Data Storytelling with Google Data Studio: A hands-on guide to using Data Studio for building compelling and effective dashboards
- Length: 464 pages
- Edition: 1
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2022-10-27
- ISBN-10: 1800568762
- ISBN-13: 9781800568761
- Sales Rank: #1038387 (See Top 100 Books)
Apply data storytelling concepts and analytical thinking to create dashboards and reports in Google Data Studio to aid data-driven decision making
Key Features
- Gain a solid understanding of data visualization principles and learn to apply them effectively
- Get to grips with the concepts and features of Data Studio to create powerful data stories
- Explore the end-to-end process of building dashboards with the help of practical examples
Book Description
Presenting data visually makes it easier for organizations and individuals to interpret and analyze information. Google Data Studio is an easy-to-use, collaborative tool that enables you to transform your data into engaging visualizations. This allows you to build and share dashboards that help monitor key performance indicators, identify patterns, and generate insights to ultimately drive decisions and actions.
Data Storytelling with Google Data Studio begins by laying out the foundational design principles and guidelines that are essential to creating accurate, effective, and compelling data visualizations. Next, you’ll delve into features and capabilities of Data Studio – from basic to advanced – and explore their application with examples. The subsequent chapters walk you through building dashboards with a structured three-stage process called the 3D approach using real-world examples that’ll help you understand the various design and implementation considerations. This approach involves determining the objectives and needs of the dashboard, designing its key components and layout, and developing each element of the dashboard.
By the end of this book, you will have a solid understanding of the storytelling approach and be able to create data stories of your own using Data Studio.
What you will learn
- Understand what storytelling with data means, and explore its various forms
- Discover the 3D approach to building dashboards – determine, design, and develop
- Test common data visualization pitfalls and learn how to mitigate them
- Get up and running with Data Studio and leverage it to explore and visualize data
- Explore the advanced features of Data Studio with examples
- Become well-versed in the step-by-step process of the 3D approach using practical examples
- Measure and monitor the usage patterns of your Data Studio reports
Who this book is for
If you are a beginner or an aspiring data analyst looking to understand the core concepts of data visualization and want to use Google Data Studio for creating effective dashboards, this book is for you. No specific prior knowledge is needed to understand the concepts present in this book. Experienced data analysts and business intelligence developers will also find this book useful as a detailed guide to using Data Studio as well as a refresher of core dashboarding concepts.
Cover Title Page Copyright and Credits Foreword Contributors Table of Contents Preface Part 1 – Data Storytelling Concepts Chapter 1: Introduction to Data Storytelling Understanding data storytelling Structuring a data story Presenting data stories Data storytelling at work Essential skills for data storytelling Building data stories – an approach Determine Design Develop Walking through an example Summary Chapter 2: Principles of Data Visualization Understanding foundational design principles Simplicity of design Organizing the layout Accuracy of information presented Reviewing Gestalt principles of visual perception Proximity Similarity Continuity Closure Enclosure Connectedness Prägnanz Figure and ground Focal point Using color wisely Use fewer distinct colors Choose an appropriate color palette and scheme Use color consistently across the dashboard Consider inclusive color schemes Summary Further reading Chapter 3: Visualizing Data Effectively Choosing the right visuals Scorecards Pie and donut charts Bar charts Line charts Combo charts Scatterplot Tables Heatmap (matrix) Treemap Geographical maps Others Avoiding common pitfalls Overloading a dashboard Designing a poor or incohesive layout Not emphasizing key information and a message Using color excessively or inappropriately Using dual axes in charts without caution Inappropriate manipulation of axes Using inappropriate or complex chart types Summary Further reading Part 2 – Data Studio Features and Capabilities Chapter 4: Google Data Studio Overview Technical requirements Getting started with Google Data Studio How it works Working with data sources Creating a data source Managing data freshness Controlling data access Editing a data source schema Other common data source operations Working with reports Creating a report Creating a report from a template Publishing a report Sharing a report Other common report operations Working with Explorer Creating an Explorer Exporting from Explorer Using Explorer in an analyst workflow Leveraging Data Studio Gallery Getting help with Data Studio Building your first Data Studio report – creating the data source Summary Chapter 5: Data Studio Report Designer Technical requirements Report Designer overview Adding charts to the canvas Adding additional data sources Adding and managing pages Choosing a report theme and layout Defining Report Settings Working with data for charts Adding dimensions Adding metrics Sorting data in the charts Implementing filters Understanding editor filters Adding an editor filter Interactive filter controls Adding design components Embedding external content Styling report components Background and Border Text styles Common chart style properties Configuring style properties in report themes Building your first Data Studio report – creating a report from the data source Summary Chapter 6: Data Studio Built-In Charts Technical requirements Charts in Data Studio – an overview Configuring tables and pivot tables Table with numbers Table with bars Table with drill down Pivot tables Configuring bar charts Columnar bar chart Horizontal bar chart Clustered bar chart Stacked bar chart Configuring time series, line, and area charts Line chart Time series chart Area chart Configuring scatter charts Configuring pie and donut charts Configuring geographical charts Geo chart Google Maps chart Configuring scorecards Configuring other chart types Treemap Bullet chart Gauge chart Building your first Data Studio report – adding charts Summary Chapter 7: Data Studio Features, Beyond Basics Technical requirements Leveraging calculated fields Organizing dimension values into custom groups Manipulating text with regular expressions Using MAX and MIN across multiple fields or expressions Displaying images and hyperlinks Using parameters Parameters and calculated fields Parameters and connectors Blending data Blending disparate data sources Blending charts Allowing the reaggregation of metrics Adding community visualizations Creating report templates Optimizing reports for performance Optimizing data sources Optimizing reports Underlying dataset performance Summary Part 3 – Building Data Stories with Data Studio Chapter 8: Employee Turnover Analysis Technical requirements Describing the example scenario Building the report – stage 1 – determine Building the report – stage 2 – design Defining the metrics Choosing the visualization types Considering the filters and their interactions Designing the layout Building the report – stage 3 – develop Setting up the data source Creating the report Summary Chapter 9: Mortgage Complaints Analysis Technical requirements Describing the example scenario Introducing BigQuery Getting started with BigQuery Getting data into BigQuery Analyzing data in BigQuery Stage 1 of building the dashboard – Determine Stage 2 of building the dashboard – Design Choosing visualization types Considering filters and interactions Designing the layout Stage 3 of building the dashboard – Develop Setting up the data source Creating a report Summary Chapter 10: Customer Churn Analysis Technical requirements Describing the example scenario Building the dashboard – stage 1 – Determine Building the dashboard – stage 2 – Design Defining the metrics Choosing visualization types and filters Designing the layout Building the dashboard – stage 3 – Develop Setting up the data source Creating a report Summary Chapter 11: Monitoring Report Usage Technical requirements Usage monitoring overview Google Analytics primer Understanding GA reports Monitoring Data Studio report usage with GA4 Setting up GA4 for Data Studio report monitoring Creating a custom report in GA4 Visualizing in Data Studio Exporting GA4 data to BigQuery Summary Index Other Books You May Enjoy
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