Build a Data Pipeline with BigQuery

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prerequisites
basics of Google BiQuery • basics of BigQuery Standard SQL
skills learned
creating tables from CSV and nested JSON data • scheduling your queries and dataset updates • creating materialized views and aggregated activity tables
Mike Shakhomirov
1 week · 8-10 hours per week · INTERMEDIATE
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Look inside
In this liveProject, you’ll create a data pipeline that can enrich source data with currency exchange rates and converted totals. As this pipeline is updated daily, you’ll need to create a scheduled query to enrich your data. You’ll learn to load essential data into BigQuery from both CSVS and JSON, and use it to generate a daily business intelligence report for your colleagues.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Mike Shakhomirov

Mike Shakhomirov is the head of data engineering at The World's Online Festival. He has an MBA as well as a diploma in big data and social analytics from MIT, and he’s a Google Cloud Certified Professional Data Engineer. Passionate, enthusiastic, and digitally focused, he loves the challenges that the diverse gamut of digital marketing can offer. Mike is an official writer for publications including Towards Data Science and The Startup, and he’s the author of more than 50 published articles on topics such as data engineering, machine learning, and AI in digital marketing. You can find him on LinkedIn and Medium.

prerequisites

This liveProject is for complete beginners to data engineering, with a basic understanding of SQL. To begin this liveProject you will need to be familiar with:

TOOLS
  • BigQuery
      • TECHNIQUES
      • BigQuery Standard SQL
        • /ul>

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