Go Beyond the Numbers: Translate Data into Insights

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Create compelling data stories by practicing exploratory data analysis and creating effective data visualizations to communicate key insights. Google employees guide you with hands-on activities and real-world examples, helping you build essential data analytics skills for your career. This is the third course in the Google Advanced Data Analytics Certificate, a series designed to prepare you for an advanced data analytics role.

Syllabus

Find and share stories using data

Introduction to Course 2
Course 2 overview
Robb: Obstacles and achievements
Welcome to module 1
Find stories using the six exploratory data analysis practices
Case study: Deloitte
Benj: Data science and storytelling
Practice Quiz: Test your knowledge: Tell stories with data
Combine PACE and EDA practices
Reference guide: The EDA process
PACE with data visualizations
Practice Quiz: Test your knowledge: How PACE informs EDA and data visualizations
Wrap-up
Glossary terms from module 1
Graded Quiz: Module 1 challenge

Explore raw data

Welcome to module 2
Yaser: Understand data to drive value
Where the data comes from
Reference guide: Import datasets with Python
Reference guide: Pandas methods for the discovery of a dataset
EDA using basic data functions with Python
Activity: Explore raw data Part - A
Practice Quiz: Test your knowledge: Discovering is the beginning of an investigation
Discover what is missing from your dataset
Reference guide: Datetime manipulation
Date string manipulations with Python
Practice Quiz: Test your knowledge: Understand data format
Use structuring methods to establish order in your dataset
Reference guide: Pandas tools for structuring a dataset
Explore raw data
EDA structuring with Python
Histograms
Activity: Explore raw data Part - B
Exemplar: Explore raw data
Practice Quiz: Test your knowledge: Create structure from raw data
Wrap-up
Glossary terms from module 2
Graded Quiz: Module 2 challenge

Clean your data

Welcome to module 3
Methods for handling missing data
Data deduplication with Python
Work with missing data in a Python notebook
Remy: A day in the life of a data professional
Activity: Clean your data - Part A
Practice Quiz: Test your knowledge: The challenge of missing or duplicate data
Account for outliers
Protect the people behind the data
Identify and deal with outliers in Python
Reference guide: How to handle outliers
Practice Quiz: Test your knowledge: The ins and outs of data outliers
Sort numbers versus names
Label encoding in Python
Other approaches to data transformation
Reference guide: Data cleaning in Python
Practice Quiz: Test your knowledge: Changing categorical data to numerical data
The value of input validation
Input validation with Python
Activity: Clean your data - Part B
Exemplar: Clean your data
Practice Quiz: Test your knowledge: Input validation
Wrap-up
Glossary terms from module 3
Graded Quiz: Module 3 challenge

Data visualizations and presentations

Welcome to module 4
Tableau Public overview
How to sign on to Tableau Public
The visualization life cycle
Download your datasets and begin presenting with Tableau
Follow-along guide: Work with Tableau, Part 1
Work with Tableau, Part 1
Practice Quiz: Test your knowledge: Present a story
Follow-along guide: Work with Tableau, Part 2
Work with Tableau, Part 2
Drew: Explore the possibilities of data
Practice Quiz: Activity: Design a bar graph that tells a story in Tableau Public
Activity Exemplar: Design a bar graph that tells a story in Tableau Public
Follow-along guide: Craft compelling stories with Tableau
Craft compelling stories with Tableau
The top five data visualization resources
Follow-along guide: Present like a pro with Tableau
Present like a pro with Tableau
Practice Quiz: Activity: Build an interactive dashboard in Tableau Public
Activity Exemplar: Build an interactive dashboard in Tableau Public
Practice Quiz: Test your knowledge: Advanced Tableau
Wrap-up
Glossary terms from module 4
Graded Quiz: Module 4 challenge