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

Hands-on exercise – data loading and transformation in BigQuery

To assist with your learning of the concepts in this chapter, we will take you through a hands-on example, including loading data from a local file and preparing some basic transformations on the table data. This hands-on exercise will prepare you for loading your own data in the future and give you experience of doing some basic processing of that data. We will follow a scenario that utilizes a traffic collision dataset. This example and the scenario will build in the future chapters. Follow along by reading the scenario and following it step by step in your Google Cloud console. It may be useful to do a little role-playing here, as follows!

Understanding the scenario

Consider yourself as the Head of Data Analytics for the company described in this scenario. Your company is building a service to reduce users’ cellphone usage while driving. The company’s data team is just beginning to bring in...