REVIEWING IBM DATA ANALYTICS CERTIFICATIONS: WHAT YOU NEED TO KNOW

Introduction

IBM is a leading global tech brand with some of the best-in-tech resources across different career niches. This blog post will review two IBM Data Analyst certifications for your career advancement. What are the things you should know about these certifications, are they worth it? Can you start or advance in Data Analysis (or Analytics) with them?

Who is a Data Analyst?

A Data analyst is a professional involved in gathering, cleaning, organizing, modeling, and visualizing data to extract helpful insights that can inform decision-making. A Data Analyst helps “make sense” of data that seems meaningless at first glance.

IBM Data Analyst Certifications

There are two IBM Data Analytics certifications, these are ;

IBM Data Analyst Professional Certificate
IBM Data Analytics with Excel and R Professional Certificate

Data-driven decisions are important to companies, especially in a very competitive environment. Companies will always need Data Analysts to help with their businesses. Do IBM certifications help you gain such skills? Let’s review each certification separately:

IBM Data Analyst Professional Certificate

**Data Analyst Extracts Insights From Raw Data For Decision-Making**

The IBM Data Analytics Certification is a professional certification to equip you with skills to work as a Data Analyst. It is available through the Coursera platform. The certification is designed to be for beginners, requiring no prior knowledge. Some of the skills you will learn include;

Data Analysis
Spreadsheet & Microsoft Excel
Python Programming Language for Data Analytics
IBM Cognos Analytics
SQL
Data Visualization
Pandas, Numpy
Pivot Tables

You will learn to use these skills in hands-on practice in a real-life project. There are about 19 labs and major exercises in the certification.

Who Is It For?

This Certification Course shares lots in common with the IBM Data Science Professional Certification – up to 50 percent of the course content. This certification is suitable for:

Absolute beginners to Data Analytics
People who will later want to transition from a Data Analyst career to Data Science (it covers much of the foundations)
People who want to have a firm grasp of Python for Data Science.

Career Opportunities and Salaries

This certification trains you to become a Data Analyst or similar job titles like

Business Analyst
Operations Analyst
Marketing Analyst
Financial Analyst

The average salary for a Data Analyst in the US is $77k per year and Senior Data Analyst positions at about $120k. This certification also allows you to transition to higher-paying career roles like Data Science, earning a bumped-up salary.

Duration and Cost of the Certification

It will take about 4 months to complete the certification, through a Coursera subscription of $39 per month (depending on your location). That puts the cost of this certification at about $156. (Learn how to reduce or eliminate this cost HOW TO GET FREE COURSES ON COURSERA).

Is this Certification Recognized?

Yes. IBM is one of the big brands when it comes to data-related careers. This certification has a good reputation and recognition from industry experts and hiring managers ( the other major competitors are similar certifications from Google and Microsoft).

Degree Credits

Completing this Professional certification also makes you eligible for degree credits in some universities and Institutions.

The recommendations are from the American Council on Education and specific details are at the discretion of individual institutions. The institutions include:

BSc. Marketing – University of London
BSc. Cybersecurity Technology, BSc. Cybersecurity Management and Policy – University of Maryland Global Campus
Masters in Business Administration, MSc. Data Science – Illinois Institute of Technology
BA. Psychology – University of Massachusetts Global
MBA in Business Analytics – O.P. Jindal Global University (MBA BA)
MSc. Information Technology – International Institute of Information Technology, Hyderabad

Certification Program Outline

This certification program consists of 9 courses taking you from an absolute beginner to becoming a Professional Data Analyst. You can take these courses independently of each other, although it is recommended that beginners take them serially. The component courses and what you will learn are as follows;

Course 1: Introduction to Data Analytics – basic introduction to the concepts of data analysis, the data analyst ecosystem, and the role of a data analyst. It is about 10 hours.
Course 2: Excel Basics for Data Analysis – You learn the basics of Excel and its use in Data Analysis. The course duration is about 11 hours.
Course 3: Data Visualization and Dashboards with Excel and Cognos -Learn Data Visualization skills, telling a story with your data through charts, line graphs, bar graphs, Excel spreadsheets, etc., and consolidating them into a dynamic Dashboard. (14 hours)
Course 4: Python for Data Science, AI & Development – a Python Programming course (24 hours)
Course 5: Python Project for Data Science – Building a Python project through a guided course. (8 hours)
Course 6: Databases and SQL for Data Science with Python – an Introduction to SQL (query language) and How to Access Databases from Jupyter Notebooks using Python and SQL.(20 hours)
Course 7: Data Analysis with Python – Learning to use Python libraries such as Pandas, Numpy, and Scipy for Data Analysis. (15 hours)
Course 8: Data Visualization with Python – Using Data Visualization Libraries like Matplotlib, Seaborn, and Folium. (19 hours)
Course 9: IBM Data Analyst Capstone Project – A real-world simulated role as a Data Analyst to solve a business challenge using a dataset. The Capstone Project is an important component of the Certification because it takes you through all the stages of the Data Analytics lifecycle. It can be incorporated into your personal portfolio. (17 hours)

The Certificate

When you complete all 9 courses for the certification, you will be awarded an IBM Data Analyst Professional Certificate. This certificate is shareable on LinkedIn, Resumes, or other online profiles.

The Pros and Cons of the Certification

The Pros of the Certification are

It is very beginner’s friendly, requiring no prior experience
It chooses Python over R or other Programming languages. Python remains the most demanded Data Analysis language by employers.
It is industry-recognized. IBM is an excellent brand
Its Python course is an extensive, excellent introduction to Data Science/Engineering for those who want to transition to this niche later.
It is fairly priced.
Each subject area has a lab project to give you hands-on practical experience. You can add some of these to your portfolio.

The Cons of the Certification are as follows;

There is little direct support when learning through the Courses platform
The Lab projects for the certification program will require you to set up an IBM account and use the IBM interface.
The presentation style for the Certificate may appear dull to some people. There is less human presence in delivering the lectures.
No Power BI or Tableau for data visualization.

Is It Worth It?

Considering what you can learn from the certification and the reputation of IBM as a leading company in Data technology, it is well worth it to learn Data Analytics with IBM. Regarding cost, Coursera as a platform also makes this certification easily accessible at a reasonable fee, a free trial option, an audit option for some courses, and financial aid. You learn at your own pace.

IBM Data Analytics with Excel and R Professional Certificate

The IBM Data Analytics with Excel and R Professional Certificate shares similarities with the IBM IBM Data Analyst Professional Certificate, the principal difference is that it uses R Programming Language instead of Python. It has a relatively shorter Certification Program(3 months), consisting of 9 courses offered through Coursera.

Certification Program Outline

It shares the first three Courses with the IBM Data Analyst Professional Certification, the only difference is in R instead of Python as the Programming language. The component courses are;

Course 1: Introduction to Data Analytics (10 hours)
Course 2: Excel Basics for Data Analysis (11 hours)
Course 3: Data Visualization and Dashboards with Excel and Cognos (14 hours)
Course 4: Assessment for Data Analysis and Visualization Foundations (1 hour)
Course 5: Introduction to R Programming for Data Science (10 hours)
Course 6: SQL for Data Science with R (27 hours)
Course 7: Data Analysis with R (16 hours)
Course 8: Data Visualization with R (12 hours)
Course 9: Data Science with R – Capstone Project (24 hours)