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Exploring and Preparing your Data with BigQuery

Approx. 13 hours to complete

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Course Summary

Explore how to prepare data for analysis using Google Cloud Platform's BigQuery. Learn how to create and manage datasets, load data into BigQuery, and write basic and advanced SQL queries.

Key Learning Points

Learn the basics of BigQuery and how to create and manage datasets
Understand how to load data into BigQuery and write basic and advanced SQL queries
Explore best practices for data preparation and analysis in BigQuery

Learning Outcomes

Create and manage datasets in BigQuery
Load data into BigQuery and write basic and advanced SQL queries
Apply best practices for data preparation and analysis in BigQuery

Prerequisites or good to have knowledge before taking this course

Basic knowledge of SQL
Familiarity with cloud computing concepts

Course Difficulty Level

Beginner

Course Format

Online self-paced course
Video lectures and quizzes
Hands-on labs and exercises

Similar Courses

Data Engineering on Google Cloud Platform
Data Analysis with Python
Applied Data Science with Python

Related Education Paths

Notable People in This Field

CEO of Google
Google Senior Vice President

Related Books

Description

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. >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<

Outline

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

Module 1: Introduction to Data on Google Cloud Platform
Highlight Analytics Challenges Faced by Data Analysts
Compare Big Data On-Premise vs on the Cloud
Real-World Use Cases
Navigate Google Cloud Platform Project Basics
Module 1 Quiz

Module 2: Big Data Tools Overview
Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools
Demo: BigQuery Tips and Tricks on Public Datasets
Explore 9 Fundamental Google BigQuery Features
Walkthrough: Data Architecture Diagram
Compare GCP Tools for Analysts, Data Scientists, and Data Engineers
Meet Qwiklabs, your on-demand labs platform
Lab Walkthrough - Exploring Ecommerce Data
Demo: Beyond the BigQuery Web UI
Module 2 Quiz

Module 3: Exploring your Data with SQL
Intro to Google Analytics ecommerce dataset
Compare Common Data Exploration Techniques
Query Basics
Intro to Functions
Demo: Explore Schemas in the BigQuery UI
Filters, Aggregates, and Duplicates
Data Types, Date Functions, and NULLs
Wildcard Filters with LIKE
Lab Walkthrough - Enable Standard SQL
Lab Walkthrough - Query Validator, Aliases, and Commas
Lab Walkthrough - Logical Errors, Group Bys, Wildcard Filters
Lab Walkthrough - Ordering, Calculated fields, Filtering after Aggregating
Lab Walkthrough - Finding top selling products, Filtering NULLs
IRS Public Dataset Overview
Module 3 Quiz

Module 4: Google BigQuery Pricing
Walkthrough of a BigQuery Job
Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs
Demo: Try out the Price Calculator
Reserved Slots
Query Validator, Quotas, and Common Pitfalls
Optimize Queries for Cost
Module 4 Quiz

Module 5: Cleaning and Transforming your Data
Examine the 5 Principles of Dataset Integrity
Characterize Dataset Shape and Skew
Clean and Transform Data using SQL
Clean and Transform Data using a new UI: Introducing Cloud Dataprep
Demo: CloudDataprep on Ecommerce Dataset
Lab Walkthrough - Connecting BigQuery data to Cloud Dataprep
Lab Walkthrough - Exploring Ecommerce Data Fields and Values with a UI
Lab Walkthrough - Building Data Transformation Recipes with a UI
Lab Walkthrough - Running and Scheduling Dataprep Jobs to BigQuery
Components of Data Fusion
Building a Pipeline
Exploring Data using Wrangler
Course Summary
New Lab! Cloud Data Fusion
Module 5 Quiz

Summary of User Reviews

Explore and Prepare Data with BigQuery on Coursera has received positive reviews from users. Many found the course to be informative and well-structured, with a good balance of theory and practical exercises.

Key Aspect Users Liked About This Course

The course material is informative and well-structured.

Pros from User Reviews

The course provides practical exercises that help users apply the concepts they learn.
The instructors are knowledgeable and provide clear explanations.
The course covers a wide range of topics related to BigQuery.
The quizzes and assignments are challenging but not overwhelming.
The course is suitable for both beginners and experienced users.

Cons from User Reviews

Some users found the course to be too basic and not challenging enough.
The course could benefit from more real-world examples.
Some users experienced technical difficulties with the platform.
The course material could be more up-to-date.
The course may not be suitable for users who are not interested in BigQuery specifically.

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