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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

Technical requirements

The dataset we use in this exercise is the Historic Vehicle GPS Data: Department of Public Services (2016) dataset. This hands-on example is intended to replicate a real-life scenario based on vehicle location data and a transportation data use case.

You may wish to use your existing Google Cloud project for this exercise or create a new one. If you wish to use a new project, do the following:

  1. Within the Cloud console, click the project selector on the top menu bar to open the project selection dialog box.
  2. From within the project selection window, you can create a new project for this exercise.

Figure 12.1 – The project selection dialog box

To follow along with this chapter you will need to bring the following data source into your BigQuery project. We will review step by step how to load the dataset into BigQuery later in this chapter. For now, you can download each file locally to your computer so it will...

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