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

Understanding the value of using notebooks

There are many benefits of using notebooks to explore data in BigQuery. Here are the most important:

  • Interactive analysis: Notebooks allow you to interactively analyze data, which means that you can manipulate the results of your queries immediately. This makes it easy to explore different datasets and find patterns that you might not have otherwise seen. The interactivity of notebooks fosters a deeper understanding of the data, as analysts can experiment with different types of queries, visualizations, and transformations with ease. The ability to mix code cells with text explanations and visualizations within a notebook empowers analysts to tell a comprehensive data story, making it easier to work with others and communicate insights to stakeholders.
  • Visualizations: Notebooks make it easy to create visualizations of your data. This can help you understand your data better and communicate your findings to others.
  • Collaboration...