Google Data Analytics Professional Certificate (part 4)

Ganapathi Kakkirala
3 min readJun 12, 2021
Roadmap to become google certified data analyst.

This is my review article on second course series in Google Data Analytics professional certificate part(4 of 8). I shall walk you through the summary of skills and best practices that you would gain in this course.

Course Name: Process Data from Dirty to Clean

Instructor: Sally, Measurement & Analytics Lead

Course Duration: 25 hours

Skills Covered:

  • 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

What you will learn in this course?

  • 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)

Week 1:

Data integrity is necessary to ensure a successful analysis. In this part of the course, you will explore methods and steps that analysts take to check data for integrity. This includes knowing what to do when you have an insufficient amount of data.

You will also learn about sample size, avoiding sample bias, and using random samples. All of these measures also help to ensure a successful data analysis.

Week 2:

Understanding clean data : Every data analyst wants clean data to work with when performing an analysis. In this part of the course, you will learn the difference between clean and dirty data. You will practice data cleaning techniques in spreadsheets and other tools.

You will explore different formulae, tools and data cleaning tips using spreadsheets.

Week 3:

C​leaning data using SQL: Knowing a variety of ways to clean data can make an analyst’s job much easier. In this part of the course, you will use SQL to clean data from databases. You will explore how SQL queries and functions can be used to clean and transform your data before an analysis.

You will understand the capabilities of SQL and where to use SQL vs Spreadsheets. It has lots of hands-on labs where you will practice the queries in the Big Query on the real dataset. This gives a glimpse of how a data analyst will crunch with their data in daily life.

Week 4:

Verifying and reporting cleaning results: Cleaning data is an important step in the data analysis process. In this part of the course, you will verify that data is clean and report data cleaning results. With verified clean data, you will be ready for the next step in the data analysis process.

The verification includes keeping a record of the changes made to the whole project along the development cycle, you will learn the importance of keeping a detailed changelog or document in this part of the course.

Week 5:

Adding data to your resume. Creating an effective resume will help you in your data analytics career. In this part of the course, you will learn all about the job application process. Your focus will be on building a resume that highlights your strengths and relevant experience.

PS: This is an optional module and I have skipped for now. I shall review it while building portfolio.

Week 6:

This short module contains course challenge based on two real scenarios. It would roughly take 45 mins to complete and again the course challenges are designed such that they reflect the activities that a typical data analyst face during their day to day activities.

All the best!

Thank You.

Read my reviews to previous courses of the program

Part 1: Google Data Analytics Professional Certificate (part 1)

Part 2: Google Data Analytics Professional Certificate (part 2)

Part 3: Google Data Analytics Professional Certificate (part 3)

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Ganapathi Kakkirala

A technology and business enthusiast with a passion to write and share knowledge through blogs.