Selasa, 06 Februari 2024

6 Feb 2024

Google Data Analytics Certificate Roadmap

1. Foundation

What you will learn:

  • Real-life roles and responsibilities of a junior data analyst
  • How businesses transform data into actionable insights
  • Spreadsheet basics
  • Database and query basics
  • Data visualization basics

Skill sets you will build:

  • Using data in everyday life
  • Thinking analytically
  • Applying tools from the data analytics toolkit
  • Showing trends and patterns with data visualizations
  • Ensuring your data analysis is fair

2. Ask

What you will learn:
  • How data analysts solve problems with data
  • The use of analytics for making data-driven decisions
  • Spreadsheet formulas and functions
  • Dashboard basics, including an introduction to Tableau
  • Data reporting basics
Skill sets you will build:
  • Asking SMART and effective questions
  • Structuring how you think
  • Summarizing data
  • Putting things into context
  • Managing team and stakeholder expectations
  • Problem-solving and conflict-resolution

3. Prepare

What you will learn:
  • How data is generated
  • Features of different data types, fields, and values
  • Database structures
  • The function of metadata in data analytics
  • Structured Query Language (SQL) functions
Skill sets you will build:
  • Ensuring ethical data analysis practices
  • Addressing issues of bias and credibility
  • Accessing databases and importing data
  • Writing simple queries
  • Organizing and protecting data
  • Connecting with the data community (optional)

4. Process

What you will learn:
  • Data integrity and the importance of clean data
  • The tools and processes used by data analysts to clean data
  • Data-cleaning verification and reports
  • Statistics, hypothesis testing, and margin of error
  • Resume building and interpretation of job postings (optional)
Skill sets you will build:
  • Connecting business objectives to data analysis
  • Identifying clean and dirty data
  • Cleaning small datasets using spreadsheet tools
  • Cleaning large datasets by writing SQL queries
  • Documenting data-cleaning processes

5. Analyze

What you will learn:
  • Steps data analysts take to organize data
  • How to combine data from multiple sources
  • Spreadsheet calculations and pivot tables
  • SQL calculations
  • Temporary tables
  • Data validation
Skill sets you will build:
  • Sorting data in spreadsheets and by writing SQL queries
  • Filtering data in spreadsheets and by writing SQL queries
  • Converting data
  • Formatting data
  • Substantiating data analysis processes
  • Seeking feedback and support from others during data analysis

6. Share

What you will learn:
  • Design thinking
  • How data analysts use visualizations to communicate about data
  • The benefits of Tableau for presenting data analysis findings
  • Data-driven storytelling
  • Dashboards and dashboard filters
  • Strategies for creating an effective data presentation
Skill sets you will build:
  • Creating visualizations and dashboards in Tableau
  • Addressing accessibility issues when communicating about data
  • Understanding the purpose of different business communication tools
  • Telling a data-driven story
  • Presenting to others about data
  • Answering questions about data

7. Act

What you will learn:
  • Programming languages and environments
  • R packages
  • R functions, variables, data types, pipes, and vectors
  • R data frames
  • Bias and credibility in R
  • R visualization tools
  • R Markdown for documentation, creating structure, and emphasis
Skill sets you will build:
  • Coding in R
  • Writing functions in R
  • Accessing data in R
  • Cleaning data in R
  • Generating data visualizations in R
  • Reporting on data analysis to stakeholders

8. Capstone

What you will learn:
  • How a data analytics portfolio distinguishes you from other candidates
  • Practical, real-world problem-solving
  • Strategies for extracting insights from data
  • Clear presentation of data findings
  • Motivation and ability to take initiative
Skill sets you will build:
  • Building a portfolio
  • Increasing your employability
  • Showcasing your data analytics knowledge, skill, and technical expertise
  • Sharing your work during an interview
  • Communicating your unique value proposition to a potential employer