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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

Using functions

When working with BigQuery, one of the most powerful features is your ability to leverage various functions to manipulate and analyze your data. Functions allow you to perform calculations, transformations, aggregations, and more with your SQL queries. This section explores the different types of functions available and shows how they can be used to enhance your data querying capabilities.

BigQuery supports a variety of functions that can be used to manipulate and analyze data. These functions can be used to perform a variety of tasks:

  • Data transformation functions can be used to transform data from one format into another. For example, you could use a function to convert a CSV file into a JSON file.
  • Machine learning functions can be used to train and deploy machine learning models. For example, you could use a function to train a model to predict customer churn.
  • Functions can be used to perform analytics on large datasets. For example, you could...

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