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

Introducing BigQuery

BigQuery is a highly scalable distributed cloud data warehouse from Google that is purpose-built for running analytics. It is fully managed by Google and serverless, allowing users to use the service without worrying about setting up and managing infrastructure.

BigQuery is optimized for Online Analytical Processing (OLAP) workloads that perform ad-hoc analysis over large data volumes. This is in contrast to relational databases such as MySQL and PostgreSQL, which are built for Online Transactional Processing (OLTP). OLTP systems are optimized for capturing, storing, and processing transactions in real time.

BigQuery is highly performant and can process terabytes of data in seconds and petabytes of data within a few minutes. This is possible due to the decoupling of the storage and compute in its architecture, which allows BigQuery to scale them independently on demand. BigQuery charges you separately for storage and processing. Storage pricing is based...