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

Data preparation

In this section, we will perform data preparation to correct column names in our Bitext Customer Support Training dataset. At this time, the Cloud console bq CLI tool and API do not support renaming column names. To do this, we will run the following query to give columns different names in the results, and we will set the query results to override the existing table data.

Type the rename column names query in the BigQuery SQL console – do not run the query yet:

#rename column names
SELECT string_field_0 AS flags, string_field_1 as instruction, string_field_2 as category, string_field_3 as intent, string_field_4 as response
FROM `ch13.bitextcustomersupport`

Before running the query, click More and then Query settings.

Figure 13.7 – Query settings menu in the BigQuery console

Within the Query settings menu, select the following options:

  • Select the destination as Set a destination...