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

Loading and Transforming Data

In the previous chapters, we introduced BigQuery and some of its foundational features. We introduced best practices and described the design and organization of resources, enabling you to understand the service. We also began defining different approaches for exploring data in BigQuery and went over the iterative process of exploration as a data analyst. Now that much of the foundational concepts have been covered, in this chapter, we will shift to the concepts and practices around loading and transforming data in BigQuery.

Loading and transforming data are critical steps in the data analysis process. These steps allow organizations to store data efficiently to begin leveraging data for insights and decision-making. In this chapter, we will explore the various techniques and best practices for loading data into BigQuery, including batch loading, streaming data, and data connections from external sources. Additionally, we will delve into the tools and...