type
54. Figure 9.54: Selecting neighborhoods and villages
55. Figure 9.55: Clicking the table is the secret step!
56. Figure 9.56: Clicking the download icon and selecting Data
57. Figure 9.57: Clicking the Download All Rows As A Text File link
58. Figure 9.58: Opening the CSV file with Google Sheets
59. Figure 9.59: The Median Sale Price is not a number!
60. Figure 9.60: Fixing the K issue with Find and Replace
61. Figure 9.61: The executed plan
62. Figure 9.62: Original neighborhood listing format
63. Figure 9.63: The final example design
64. Figure 9.64: Setting dimension properties
65. Figure 9.65: Using the custom picker to select an exact color
66. Figure 9.66: Getting the embed code
67. Figure 9.67: Set sharing options for embedding
68. Figure 9.68: Google Site ready for report embedding
69. Figure 9.69: Selecting Embed from the circular editing menu
70. Figure 9.70: Using the embed URL for Google Sites
71. Figure 9.71: Completed Google Site with report embedded
72. Figure 9.72: Selecting the area for the embed
73. Figure 9.73: Pasting the embed code for the report
74. Figure 9.74: The WordPress page with the report embedded
75. Figure 9.75: Data Studio pivot table
76. Figure 9.76: Default view of Script Editor
77. Figure 9.77: Setting names to Unpivot
78. Figure 9.78: Entering the Unpivot function
79. Figure 9.79: Original pivot sheet layout
80. Figure 9.80: Unpivot function result
Chapter 10
1. Figure 10.1: Explaining anomalies in the time‐series chart
2. Figure 10.2: Using shading and text for annotation
3. Figure 10.3: A scrollable text box for long text descriptions
4. Figure 10.4: Embedding a YouTube video
5. Figure 10.5: Dynamic annotation fields in a chart and table
6. Figure 10.6: The date range changes update the annotations displayed.
7. Figure 10.7: Completed instruction layer page
8. Figure 10.8: Constructing the callout box
9. Figure 10.9: Completed detail layer page
10. Figure 10.10: Completed main page with link icons
11. Figure 10.11: Setting community visualization access
12. Figure 10.12: Selecting a community visualization chart
13. Figure 10.13: Completed Sunburst chart
14. Figure 10.14: A basic data widget
15. Figure 10.15: A Data Studio part finder
16. Figure 10.16: Comparing mountain bikes
17. Figure 10.17: Finding the right mountain bike
18. Figure 10.18: Selecting charts for a blend
19. Figure 10.19: Blended chart and properties
20. Figure 10.20: Blend data properties configuration
21. Figure 10.21: Our new Total Combined Sessions field
22. Figure 10.22: Final Total Combined Sessions chart
23. Figure 10.23: Ready to upload a new CSV file
24. Figure 10.24: File uploaded successfully
25. Figure 10.25: Name your BigQuery project.
26. Figure 10.26: Choosing Explore Public Datasets
27. Figure 10.27: Selecting a data set table
28. Figure 10.28: Selecting Explore With Data Studio
29. Figure 10.29: Selecting a new geo map chart
30. Figure 10.30: Updated color scale for the map

Introduction

I'll confess that when I was initially approached to write a book about Google Data Studio, I was hesitant. At the time, I was building a reputation, and some authority, on the subject. I particularly enjoyed blogging, giving presentations, and collaborating with newfound colleagues. It was exciting to explore the bounds of what was possible with each new release. But write a book on the subject? That was another matter, for sure.

I thought it might be a fool's errand to try to capture all the capabilities of such a quickly evolving platform in book form. After reading and reviewing hundreds of resources about Google Data Studio over the past few years, I had seen many “ultimate” guides published on the web, only to be outdated soon after their release. I seriously considered turning down the opportunity.

What changed my mind was a reflection on why I enjoyed working with Data Studio in the first place. It was the feeling of empowerment. I had found Data Studio to be like the Swiss Army knife of data visualization tools: although it certainly is not the best tool for every job, you can do quite a lot with it, and it is easily accessible.

Developing the ability to make sense of the tremendous amounts of data generated in our society is a challenge as well as an opportunity. Both individuals and large corporations can benefit from increased access to data if the tools to work with it are accessible and approachable. I believe that Data Studio meets these requirements and can help in the democratization of these skills.

The development of data literacy, and increasing your ability to communicate insights through visualization, is not just a set of skills to be used in a business context. Although it is becoming increasingly important for businesses to develop these skills, you can go beyond the business context and use these capabilities for your community and your personal interests.

Data Studio continues to evolve sophisticated features, but the fundamental capabilities have remained available and accessible to users at all levels. My approach to writing this book was not to provide an exhaustive detailing of features or to dive into the latest or most exotic implementations, as fun as that might be. The challenge in writing this book was to provide the reader with access to the fundamentals and guide them through the development process with examples that are relevant to their interests. The goal is to provide a foundation for those who want to explore or develop data skills.

During the writing of this book, which took several months, there were more than 20 Data Studio updates and releases. Despite all those changes, there have been only a few cosmetic updates to the examples provided. My hope, and so far, my experience, is that this book will be of value for some time to come. It is designed as a survival guide: a resource to get you started and see you safely through the challenges of working in areas that might be unfamiliar.

Beyond this book, you should find resources available to empower you to pursue your own interests even further and take advantage of new features as they become available.

Who Should Read This Book

This book is primarily designed with novices in mind. It is heavily weighted in favor of those who may be unfamiliar with the many different systems and services available. A wide range of applications are covered in this book, and chances are good that you will have an interest in several of the topics. This book should help

Beginners looking for an accessible way to get started building skills in data visualization and analysis
Those interested in gaining experience with data visualization tools
Organizations looking for better ways to communicate their community involvement
Small business owners looking to gain insight and monitor their websites and business listings
Freelancers or small agencies looking to add better reporting capabilities for their clients
People involved in organizations that can benefit from better reporting and communication capabilities
People who have an interest in building their data skills and literacy for career enhancement
Those who need to gain experience using Data Studio specifically due to business adoption
Individuals interested in using their own data for personal growth
People interested in analyzing and reporting on public data

What You Will Learn

This book provides a practical guide to many of the steps in the data life cycle. You'll learn how to find data, connect to data services, retrieve data, and study the basics of data preparation. We'll cover the basics of report design as well as using reports for analysis and insight discovery. And, of course, you'll learn all about using Data Studio as a tool for data visualization, analysis, and communication.

Throughout most of this book, we'll use a basic cooking analogy to guide you through the steps of creating reports and applications. We'll usually start with the finished product so that you can see the main components used in each example, and we'll then proceed to re‐create the example.

For each example, I'll walk you through all the steps and not just how to create the report itself. It's important to know how and where to shop for data, how to prepare the data when necessary, and how to use the finished product.

Data Studio is a tool that can help you find your own insights from data in addition to being a medium for visual data communication. The more you work with data, the more you will build greater intuition as to where to look for insights. At the same time, your skills in analysis will grow. Again, there is no substitute for practice and experience.

It is my hope that as you work with your own data and learn to use the tools discussed in this book, you'll become more than a passive consumer of other people's work. Hopefully, you'll develop an appreciation of well‐crafted communications. Also, you may develop a healthy skepticism for data presented in ways designed to promote a conclusion rather than to highlight an insight.

You have to expend a lot of mental energy in order to gain your own insights and even more energy to communicate them to an audience. I have found that working on topics and areas that interest me personally provides the motivation to expend the effort required.

My advice is to find an area of your own interest, in your personal, business, or public life, and explore that area with the tools now available.

How This Book Is Organized

Each chapter in the book has its own set of online resources. You'll find links to the live Data Studio examples, online references, and services. In addition, sample data files are provided for Part I so that you can follow along using the example data. You can access all of the online resources at www.wiley.com/go/handsondatastudio.

Part I: Data Studio Basics

This group of chapters covers the basics of working with Data Studio.

Chapter 1: Data Studio and the Data Citizen This chapter is designed to introduce users to the tools and skills that you'll be building by following the examples in this book. It explores the concepts involved in the data life cycle, the increased demand for data skills, and the roles that Data Studio can fill.
Chapter 2: Cooking with Google Data Studio This chapter will help users new to Data Studio to get up and running with the tool. Starting from scratch, we go from account setup, to personal financial data retrieval, to basic data preparation. After data preparation, we build the example report.
Along the way, you'll be introduced to basic Data Studio concepts and how to use the fundamental features of the tool. We'll cover in detail how to set up a Google Sheet with a new data connection and add that to your report. We'll also explore several of the fundamental chart visualizations and focus on configuration options that are most commonly used. Finally, you'll learn how to share the report.
Chapter 3: Enhancing Basic Graphs This chapter builds on the example created in Chapter 2. Here we cover the setup and configuration options that are important to most users, from chart visualization options to time range comparisons. I also provide an introduction to grouping concepts in order to build the updated report.
This chapter also covers how to copy Data Studio reports and reuse elements in order to save time. You'll learn more about static report design and how to use Data Studio to create password‐protected PDFs for safe report sharing.
Chapter 4: Data Exploration with Interactive Elements This chapter sticks to using personal accounting data, but instead of creating static reports, we build a workbench designed for analysis. The chapter then explores the major interactive features available to Data Studio users, and it provides guidance on using various interaction options.
This chapter also introduces you to modifying and augmenting data using Data Studio functions when it is inconvenient, or impossible, to modify the source data. The last part of the chapter explores how to use the report as an analysis tool to answer specific questions.

Part II: Business and Marketing Applications

This part caters to the natural strengths of Data Studio. The focus here is on reporting for web application data, but the concepts are transferrable to other systems as well. In this set of chapters, we explore three main applications that, because of the widespread use of the web, are quite likely to be of interest to the largest set of users.

Another aspect that links these applications together is the use of data that is “live.” This connection to live data sources, ones that are constantly updating and changing, lends itself well to the concept of dashboards, another major report type often developed in Data Studio.

Chapter 5: Web Data Visualization with Google Analytics This chapter explores the major Google web measurement services, their roles, and their applications, and it dives deeper into using Data Studio with Google Analytics. Even if you don't have a web property with which to work, you'll be able to follow along by using Google's demo connectors that simulate a live website as we create the example report.
Google Analytics is one of the most widely used data collection tools globally, so naturally it is of interest to a lot of people. Although Google Analytics has its own charting capabilities, it can be difficult to create polished reports and share them with stakeholders. This chapter looks at how Data Studio can help those who report on web properties save time communicating insights as well as providing a powerful interactive platform for exploring data.

Along with making use of Google Analytics as a data source, this chapter explores working with premade templates to speed up development, applying dynamic data controls to extend the use of reports, and creating multiple‐page reports.

In addition to working with an extensive data source like Google Analytics, you'll be introduced to several new chart types and some advanced interaction features such as drill‐down capability.
Chapter 6: Using Google Search Console for Audience Insights This chapter covers another widely used and important service for website owners. We take a closer look at the service and the data that it can provide about what people are searching for and how to use that information to connect to the audience for the website.
A substantial amount of this chapter is devoted to live cases of using Data Studio reports. The example reports are used to investigate a website's historical mysteries and find valuable, actionable insights for a real business.

Along the way, you'll learn how to increase the value of your data by adding your own categories and how to use hyperlinks to extend the user experience beyond your report pages.
Chapter 7: Viewing Local Organization Data from Google My Business This chapter wraps up this section with an extensive look at Google My Business (GMB). We look at the role that GMB plays in the marketing of local businesses and organizations and its growing importance. Digging into the application, we discover why using Data Studio makes sense for users of this service.
This chapter introduces the reader to using third‐party data connectors and explores the fundamentals of dashboards and mobile application design. The resulting example from this chapter is a report that works like an application on mobile phones and is designed for frequent use by busy managers.

Part III: Beyond the Office

The series of chapters explores the possibilities for using Data Studio in areas outside of standard business applications. We look at a wide variety of data sources and data visualizations. This chapter goes beyond the standard uses of Data Studio to see how it can be used by data citizens for their own personal and community interests.

Chapter 8: Getting Personal This is a wide‐ranging chapter that is devoted to creating Data Studio reports and applications for your personal use. The chapter covers self‐generated, curated, and generated sources of personal data and provides examples of using each of them.
Examples in this chapter cover using direct connections as well as third‐party services that can help you access your own data. This chapter details the use of several types of charts and a larger multipage Data Studio application that pulls all the personal sources together.
Chapter 9: Going Public This chapter goes beyond business and personal applications and explores the larger arena that deals with community‐oriented reporting. Although this has largely been the domain of other visualization tools, some large data organizations are providing their own Data Studio connectors to simplify the data connections process.
In this chapter, we explore how to find accessible sources of data. The examples in this chapter use major free data services and corporate sources that offer data with public access. Examples in this chapter also make use of some private data connections and teach you how to use a special Google connector with slow data sources to make your reports more responsive. You'll also find help in this chapter for working with some common data structure issues.

This chapter also explores some of the resources available to the data visualization community and how you can participate so that you can get feedback on your work and grow as a developer. Along with the standard report‐building instruction, you'll find guidance for the design of embedded reports and detailed instructions showing you how to embed your reports in the pages of popular web systems.
Chapter 10: Where Do You Go from Here? This chapter explores some directions you can take after you have mastered the basics. On the communication side, you'll find examples for annotating your reports with contextual information and instructions for your audience. This chapter provides instruction for adding videos to your reports and extending your options through the use of community visualization resources.
On the data side, this chapter covers some of the tools that Google provides for working with large volumes of data and extending your reach through data connector development.

Hardware and Software Requirements

You don't need much to create the examples in this book. To use Data Studio, you have to set up a Google Gmail account if you don't have one already, and you'll need an Internet‐connected computer to work with Data Studio services.

The examples in Chapter 6 use real website data from live Google Search Console accounts. If you do not have access to that service for a real website, you can use the sample search console connectors provided by Google for most of the tasks.

The examples in Chapter 7 connect to live Google My Business accounts. At this time, there are no sample data connections available for these Google services used in that chapter.

Regardless of your ability to directly re‐create the examples, you should still find value in these chapters.

How to Use This Book

If you are just starting off, I recommend that you begin by going in order through the examples in Part I. This will help you understand the fundamentals of the Data Studio tool and how to connect to sources of data.

After completing the first section, new users may want to explore the other chapters as it suits their interests. If you are interested in helping people out with their websites and other Internet properties, you'll want to go right on to Part II and work with Google Analytics and Search Console.

If you are a local business owner, or if you are involved in a local organization, you should pay particular attention to Chapter 7. Understanding and optimizing GMB listings is one of the fastest ways to increase the visibility of a business or organization. Each of these chapters offers more than just instructions for creating reports; each provides practical fundamental advice for using your reports to improve the performance of the organizations with which you are involved.

Suggestions for the More Experienced User

If you come to this book with previous Data Studio experience on the digital marketing side, I invite you to skim through Part I and Part II and go on to explore Part III in more detail. Working with personal and community‐oriented applications will give you greater exposure to possibilities outside of the usual digital marketing reports. My guess is that working in some of these other areas will also spark your creativity when it comes time to get back to work.

If you are seeking career enhancement, going beyond the skills of the data citizen and pursuing growth as a citizen data scientist, focusing on any of the book sections should be helpful to you. However, I suggest that you pay extra attention to Chapter 9 and start participating in online communities in order to share your work and get support and feedback.

Whether you are a beginner or an experienced user, my hope is that you'll use the book as a guide to help you grow your communication and analytics abilities.

How to Contact the Publisher or Author

I appreciate any feedback that you have on this book. Stories of success, often from unexpected places, are one of the greatest rewards for anyone who seeks to help others. I hope you'll contact me if this book helps you and share your achievements, large or small.

You can contact me through the Helpfullee website at https://helpfullee.com/contact. I am also quite active on Twitter, where you can find me @Helpfullee.

If you believe you've found a mistake in this book, please bring it to our attention. At John Wiley & Sons, we understand how important it is to provide our customers with accurate content, but even with our best efforts an error may occur.

To submit any errata, please email our Customer Service Team at wileysupport@wiley.com with the subject line “Possible Book Errata Submission.”

Hands On With Google^® Data Studio

A Data Citizen’s Survival Guide

About the Author

About the Technical Editor

Acknowledgments