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

Saving, sharing, and scheduling queries

BigQuery also provides features for saving, sharing, and scheduling queries, allowing you to collaborate with others, reuse queries for future analysis, and schedule queries to run at a future time. Understanding how to save, share, and schedule queries will help improve your productivity in BigQuery.

To save a query in BigQuery, you first need to write the query in the BigQuery Query Editor. Once you have written the query, you can save it by clicking the Save button. When you save a query, you can choose to save it as a Personal query, Project query, or Public query types. A personal query can only be accessed and edited by you. A project query can be edited by other project users with appropriate permissions. Finally, a public query can be accessed by anyone outside of your project with your query-shared URL.

Sharing queries in BigQuery allows you to collaborate with others and distribute query results. There are a few ways to share...