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 storage

After preparing and setting up your data, a good area to begin optimizing BigQuery usage is at the storage layer. BigQuery storage is relatively low cost, starting at $0.02 per GB per month (comparable to Cloud Storage or Amazon S3 storage costs) with the first 10 GB of storage per month free. When getting started with BigQuery, the first 10 GB of storage at no cost is a great advantage and creates a frictionless entry point for cost-conscious individuals and businesses. As you begin to load more data, you will want to be aware of the best practices for optimizing storage to operate efficiently and cost-effectively. In this section, we will highlight some of the best practices for managing your data storage in BigQuery.

When you create a dataset, you can set the default table expiration (refer to Figure 10.1). This allows you to set the number of days after creation that the table will be automatically deleted. This is useful for temporary data...