I choose to complete the Google data analytics professional certificate because

Google stated last year that it will develop a certificate program that would not require a college diploma and could be completed in three to six months. Google even claims that the certificate will be considered equivalent to a four-year college degree. Self-paced, low-cost, and highly valuable are all factors to consider before taking up any course. All of these features are available with Googles professional certificate.

After waiting for the job-guaranteed certificate eagerly, in March 2021, Google launched its Data Analytics Professional Certificate along with other certificate programs that focused on Project Management and User Experience Design. We wont be talking about them here.

Google employees teach the most in-demand skills needed for an entry-level Data Analyst in this course. To complete it, all that is needed is approximately 10 hours of study per week.

By studying for at least 5 hours every day, I was able to earn the Professional Certificate in less than 3 months. Yes, the pandemic freed up a lot of my time. If I hadnt taken so many breaks, Im confident I could have finished it in under two months. Some of my peers were able to get their diplomas in less than a month. Dont believe it? Well, the trick is to be disciplined and dedicated.

About the Data Analytics Professional Certificate

The Professional Certificate is made up of eight courses in total. One of which is a Capstone Project. Each course is arranged into four to five weeks, with graded weekly quizzes and a course quiz at the end. Just before the weekly quizzes, a glossary of the terms acquired over the week is provided to the learners. Lets take a look at what each course enlightens us with and what I loved about them.

Foundations: Data, Data, Everywhere!

This is a foundational course for those who want to learn the fundamentals of data. It provides an overview of the field of data analytics. Teaching how the Professional Certificate is broken down into sections and what we will study in each.

The topics covered in this course are:

• The 5 essential skills of a Data Analyst.
• The 5 key aspects of Analytical Thinking.
• Lifecycle of Data.
• The Steps/Phases of Data Analysis.
• Tools a Data Analyst uses in a Data Ecosystem.
• Lastly, job opportunities and best practices for job search.

Quick heads-up, the professional certificate is divided by the phases of the Data analysis process.

What I liked the most was Data Journal also known as Learning Logs, which encourages the learners to take notes and answer the questions according to their understanding.

Ask Questions to make Data-Driven Decisions

The very first Phase of the Data Analysis process, known as the Ask Phase, is what the course is based on.

This course addressed the following topics:

• Asking effective Questions using SMART Methodology
• Questions to avoid while asking
• Types of Data
• Data presentation tools and their use
• Small Data vs. Big Data
• Brief exposure to Spreadsheets
• Types of Stakeholders and their roles in the project
• How to work with the stakeholders and tips for Communication

My favourite part about this course was how a data analyst should make a Scope of Work for the project they are working on. It helps in keeping track of the workflow of the project. The SOW consists of Deliverables, Milestones, Timeline, and Reports in order for the project to meet its deadlines and goals through excellent planning and coordination by the team members.

Prepare Data for Explorations

Prepare Phase, the second step of the Data Analysis process. Tells how one needs to prepare the data before starting with the Data Analytics project.

It teaches about:

• How data is collected.
• Considerations for Data Collection
• The different Formats of Data
• Data types and how to identify good Data
• Bias and its types
• Aspects of Data Ethics
• Data Privacy and Data Security
• Lastly, some SQL Basics
• Getting started with Linkedin and Kaggle.

The part that excited me the most in this course was its introduction to Kaggle and how one can get started. I had only used Kaggle to check Notebooks and competitions up until now, but this prompted me to sign up.

Process Data from Dirty to Clean

Moving on to the very next step of the Data Analysis process, the Process Phase. This 6-week long course focused more on Data Cleaning processes. Technically its a 5-week course as the 6th week is just a course challenge.

Topics discussed in this course were:

• Statistical measures associated with data integrity including statistical power, hypothesis testing, and margin of error
• Data integrity with reference to types and risks
• Data Cleaning techniques
• Cleaning Data in Spreadsheets and SQL
• Documenting Data Cleaning process
• Elements of a Data Analyst resume

Data Integrity was one fascinating topic in this course. It is the accuracy, completeness, consistency, and trustworthiness of Data throughout its lifecycle. To ensure Data Integrity, Data cleaning comes into the picture.

Analyze Data to Answer Questions

Analysis, is what the course is based on. The process that is used to make sense of the data collected. The Analyze Phase of the Data Analysis process is discussed here.

Topics covered were:

• Data Analysis Basics
• Organizing Data for analyzing
• Sorting Data in Spreadsheet and SQL
• Converting and Formatting Data
• Combining multiple Datasets
• Data aggregation using VLOOKUP and JOINS
• Pivot Tables and Data Validation process.

I enjoyed learning the JOIN clause in SQL as it was one of the things that I always struggled with, and the videos were extremely helpful in making me understand it.

Although this course explains how to analyze data in both SQL and Spreadsheets, it was sometimes confusing to grasp the functions as the videos were mixed up.

Share Data through the Art of Visualization

This course was the most intriguing section of the Professional Certificate. The Share Phase of the Data Analysis process was taught here. It demonstrates how to get started with Tableau, a data visualization tool.

Went through the following topics:

• Communicating Data insights
• Frameworks for organizing Visualizations
• Principles of Design
• Phases of Design Thinking
• Data Storytelling
• The Art and Science of Effective Presentation

I enjoyed every minute of this course because it introduced me to Tableau and provided excellent presentation tips. Another notion that I liked was Data Storytelling, which teaches people how to make their stories more engaging to their audience.

Data Analysis with R Programming

The professional certificates last course teaches how to run codes in Rstudio using the R programming language. It also covers the Act Phase of the Data Analysis Process in the end.

The course covers the following topics:

• Basic programming concepts
• Exploring R packages
• Cleaning Data in R
• Creating Data Visualizations in R
• Developing Documentations and Reports in R

In this course we learned how to clean, process, manipulate, visualize, and document using the R programming language. It was a combination of all the previous courses.

The hands-on activities were the most beneficial, as they allowed me to practice using Rstudio. Although getting started with Rstudio was a little difficult at first, practice made it easier.

Google Data Analytics Capstone: Complete a Case Study

The Final course of the professional certificate, which is a capstone project. It isnt necessary to complete it, however, it is required in order to obtain the Google Data Analytics Professional Certificate.

There are two tracks on the course. The learners must select one of the tracks and apply their knowledge to clean, process, manipulate and analyze the data. Lastly, they had to present their insights and recommend the right steps to take for solving the case study.

Track 1

• Case Study 1: Cyclistic Bike-Share
• Case Study 2: Bellabeat smart devices

Track 2

• Here the learners need to choose their own case study and give valuable insights.

The learners were also instructed on how to build a portfolio and what resources they could use to do so.

My favourite part was the mock interview that was presented at the end of the course. Teaching about the interview process, how the candidates can introduce themselves, solve case studies during the interview and negotiate the contract.

Conclusion

The article has now come to an end. The Google Data Analytics Professional Certificate, in my opinion, is perfect for anyone interested in getting started with data analysis. The coursework is well-presented, and it equips students with the necessary fundamental knowledge of Data Analysis.

Being from a technical background, I found it a little pointless at the start because I was already familiar with SQL and spreadsheets, but as I continued through the course, I learned a variety of new concepts and tools

Once you are done with the course you will get one-year free membership of Courseras BigInterview which assists you in preparing for interviews. Apart from that you can register to Coursera Job Platform and Career Circle.

Upon completion of the certificate, you will have the option to share your information with top U.S. employers that are hiring entry-level professionals, like Cognizant, H&R Block, Hulu, JM Smucker, Infosys, Intel, KForce, MCPc, PNC Bank, RICOH USA, TEKSystems, UPMC, Veterans United Home Loans, Walmart and of course, Google. Currently, access to jobs in the employer consortium is only available to those eligible to work in the U.S., but it is expanding to India, Europe, and other regions soon.

Overall, the course is perfect for any beginner and even intermediate in the field of data. However, one shouldnt entirely depend on it because they believe they know everything about Data.

The aspirants must master the topics in-depth on their own, as learning never stops in the data domain.

Why would I say something like that? Well, the field of Data is large and is rapidly expanding every day, every second. As a result, there will be no end to learning new technologies and concepts.

Hope you find this article useful!

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Keep yourself motivated, work hard, and believe in yourself! Things will eventually fall into place!

Sahar TJ