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.

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Spis treści

Data Exploration and Preparation with BigQuery. A practical guide to cleaning, transforming, and analyzing data for business insights eBook -- spis treści

• 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