Exploring and Preparing your Data with BigQuery
Welcome to the Coursera specialization, From Data to Insights with Google Cloud Platform brought to you by the Google Cloud team. I’m Evan Jones (a data enthusiast) and I’m going to be your guide.
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.
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Welcome to From Data to Insights with Google Cloud Platform: Exploring and Preparing your Data
-Learn the courses, content, and technologies that are part of this data analyst specialization
Module 1: Introduction to Data on Google Cloud Platform
-Understand the core principles behind Google Cloud Platform and how to leverage them for big data analysis
Module 2: Big Data Tools Overview
-Learn what are the key big data tools on Google Cloud Platform that you will be using to analyze, prepare, and visualize data
Module 3: Exploring your Data with SQL
-Learn how to query your data with the basics of SQL (Structured Query Language) and practice writing queries in BigQuery
Module 4: Google BigQuery Pricing
-Understand how pricing works in BigQuery and how you can best optimize your queries
Module 5: Cleaning and Transforming your Data
-Understand the importance of creating high quality datasets and learn the tools that will help you transform your data