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

Exploring data loading techniques

There are various ways to ingest data into BigQuery. Data loading can be broken up into a few approaches: batch, streaming, and scheduled. Data load jobs can be executed via the console, the bq command-line interface, the API, other Google Cloud service integrations, and scheduled jobs. In this section, we will discuss each approach to help you understand the best data loading technique to get started and establish a data loading strategy for one-time or regular ingestion and analysis.

Batch loading data

Batch loading or bounded data is a process of loading data into BigQuery in a single operation. This can be done from a variety of sources, including files located in Google Cloud Storage or Google Drive, and local files. Acceptable file types include CSV, JSON, Apache Avro, ORC, and Apache Parquet formats. Batch loading is typically driven through the console UI, automated via API, or via scheduled jobs.

When loading data from a source, you...