Google Collection: Exploring and Preparing your Data with BigQuery

About this Course

This first course in this specialization is Exploring and Preparing your Data with BigQuery. Here we will see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud Platform. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Cloud Dataprep to analyze and transform your datasets. This course should take about one week to complete, 5-7 total hours of work. By the end of this course, you’ll be able to query and draw insight from millions of records in our BigQuery public datasets. You’ll learn how to assess the quality of your datasets and develop an automated data cleansing pipeline that will output to BigQuery. Lastly, you’ll get to practice writing and troubleshooting SQL on a real Google Analytics e-commerce dataset to drive marketing insights.

Instructor: Evan Jones 

What You’ll Learn

  • How to query and draw insight from millions of records in Google’s BigQuery public datasets
  • How to assess the quality of your datasets and develop an automated data cleansing pipeline that will output to BigQuery
  • How to write and troubleshoot SQL on a real Google Analytics e-commerce dataset to drive marketing insights

Skills You’ll Gain

  • BigQuery
  • GoogleCloud Platform
  • Cloud Computing
  • SQL

Syllabus 

Welcome to From ​Data ​to ​Insights ​with ​Google ​Cloud Platform: ​Exploring ​and ​Preparing ​your ​Data

Module 1: Introduction ​to ​Data ​on Google ​Cloud ​Platform

Module 2: ​Big ​Data ​Tools ​Overview

Module 3: ​Exploring ​your ​Data ​with SQL

Module 4: ​Google ​BigQuery ​Pricing

Module 5: ​Cleaning ​and ​Transforming your ​Data 

Approximate Completion Time: 10 hours to complete (Suggested: 1 week of study; 5-7 hours per week).  Enroll now for free on Coursera

You might also be interested in:

Google Cloud Platform Big Data and Machine Learning Fundamentals

Business Transformation with Google Cloud

Google Cloud Platform Fundamentals: Core Infrastructure

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