Google Data Analytics

Foundations: Data, Data, Everywhere

• Define key concepts in data analytics
• Conduct analytical thinking self-assessment
• Discuss the role of spreadsheets, query languages, and data visualization tools

Ask Questions to Make Data-Driven Decisions

• Explain problem-solving road map steps
• Demonstrate the use of spreadsheets for data analysis
• Describe the key ideas associated with structured thinking

Prepare Data for Exploration

• Explain factors to consider in data collection
• Discuss biased and unbiased data
• Describe best practices for organizing data

Process Data from Dirty to Clean

• Define data integrity and its types
• Apply basic SQL functions for data cleaning
• Verify the results of cleaning data

Analyze Data to Answer Questions

• Discuss the importance of data organization
• Apply functions and syntax for data analysis
• Describe the use of functions for basic calculations

Share Data Through the Art of Visualization

• Describe the use of data visualizations
• Identify Tableau as a data visualization tool
• Explain principles and practices associated with effective presentations

Data Analysis with R Programming

• Describe the R programming language and its environment
• Explain fundamental concepts associated with programming in R
• Demonstrate understanding of R Markdown for content emphasis

Google Data Analytics Capstone: Complete a Case Study

• Differentiate between a capstone, case study, and a portfolio
• Identify key features of a completed case study
• Apply data analysis practices to a given set of data