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Google BigQuery guide for beginners

 

Google BigQuery guide for beginners

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Google BigQuery guide for beginners The best way to get you started with data science in Google BigQuery
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What you'll learn

  • Understand the concept of BigQuery and how does it stand next to other databases such as MySQL or Postgress
  • Import your data to BigQuery and Cloud storage, create your table, export data
  • SQL basics – SELECT, WHERE, ORDER BY, LIKE, JOIN, Date and String functions
  • SQL aggregation functions - SUM, AVG, COUNT, HAVING and GROUP BY
  • BigQuery ML to create your own machine learning model easily with SQL, make a time series prediction
  • Visualise your data in Google Data Studio and make your own dashboard
  • Advanced BigQuery concepts – Partitioning tables, Clustering and Nested Fields
  • Window analytical functions - SUM() OVER (PARTITION BY...)

Requirements

  • Interest in data or cloud technologies
  • No specific technical knowledge needed

Description

I designed this class for people that are starting with Google Cloud Platform and BigQuery. I put 5 years of my knowledge into 3 hours of video content where I try to explain all the important concepts of BigQuery.

We will take it through:

  • Understanding the concept of BigQuery
  • Import your data into BigQuery and Cloud storage
  • SQL basics (WHERE, GROUP BY, JOIN TABLES, CASE WHEN)
  • SQL Date and String functions
  • SQL BigQuery specific features (Nested fields, Partitioned tables, Clustering)
  • SQL window analytical functions
  • BigQuery ML – create easily your machine learning models using SQL
  • Making a time series prediction using BigQuery ML
  • Visualise data in Data Studio
  • Export your data into Jupyter Notebook and Python using Google Collaboratory

This course is not supposed to master your SQL skills. Instead, I will take you through SQL basics and uncover to you the potential of BigQuery. In this class, I will take care that you know what BigQuery is, how you can get in and out your data, what are the most interesting features of BigQuery (BigQuery machine learning, Partitioning, Clustering, Nested fields...) and how you can use the advantage of them.



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