Google Data Analytics Certification vs IBM Data Analyst- Which is Better?

If you are confused between Google Data Analytics Certification vs IBM Data Analyst Certification, then this comparison will clear your doubts. I hope this comparison will help you to decide which program is better for you.

I have compared both programs on these criteria- Projects, Topics, Content Quality, Rating, and support provided. And at the end of this article, you will get my final recommendation on whether you should go with the Google Data Analyst Certificate or the IBM Data Analyst Certificate.

In Google Data Analytics Certification, there are 8 courses. So let’s see the details of each course.

Course 1- Foundations: Data, Data, Everywhere

In this course, data analysts will introduce to the course and then they will discuss data analytics roles and responsibilities. You will also learn six phases of data analysis. At the end of this course, you will listen to data analysts about their experiences and understand the interview best practices.

Pros of this Course-

• The course is combined with various practice exercises.

• Along with video tutorials, you will get extra reading resources.

• A good course for complete beginners.

Cons of this Course-

• Very basic course.

• At beginning of the course, the instructor doesn’t cover any technical concepts.

Course 2- Ask Questions to Make Data-Driven Decisions

In the second course, you will learn how to solve problems by asking effective and correct questions. Spreadsheet basics are also covered in this course. You will learn Formulas in spreadsheets and how to use a spreadsheet. At the end of this course, you will learn about appropriate communication with stakeholders. The instructor will provide tips for effective communication.

Pros of this Course-

• The course will help you to learn about Spreadsheets and Data Communication.
• Throughout the course, there are various practical exercises.

Cons of this Course-

• This course might be boring for you if you already have some previous experience in data analytics.
• Very basic course.

Course 3- Prepare Data for Exploration

The third course is about Data Exploration. In this course, you will learn everything about data such as what is structured data and unstructured data, how to ensure data integrity, what is bias and unbiased data, etc. The instructor also explains databases and how to import data from spreadsheets and databases.

Pros of this Course-

• This is a good course to revise your SQL concepts and understand data.
• You will work on ungraded projects in this course.

Cons of this Course-

• The course is more theoretical.

Course 4- Process Data from Dirty to Clean

This course will teach about data cleaning. Data Cleaning is an essential step in data analytics and this course will cover data cleaning tools and techniques. You will learn how to clean data using spreadsheets and SQL. The instructor also explains the differences between spreadsheets and SQL.

Pros of this Course-

• There are hands-on practices in this course for data cleaning.
• The instructor explains the topics very well.

Cons of this Course-

• This course should have more hands-on exercises. Because Data Cleaning can’t be taught by theory. It requires practice.

Course 5- Analyze Data to Answer Questions

In this course, you will learn data analysis. But before teaching data analysis, the instructor explains data organization and data formatting. You will learn about the SORT function. After that, you will learn how to perform data calculations and understand common calculation formulas. In this course, the instructor explains how to work on a pivot table. 

Pros of this Course-

• This course is good for understanding how to perform data analysis using SQL and spreadsheets.
• This course focuses on the practical part, which is good.

Cons of this Course-

• Some of the topics are very advanced and some topics are very basic. Which might confuse the students.

Course 6- Share Data Through the Art of Visualization

After analyzing your data, you must know how to graphically represent your data. And this course is all about data visualization. In this course, you will learn all about Tableau and how to use Tableau to create dashboards and dashboard filters. You will also learn how to craft a story with data and how to prepare a presentation to showcase your findings.

Pros of this Course-

• The course covers Tableau for Data Visualization, which is helpful.
• There are some hands-on exercises on Tableau.
• Covers Presentation skills.

Cons of this Course-

• The course doesn’t cover advanced concepts of Tableau.

Course 7- Data Analysis with R Programming

In this course, you will learn R programming, RStudio, and fundamental concepts associated with R such as functions,  variables, and various R packages. Then you will learn data organization and data cleaning using R Programming. At the end of this course, you will learn the basics of data visualization using R and tidyverse. ggplot() is also explained in this course. ggplot() is a data visualization library in R programming.

Pros of this Course-

• This course has more hands-on practice and exercises.
• Good course to learn R basics for beginners.
• The instructor’s explanation is perfect.

Cons of this Course-

• If you already know R Programming, you might feel that exercises are easy.

Course 8- Google Data Analytics Capstone: Complete a Case Study

This is the last course of Google data Analytics Certification. In this course, there is a case study that you have to complete. In this capstone project, you have to use all the concepts learned throughout the course. You can select the dataset of your choice. You will also get interview tips and guidance such as how to discuss your portfolio and highlight specific skills in interview scenarios.

Pros of this Course-

• This Capstone Case Study will help you in your interview.
• You will learn how to build your portfolio.

Cons of this Course-

• If you are stuck in this capstone, you have to figure it out by yourself.

Course 1- Introduction to Data Analytics

The first course provides an introduction to data analytics by using real-world examples. You will understand the responsibilities of a Data Analyst. This course will also cover Data ecosystems and Data Repositories such as RDBMS, NoSQL, etc. Data Wrangling and Data Cleaning are covered in the first course, which is good. The instructor of this course provides a basic introduction to data mining and data visualization too.

Pros of this Course-

• If I compare it to the Google Data Analytics first course, this course is more informative.
• This course covered more technical terms in this first course than Google Data Analytics’ first course.

Cons of this Course-

• The course covers the theoretical part only.

Course 2- Excel Basics for Data Analysis

This course is focused on teaching Excel Basics. You can use Excel for performing Data Analysis tasks. You will learn Spreadsheets basics in this course. After that, you will understand how to perform data wrangling and cleaning using Excel. At the end of this course, you will understand how to use VLOOKUP and HLOOKUP Functions.

Pros of this Course-

• This course has graded and practice quizzes.
• There is one project in this course cleaning and analyzing the data using Excel.

Cons of this Course-

• If you already know Excel, this course might bore you.

Course 3- Data Visualization and Dashboards with Excel and Cognos

This course is short and more focused on hands-on practice. In this course, you will gain a basic understanding of Data Visualization. The instructor covers how to create Treemaps, Scatter Charts, and Histograms. After that, you will learn Cognos Analytics. There is one project in this course where you have to perform data visualization using Excel and Cognos.

Pros of this Course-

• The structure of this course is easy to follow.
• Good course to learn Cognos.

Cons of this Course-

• The course doesn’t cover in-depth concepts. It is a basic introduction-type course.

Course 4- Python for Data Science and AI

This is the same course available in IBM Data Science Professional Certificate. In this course, you will learn Python basics, Data Structure, and the two popular Python libraries Pandas and Numpy. At the end of this course, the instructor explains APIs such as Simple APIs, REST APIs & HTTP Requests, etc.

Pros of this Course-

• Along with video tutorials, there are various reading materials available.

Cons of this Course-

• The final project on IBM Watson is not clear.

Course 5- Python Project for Data Science

There is one project course in between the certificate program. In this project, you have to test your understanding of previously learned Python concepts. This project force you to explore and experiment with your knowledge. This is not an easy project for beginners.

Pros of this Course-

• Help you to understand how to work on real-world problems by yourself.

Cons of this Course-

• Very few details are given by IBM for the project. That’s why you have to figure it out by yourself.

Course 6- Databases and SQL for Data Science with Python

SQL knowledge is essential for data analysts and data scientists. And this course will teach you SQL basics and different types of SQL statements. This course also covers some advanced concepts of SQL such as how to work with multiple tables, Sub-Queries and Nested Selects, etc. After that, the instructor explains how to connect a database using Python. At the end of this course, you will work on the 1-course assignment.

Pros of this Course-

• The quizzes of this course help you to practice more.
• There is a bonus section that covers advanced SQL.

Cons of this Course-

• The course has some technical issues for eg working on IBM Db2 Cloud is time-consuming.

Course 7- Data Analysis with Python

In this course, you will learn Python libraries available for data analysis. You will also learn how to import and export the data using Python. In short, this course will teach you the complete data analysis process starting from data processing to model evaluation using Python. At the end of this course, there is one project, where the dataset will be provided and you have to perform data analysis from scratch.

Pros of this Course-

• You will learn statistical concepts in this course.
• This course has practice and graded quizzes.

Cons of this Course-

• The course material lacks in quality and needs improvement.

Course 8- Data Visualization with Python

Matplotlib is a data visualization library in Python. And in this course, you will learn how to create data visualization using Matplotlib. This course also covers Area Plots, Histograms, Bar Charts, Pie Charts, Box Plots, and Scatter Plots. Some advanced techniques of data visualization are also explained in this course. You will learn about Plotly and Dash.

Pros of this Course-

• The course has one project to test the understanding.
• There are practical exercises and quizzes in this course.

Cons of this Course-

• The course quizzes have errors.

Course 9- IBM Data Analyst Capstone Project

This is the last course of this certification program. This is the Capstone project. In this capstone project, you have to perform all the tasks related to data analysis starting from Data Collection. For data collection, you have to scrape the data using web APIs.

After data collection, you have to perform data wrangling and clean the data. Next, you have to analyze the data. And after analyzing your data, you have to showcase your results by using data visualization skills.

Pros of this Course-

• This Capstone project will help you in your portfolio.
• You can showcase this project at the time of the interview.
• And this project help you to revise all the concepts learned in this program.

Cons of this Course-

• You have to complete this project by yourself. No support will be provided.

I recommend Google Data Analytics Certification.

Why?

Because it has a network established of employers that are already going to accept this certificate in place of a degree equivalent, another reason is that you will learn from data analysts and see what problems they are facing as data analysts daily and get to know about their experiences while learning.

A capstone project is the next reason. Because in Google Data Analytics Certification, you can choose your own dataset to build the capstone project. Along with that, you will also get interview tips and guidance, which is not provided by IBM Data Analyst Certification.

But, it doesn’t mean that IBM data analyst is not good. Especially if you are looking for a course in your native language or you want to learn Data Analytics using Python. But if we compare it with Google Data Analytics Certification, then Google Data Analytics Certification is much better than IBM data analyst.