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Data Exploration and Preparation with BigQuery

Data Exploration and Preparation with BigQuery

By : Mike Kahn
5 (17)
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Data Exploration and Preparation with BigQuery

Data Exploration and Preparation with BigQuery

5 (17)
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)
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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
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Part 4: Hands-On and Conclusion

In the final part of this book, three hands-on exercises and use cases will be presented. These exercises are modeled from common, real-life data analytics challenges and data sources that teams have used to start a data analytics function. The use cases and approaches can be utilized with your own company data. This part is intended to accelerate your ability to gain insights, deliver value, and begin building a strong data analytics practice. Finally, the book will conclude with future directions to explore and be aware of in the rapidly evolving field of data analytics.

This part has the following chapters:

  • Chapter 11, Hands-On Exercise – Analyzing Advertising Data
  • Chapter 12, Hands-On Exercise – Analyzing Transportation Data
  • Chapter 13, Hands-On Exercise – Analyzing Customer Support Data
  • Chapter 14, Summary and Future Directions

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