Exploring and Preparing your Data with BigQuery
In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud.
What you'll learn
In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets. This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.
Table of contents
- Data analyst tasks and challenges and Google Cloud data tools 5m
- 9 fundamental BigQuery features 4m
- Walkthrough: Data architecture diagram 3m
- Google Cloud tools for analysts data scientists and data engineers 3m
- Getting Started with GCP and Qwiklabs 4m
- Lab: Exploring an Ecommerce Dataset using SQL in Google BigQuery 0m
- Introduction to the Google Analytics ecommerce dataset 1m
- Common data exploration techniques 4m
- IRS public dataset overview 0m
- Query basics 4m
- Introduction to functions 9m
- Filters, aggregates, and duplicates 13m
- Data types, date functions, and NULLs 7m
- Wildcard filters with LIKE 3m
- Lab: Troubleshooting Common SQL Errors with BigQuery v1.5 0m
- 5 principles of dataset integrity 9m
- Dataset shape and skew 3m
- Clean and transform data using a new UI: Introducing Dataprep 5m
- Clean and transform data using SQL 6m
- Lab: Exploring and Creating an Ecommerce Analytics Pipeline with Cloud Dataprep v1.5 0m
- Components of Data Fusion 2m
- Build a pipeline 6m
- Explore data using wrangler 2m
- Lab: Building Transformations and Preparing Data with Wrangler in Cloud Data Fusion 0m