Book Image

Data Exploration and Preparation with BigQuery

By : Mike Kahn
Book Image

Data Exploration and Preparation with BigQuery

By: Mike Kahn

Overview of this book

Data professionals encounter a multitude of challenges such as handling large volumes of data, dealing with data silos, and the lack of appropriate tools. Datasets often arrive in different conditions and formats, demanding considerable time from analysts, engineers, and scientists to process and uncover insights. The complexity of the data life cycle often hinders teams and organizations from extracting the desired value from their data assets. Data Exploration and Preparation with BigQuery offers a holistic solution to these challenges. The book begins with the basics of BigQuery while covering the fundamentals of data exploration and preparation. It then progresses to demonstrate how to use BigQuery for these tasks and explores the array of big data tools at your disposal within the Google Cloud ecosystem. The book doesn’t merely offer theoretical insights; it’s a hands-on companion that walks you through properly structuring your tables for query efficiency and ensures adherence to data preparation best practices. You’ll also learn when to use Dataflow, BigQuery, and Dataprep for ETL and ELT workflows. The book will skillfully guide you through various case studies, demonstrating how BigQuery can be used to solve real-world data problems. By the end of this book, you’ll have mastered the use of SQL to explore and prepare datasets in BigQuery, unlocking deeper insights from data.
Table of Contents (21 chapters)
Free Chapter
1
Part 1: Introduction to BigQuery
4
Part 2: Data Exploration with BigQuery
10
Part 3: Data Preparation with BigQuery
14
Part 4: Hands-On and Conclusion

Best practices for optimizing compute

This section covers analysis optimization. Here, you will learn how to plan, adjust, and utilize the greatest amount of cost efficiency in BigQuery. Referred to as compute, analysis, or processing, you have various options and strategies to leverage and consider as you utilize and optimize BigQuery to process your table data.

Analysis cost options

Because of its accessibility and capabilities, BigQuery has been adopted as the primary data platform for users from various data backgrounds and experience levels. Initially, the service was entirely an on-demand pay-as-you-go pricing model. This means you are only billed for what you use and there is a standard service level and features for everyone. Now, in addition to on-demand pricing, with BigQuery Editions, there are options for more demanding and predictable data analytics workloads.

As mentioned previously, query processing costs in BigQuery can be billed in two different ways –...