Justin Quizhpi
Business Administration Marketing Student
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Google Data Analytics Professional Certificate
Define and explain key concepts involved in data analytics including data, data analysis, and data ecosystems.
Discuss the role of spreadsheets, query languages, and data visualization tools in data analytics.
Explain how the problem-solving road map applies to typical analysis scenarios.
Demonstrate the use of spreadsheets to complete basic tasks of the data analyst including entering and organizing data.
Explain what factors to consider when making decisions about data collection.
Discuss the difference between biased and unbiased data.
Define different types of data integrity and identify risks to data integrity.
Apply basic SQL functions to clean string variables in a database.
Discuss the importance of organizing your data before analysis by using sorts and filters.
Apply the use of functions and syntax to create SQL queries to combine data from multiple database tables.
Describe the use of data visualizations to talk about data and the results of data analysis.
Explain what data driven stories are including reference to their importance and their attributes.
Describe the R programming language and its programming environment.
Explain the fundamental concepts associated with programming in R including functions, variables, data types, pipes, and vectors.