Introduction to Cloud Data Analytics with Google BigQuery

Learn foundational skills in Google Cloud, Data pipeline, SQL , Data Visualization via DataStudio and Google BigQuery

This course is designed for the students who are at their initial stage or at the beginner level in learning the data warehouse, cloud computing data visualization and Analytics.

What you’ll learn

  • Data Studio for Analytics and Visualization.
  • BigQuery User Interface and Key Features.
  • Introduction to Cloud Computing Basics.
  • Introduction Data Warehousing Basics.
  • Google BigQuery Essentials.
  • Loading Datasets to Google BigQuery.
  • Multiple Data Importing Techniques in Google BigQuery.
  • Google Cloud Storage – Buckets.
  • Exporting BigQuery Data in CSV Formats.
  • Exporting BigQuery Data to Google Account.
  • Data Handling.
  • Data Visualisation.
  • Data set Report Generation and Sharing.

Course Content

  • Introduction to Cloud Computing –> 4 lectures • 27min.
  • Introduction to Data Warehouse –> 5 lectures • 33min.
  • Google BigQuery –> 4 lectures • 19min.
  • ETL Process –> 3 lectures • 13min.
  • Practical Guide to BigQuery –> 13 lectures • 55min.
  • Practical Guide to Google Cloud SDK and BQ CLI Tool –> 5 lectures • 36min.
  • Google Data Studio –> 10 lectures • 40min.
  • Capstone Project –> 1 lecture • 1min.

Introduction to Cloud Data Analytics with Google BigQuery

Requirements

  • Basic or Little Knowledge of SQL.
  • Existing Google Account.
  • Basics of Computer and Internet Usage.

This course is designed for the students who are at their initial stage or at the beginner level in learning the data warehouse, cloud computing data visualization and Analytics.

This course focuses on what cloud computing is followed by some essential concepts of data warehousing. It also has practical hands-on lab exercises which covers a major portion of big data importing and performing some Analytics on the big data.

The ETL tool used is Google BigQuery and analytics is performed using a visual tool known as data studio. The lab portion covers all the essentials of the two platforms starting from importing the datasets, loading it, performing powerful SQL queries and then analyzing the same data using the visual graphical tools available on DataStudio platform.