Recently, I decided to complete the Google Data Analytics Professional Certificate as a way to refresh my skills since I have over a year without doing anything related to data analysis. The certificate is recommended for anybody interested in data analysis no matter the experience. Some employers would take Google certificates as equivalent to a degree for junior positions.
This certificate has seven courses and a capstone where you would apply everything learned in the previous courses:
Foundations: Data, Data, Everywhere
This course provides an overview of the entire certificate and the tools needed to succeed as a data analyst. It covers the data analysis life cycle and teaches how to think like a data analyst in order to solve problems analytically. If you have experience in data analysis, you can take a test and jump right into the second course.
Ask Questions to Make Data-Driven Decisions
During the second course, you will learn how to deal with stakeholders and ask the right questions so they can successfully make business decisions. Moreover, learn how to share information via reports and dashboards depending on the problems and requirements of the stakeholders. Spreadsheets are also covered here at the basic levels for anyone that is unfamiliar with it.
Prepare Data for Exploration
This course discusses the different sources of data, data types, and avoiding bias in your data and analysis to make accurate and inclusive decisions. Also, it continues working on spreadsheets and an introduction to SQL to make queries within traditional databases.
Process Data from Dirty to Clean
In this course, you will be learning data cleaning and the integrity of the data so all analyses are as accurate as possible. Furthermore, topics like what to do when there is not enough data, tracking the changes made to the data during the cleaning process, and more SQL and spreadsheets tutorials on how to perform data cleaning for the most common use cases.
Analyze Data to Answer Questions
During this course, you will learn how to aggregate and summarize data. Also, data formatting and performing calculations in SQL and spreadsheets. Ordering, filtering, and more advanced tasks like merging data sources and joining multiple tables are covered here as well.
Share Data Through the Art of Visualization
This course covers the fundamentals of data visualization and the presentation of the findings to stakeholders. Tableau will be the main tool learned here for creating dashboards and data presentations. Also, tips on how to organize your presentations and be prepared for answering questions about the data at the end of the presentations.
Data Analysis with R Programming
This is the most technical course of the certificate as it teaches the R programming language. The main IDE for this course is RStudio which is considered the de facto standard for R programming. Here you will perform data analysis in different datasets while creating visualizations and reports to practice your skills.
Google Data Analytics Capstone: Complete a Case Study
More than a capstone project, this course is more about providing suggestions and resources for you to create a capstone project, case study, or portfolio to show to potential employers. Also, it helps you to prepare for interviews and shows some examples of the interview process and salary negotiation skills needed to get the job.
This is a great certificate on all levels. I really like the idea of how much the courses try to emphasize the career of the data analyst and make the students “job ready”. It is not only teaching the fundamental concepts but giving an idea of the career path and getting people with this certificate the tools to ace the job interview.
Nevertheless, the content could be improved. For example, most of the specializations in Coursera have between three to five courses. I believe five courses including the capstone should be more than enough to teach the fundamentals for junior data analysts. Although, eight courses could be a perfect number if more advanced material is included. For example, a necessary tool for Data Analysts is the Data Analysis add-in in Excel to make regression analyses and hypothesis tests. I understand that this is a Google ecosystem-oriented certificate. But, considering that Excel is the standard with many tools, it must be covered as Google Spreadsheets doesn’t have enough features to be a complete alternative.
Some would argue that they would have preferred Python instead of R as the programming language for data analysis. But, I think it is fine using R because this is not a dead programming language. The main complaint about R is that Python is very popular but considering that there are still programmers making a living with Cobol, it is safe to assume that you will be found using R which is also very popular in academic settings.
In brief, I recommend this certificate with my eyes closed to anyone that is changing careers, wants to refresh their skills, or just wants to learn something new. As data is essential in all business decisions today. Nonetheless, I would recommend using the Business Statistics and Analysis Specialization by Rice University as a good companion and feeling the gaps that the Google certificate has in terms of hypothesis testing and regression analysis.