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

BigQuery best practices and cost management

In this section, we will go over general best practices for using BigQuery. We will also touch on cost management and the different approaches to optimizing your spending on BigQuery. By the end of this section, you will have a good understanding of how to efficiently use BigQuery to control costs and optimize storage and queries.

Best practices

There are many best practices for using BigQuery. The following are a few best practices that are foundational for using this service efficiently. Take note and implement these approaches to get the most performance and benefit out of BigQuery:

  • Use the right data type for your data: BigQuery supports many data types, each with its own storage cost. Keep in mind that a large string column takes up more space than an integer column. When designing your table schema, make sure to choose the right data type for your data.
  • Query only the columns you need: Avoid using SELECT * as this...