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

Technical requirements

To get the most out of this chapter and the book, you will want to set up access to the Google Cloud console (https://console.cloud.google.com/). At the time of writing this publication, there is a free trial that will allow you to explore and build resources. Many services are also eligible for the Free tier (https://cloud.google.com/free), including BigQuery, which includes 1 TB of querying per month and 10 GB of storage each month. All you will need to get started is a Google account (most people know this as their Gmail account). If you wish to use the Cloud console with your work email, you may be prompted to contact your organization administrator.

If you wish to explore BigQuery at no cost to determine whether BigQuery fits your needs, you can also utilize the BigQuery sandbox (https://cloud.google.com/bigquery/docs/sandbox). The sandbox lets you experience BigQuery and the Google Cloud console without enabling billing for your project. To access the...