I study for the IBM Data Analyst Certificate. Here’s how’s it going
In the beginning of the year, I’ve started learning towards a new professional qualification: Data Analytics. Between the Data Analyst professional certificates from Google and IBM I picked the latter: I wanted more technical knowledge and less “water”.
Certificate structure and my current progress
IBM offers 9 courses under the umbrella of this certification (please excuse the shuffled order; this is how Coursera displays it).
The ones I completed are marked with blue dots. As I’m writing this, I’ve just finished course 3 out of 9: Data Vizualization and Dashboards with Excel and Cognos.
6 more to go!
How much time it took me so far
I’ve started the course in the first days of January 2024. Today is April 6. So, the first three courses took me 3 months to complete.
Is it possible to move faster?
On the one hand, definitely yes. I was quite inconsistent with my learning. Also, I am balancing my studies with a full-time job and creating content for my YouTube channel. This is why each of the courses took me around a month to complete.
On the other hand, research shows that only around 12% of people finish MOOCs (Massive Open Online Courses) like this one. My speculation is, the majority of people (including myself!) goes into them with the mindset along the lines of: oh I don’t believe it will take 6 months, I’ll focus and finish this in a few weeks.
You can be overactive in the first week or two, and then the enthusiasm gradually wears out, and the tasks become more difficult and cannot be clicked through mindlessly. This is where, I believe, the majority of people quit.
Everything depends on how much time you have at hand, your ability to focus, and your ability to keep yourself seated staring at the monitor while your body feels like it wants a stretch, a hug, a tasty meal and to go outside and touch grass.
Also, I think it’s important to note that for me, the learning wasn’t linear: sometimes I studied 5 hours a day and sometimes I wasn’t studying for 5 days in a row. If you have lots of free time at your disposition, you can easily finish the first three courses in a month, for sure.
Why I selected IBM over Google
In the battle between the IBM Data Analyst Professional Certificate and Google Data Analytics Professional Certificate (both offered through Coursera) I selected IBM* for the following reasons:
I want to learn Python
If you want to approach anything technical in the IT field, you will most likely be advised to start with learning Python. It is still ranking as the most popular programming language in 2024. I’m interested in Data Analysis, Data Science and AI Engineering, so Python is definitely my choice here (unlike the R programming language offered by Google).
I’ve tried Google Courses
Some time ago, throwing stuff at the wall to see what sticks, I’ve tried the Google UX Design Professional Certificate. While it featured lots of well-created videos, nice graphics, and well-elaborated texts, it was also filled with tons of beginner-level information that was not suitable for my needs.
From reviews on the Google Data Analytics Certificate I understand that the saturation of information is the same as in their UX Certificate. I love to get to the core of things quickly, this is why I went towards the IBM Certificate.
I wanted to learn Excel specifically
IMB offers Excel, Google offers Google Sheets. While I’ve had some Google Sheets experience at my job, I had none with Excel. This was another straightforward hint to pick the IMB course over Google.
* One considerable benefit of Google’s certificate over IBM’s certificate is learning Tableau. With IBM, you learn it’s proprietary tool called Cognos Analytics. While it didn’t seem bad to me, I haven’t seen it in any of the recently reviewed Data Analyst job postings. While Tableau is in 80% of them.
The good news is, I believe the main principles of data vizualization are more or less similar across softwares. Learning one allows you to learn the second one more easily. So, I decided that I will be supplementing my studies with a dedicated Tableau course after I finish the IBM Certification.
My impressions from the 3 courses I’ve completed so far
Course 1. Introduction to Data Analytics.
The initial course in the series is estimated to take 5 weeks (I’ve finished it in around two.
The course gives a good theoretical overview of what you’re about to get yourself into.
I’ve made it very clear for myself what Data Analysts do — as well as at what part of the process of working with data they are involved.
After that, I dove into lots of new concepts and notions: relational databases, SQL and non-SQL databases, how data is wrangled (transformed from raw to prepared), basic statistics principles and the basics of data vizualization.
Here is what is important:
- you get bombarded with lots of new theoretical information. You learn, for example, about a data lake, but you have no idea how it looks like or what to do with it. At this point, knowing what comes next, I would recommend you to relax. You don’t need to learn all of this by heart. You’re basically having a tour around the DA profession.
- the initial course is, in my experience, the least practical and most boring one. But the following certification courses will not be the same. More and more practical information will be introduced as you progress.
- at this stage, I’ve tried to focus on understanding why the Data Analyst profession is needed, what the process of working with data is, and immerse myself into what my work should look like in the future.
Course 2. Excel basics for Data Analytics.
This second course is also estimated for 5 weeks of learning.
Here, things got more practical. We have 6 hands-on labs in total. To complete a hands-on lab, you typically:
- open an Excel instance (make sure you get yourself Excel for the web)
- download the dataset provided in the lab
- manipulate the dataset reading the instructions step-by-step.
As a result, you learn to perform basic Excel operations.
This course is much more interesting to complete.
A good idea would be to use a monitor, if you have one: this way, you would be able to open the instructions on one screen, and complete the actual Excel work in the second.
What lacks in this course, in my opinion, is a general understanding of the purpose of actions that we are doing. I mean, we learn what individual operations are for (like, why use the Flash Fill or the IF functions), but these actions are not tied to a real-life scenario. You basically learn to do what is stated in the lab, without a high-level understanding of how you will apply this knowledge in the future.
Nevertheless, the course is great to learn the basics of Excel and remember the main operations. I hope that I will be able to make more sense of it in the future:)
Course 3. Data Vizualization and Dashboards in Excel and Cognos
The courses become more and more engaging.
In course 3, we learn how to visualize your data and how to combine your vizualizations into a Dashboard.
Unfortunately, we don’t learn here the tools that are demanded by most employees (like Tableau — I mentioned this in the beginning).
Nevertheless, from what I know watching lots of DA YouTube videos — you should have knowledge how to do the entire DA process using only Excel. Yes, the graphs in Excel may look not as sexy as in other softwares, but the insights we derive from content are the main thing, right?
Also, we get a hands-on 30-day free trial experience with Cognos Analytics, a proprietary IBM data vizualization software. Here, I’ve learned to make basic dashboards. So far, it wasn’t difficult, but maybe a bit tedious.
You also have a choice to learn Google’s Looker Studio, optionally. I skipped this part since I plan to learn Tableau separately, anyway.
In the final assignment, you have to create 5 vizualizations of pivot tables in Excel (pretty easy task considering that you already have the pivot tables prepared for you) and two dashboards in Cognos Analytics.
The instructions in the final assignment are detailed and provide hints, so this part didn’t cause any issues. And I am glad I’ve had hands-on experience with Cognos Analytics, since I believe it will help me to learn other vizualization softwares more easily in the future.
Final Thoughts
So far, I’m enjoying my learning more with every course. I love that the information becomes more and more technical, as well as more and more practical.
I’m very excited to start learning Python in course 4. Let’s see how it goes.
I will be reporting on my further progress soon!
