Leverage BigQuery to understand and prepare your data to ensure that it's accurate, reliable, and ready for analysis and modeling
Key Features
- Use mock datasets to explore data with the BigQuery web UI, bq CLI, and BigQuery API in the Cloud console
- Master optimization techniques for storage and query performance in BigQuery
- Engage with case studies on data exploration and preparation for advertising, transportation, and customer support data
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description
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.
What you will learn
- Assess the quality of a dataset and learn best practices for data cleansing
- Prepare data for analysis, visualization, and machine learning
- Explore approaches to data visualization in BigQuery
- Apply acquired knowledge to real-life scenarios and design patterns
- Set up and organize BigQuery resources
- Use SQL and other tools to navigate datasets
- Implement best practices to query BigQuery datasets
- Gain proficiency in using data preparation tools, techniques, and strategies
Who this book is for
This book is for data analysts seeking to enhance their data exploration and preparation skills using BigQuery. It guides anyone using BigQuery as a data warehouse to extract business insights from large datasets. A basic understanding of SQL, reporting, data modeling, and transformations will assist with understanding the topics covered in this book.
Table of Contents
- Introducing BigQuery and Its Components
- BigQuery Organization and Design
- Exploring Data in BigQuery
- Loading and Transforming Data
- Querying BigQuery Data
- Exploring Data with Notebooks
- Further Exploring and Visualizing Data
- An Overview of Data Preparation Tools
- Cleansing and Transforming Data
- Best Practices for Data Preparation, Optimization, and Cost Control
- Hands-On Exercise - Analyzing Advertising Data
- Hands-On Exercise Analyzing Transportation Data
- Hands-On Exercise - Analyzing Customer Support Data
- Summary and Future Directions
Mike Kahn is a data and infrastructure enthusiast and currently leads a Customer Engineering team at Google Cloud. Prior to Google, Mike spent five years in solution architecture roles and worked in operations and leadership roles in the data center industry. His over 15 years of experience have given him a deep knowledge of data and infrastructure engineering, operations, strategy, and leadership. Mike holds multiple Google Cloud certifications and is a lifelong learner. He is based in Boca Raton, Florida, in the US and holds a Bachelor of Science degree in Management Information Systems (MIS) from University of Central Florida and a Master of Science degree in MIS from Florida International University.
