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

Using expressions and aggregations

In BigQuery, expressions and aggregations play a crucial role in performing calculations and summarizing data during querying. They allow you to transform and manipulate data to derive meaningful insights from your datasets. Let’s explore how expressions and aggregations are used in BigQuery.

Expressions

In BigQuery, expressions are used to perform calculations, create derived columns, and apply transformations to table data. You can use various operators, functions, and literals within expressions to manipulate values. Let’s look at some key aspects of using expressions in BigQuery.

BigQuery supports a wide range of operators, including arithmetic operators (+, -, *, /), comparison operators (=, <, >), logical operators (AND, OR, NOT), and string concatenation operators (||). These operators allow you to perform mathematical operations, compare values, and combine conditions.

BigQuery provides an extension library...