Using Python to Drive Insights in BigQuery

Developed with
Calculated Systems

Lab Steps

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Signing In to the Google Cloud Console
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Opening the Lab's Jupyter Notebook in Google Cloud

Ready for the real environment experience?

DifficultyBeginner
Time Limit1h
Students23
Ratings
5/5
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Description

In today’s world, we have to deal with ever-growing datasets. These often require specialized computer solutions to handle the extremely large volume. Google BigQuery makes it easy to query, process, and visualize large datasets. In this lab we will get started with BigQuery to analyze a large public dataset.

Learning Objectives

Upon completion of this lab you will be able to:

  • Utilize BigQuery magic notation to query in Jupyter Notebooks
  • Utilize Python to interact with BigQuery
  • Visualize a BigQuery dataset

Intended Audience

This lab is intended for:

  • Data engineers
  • Anyone interested in gaining insights from BigQuery using Python

Prerequisites

You should possess:

  • A basic understanding of Python
  • A basic understanding of data engineering concepts
About the Author
Students1529
Labs14
Courses7
Learning paths11

Calculated Systems was founded by experts in Hadoop, Google Cloud and AWS. Calculated Systems enables code-free capture, mapping and transformation of data in the cloud based on Apache NiFi, an open source project originally developed within the NSA. Calculated Systems accelerates time to market for new innovations while maintaining data integrity.  With cloud automation tools, deep industry expertise, and experience productionalizing workloads development cycles are cut down to a fraction of their normal time. The ability to quickly develop large scale data ingestion and processing  decreases the risk companies face in long development cycles. Calculated Systems is one of the industry leaders in Big Data transformation and education of these complex technologies.