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 approaches

When getting ready to begin data preparation, you benefit most from a systematic approach to handling the complexities and potential challenges associated with raw data. We previously discussed the fundamental foundational steps to get started with data preparation. In this section, we will discuss the different data preparation approaches that can be taken with data preparation tools that we will discuss later in this chapter. These approaches will assist you in selecting a route for transforming and preparing your data for analysis.

There are a number of different approaches to data preparation. The best approach for a particular project will depend on the specific needs of the project. It is important to understand the options available so you can apply an approach that works best for you and your unique needs:

  • Manual data preparation (ad hoc): This involves manually cleaning, transforming, and integrating data. This approach can be time-consuming...