Data Exploration and Preparation with BigQuery: A practical guide to cleaning, transforming, and analyzing data for business insights - Softcover

Kahn, Mike

Softcover

ISBN 10: 1805125265 ISBN 13: 9781805125266

Publisher: Packt Publishing, 2023

Synopsis

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

1. Introducing BigQuery and Its Components
2. BigQuery Organization and Design
3. Exploring Data in BigQuery
4. Loading and Transforming Data
5. Querying BigQuery Data
6. Exploring Data with Notebooks
7. Further Exploring and Visualizing Data
8. An Overview of Data Preparation Tools
9. Cleansing and Transforming Data
10. Best Practices for Data Preparation, Optimization, and Cost Control
11. Hands-On Exercise – Analyzing Advertising Data
12. Hands-On Exercise Analyzing Transportation Data
13. Hands-On Exercise – Analyzing Customer Support Data
14. Summary and Future Directions

About this title

About the Author

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) and a Master of Science degree in MIS from Florida International University.

From the Inside Flap

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; its a hands-on companion that walks you through properly structuring your tables for 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 data analysis, visualization, and for machine learning
• Explore approaches to visualize data in BigQuery
• Apply acquired knowledge to real-life scenarios and design pattern
• Set up and organize BigQuery resources
• Use SQL and other tools to navigate datasets
• Implement best practices for querying BigQuery datasets
• Gain proficiency in using data preparation tools, techniques, and strategies

What this book covers
Chapter 1, Introducing BigQuery and Its Components, Learn about how BigQuery operatates to use it more effectively. Review an 'under the hood' look of the technologies that deliver BigQuery. Understand data exploration and preparation goals.

Chapter 2, BigQuery Organization and Design, Understand how to build a secure and collaborative BigQuery environment. Gain strong understanding of all services that deliver the BigQuery service beyond the SQL query. Understand design patterns for deploying BigQuery resources.

Chapter 3, Exploring Data in BigQuery, Review various ways to explore data in BigQuery and review the process and steps of data exploration.Learn about the different methods to access data in BigQuery and best practices to get started.

Chapter 4, Loading and Transforming, Explore the techniques and best practices for loading data into BigQuery. Review the tools and methodologies for transforming and processing data with BigQuery. This chapter includes hands-on excercise - data loading and transformation in BigQuery.

Chapter 5, Querying BigQuery Data, This chapter will familarize you with the structure of a query and give you a strong foundation in crafting queries. More complex querying practices will be reviewed as well. This chapter will give you the skills to begin writing queries.

Chapter 6, Exploring Data with Notebooks, Understand the value of using notebooks for data exploration. Better understand the notebook options in Google Cloud. This chapter includes hands-on exercise- analyzing Google Trends data in Workbench.

Chapter 7, Further Exploring and Visualizing Data, Better understand data attributes, discover patterns, and communicate findings effectively. Learn common practices for exploring data and review techniques and tools to analyze and visualize your data. This chapter includes a hands-on excercise creating visualizations with Looker Studio.

Chapter 8, Data Preparation Tools, Explore approaches and tools that can be used with BigQuery for data preparation tasks to improve data quality.

Chapter 9, Cleansing and Transforming Data, Review cleaning and transforming data in greater detail for optimizing table data after loading and initial exploration. Learn the skills to handle situations that you will encounter as you refine query results and reporting accuracy.

Chapter 10, Best Practices for Data Preparation, Optimization and Cost Control, Introduce cost control and optimization features of BigQuery. Learn how to use BigQuery in a cost effective way.

Chapter 11, Hands-On Exercise - Analyzing Advertising Data, This hands-on excercise will present a use case including sales, marketing, and advertising data. Follow along with the exercise to learn how to analyze and prepare advertising data and utilize the steps as a repeatable process with your real data.

Chapter 12, Hands-On Exercise Analyzing Transportation Data, This hands-on exercise will present a use case with vehicle data. Follow along with the exercise to learn how to analyze and prepare transportation data, the steps presented can be replicated with real data.

Chapter 13, Hands-On Exercise Analyzing Customer Support Data, This hands-on exercise will present a use case with customer support data. Two different customer support data sources will be used as well as BigQuery ML sentiment analysis to better understand customer service data.

Chapter 14, Summary of Key Points, Future Directions, Recap the key points discussed throughout the book. Look into the future and learn emerging trends and transformative directions that will shape the landscape of data exploration, preparation and analytics with BigQuery.

Edition details

• Publisher: Packt Publishing
• Publication date: 2023
• Language: English
• ISBN 10: 1805125265
• ISBN 13: 9781805125266
• Binding: Paperback
• Edition number: 1
• Number of pages: 264