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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

Joining tables

BigQuery supports a variety of join types that can be used to combine data from two or more tables. The most common join types are inner joins, outer joins, and self joins.

Inner joins

An inner join returns rows that match the JOIN condition from both tables. It only returns the rows where the joining condition is met on both tables. The JOIN condition is a Boolean expression that compares values in the two tables. For example, the following query joins the customers table and the orders table on the customer_id column:

SELECT customer_id, name, order_id, order_date
FROM customers
INNER JOIN orders
ON customers.customer_id = orders.customer_id

This query will return all rows from the customers table that have a matching row in the orders table. Inner joins are useful when you want to focus on the intersection of data between tables.

Outer joins

An outer join returns all rows from the left table, even if there is no matching row in the right table. The...

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