Book Image

Data Storytelling with Google Looker Studio

By : Sireesha Pulipati
Book Image

Data Storytelling with Google Looker Studio

By: Sireesha Pulipati

Overview of this book

Presenting data visually makes it easier for organizations and individuals to interpret and analyze information. Looker 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 Looker 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 Looker 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 Looker Studio.
Table of Contents (17 chapters)
Free Chapter
1
Part 1 – Data Storytelling Concepts
5
Part 2 – Looker Studio Features and Capabilities
10
Part 3 – Building Data Stories with Looker Studio

Building your first Looker Studio report – creating the data source

As you learn about Looker Studio and explore its various capabilities, you will build a simple report in Looker Studio in an incremental manner. You will do this in this chapter to Chapter 6, Looker Studio Built-in Charts. You will work with the call center dataset of a fictional company that provides meal subscription services to customers in the United States.

The objective of this report is to visualize customer call trends and patterns concerning key factors such as call topics, customer attributes, and so on and also to monitor performance metrics such as Call Abandonment Rate and Average Speed of Answer. The dataset contains 6 months of customer call details from January to June 2022.

As the first step, you must create a reusable data source. The dataset is a CSV file that can be accessed at https://github.com/PacktPublishing/Data-Storytelling-with-Google-Data-Studio/blob/master/Call%20Center%20Data...