Book Image

Data Exploration and Preparation with BigQuery

By : Mike Kahn
Book Image

Data Exploration and Preparation with BigQuery

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)
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

Loading data from GCS to BigQuery

In the previous chapter, we loaded data into BigQuery from a local file. This time, we will upload our data source into Google Cloud Storage (GCS) and load it into BigQuery from GCS.

Uploading data files to Google Cloud Storage

If you do not already have a Cloud Storage bucket, create one now:

  1. Visit Cloud Storage in the Cloud console: https://console.cloud.google.com/storage/browser.
  2. Click CREATE to create a new bucket.

Figure 12.3 – Create a Cloud Storage bucket

  1. Give the bucket a name and location type, set the storage class and protection tools, and click CREATE.

Note

During this step of creating a storage bucket, you can accept all the defaults. Keep in mind it is best to keep your storage bucket in the same region as your BigQuery dataset.

  1. After your bucket has been created, add the data files by clicking UPLOAD FILES.
  2. Select the dataset CSV file we are using...