A Snapshot of My Recent Progress in Data Analytics

This article might be a little dry to read, but I keep it as a personal reference.

Yes, I am still fascinated by data analytics. Five weeks have passed since I last posted on this blog. This post is about steady accumulation rather than breakthroughs.

Below are some updates on my progress in my studies.

Recent Progress

• 2 IBM Data Analyst Professional Certificate courses completed
  • Course 4: Python for Data Science, AI & Development
  • Course 5: Python Project for Data Science
• 2 Google Advanced Data Analytics Professional Certificate courses completed
  • Course 3: Go Beyond the Numbers: Translate Data Insights
  • Course 4: The Power of Statistics
• 70 SQL problems solved (mostly medium, solved independently)
• 6 Python algorithm problems solved (for fun)
• Learned basic Tableau skills and created 7 files on Tableau Public

Habits I’ve Managed to Keep Consistently

• Focus on steady, daily progress rather than one-time intensity.
Some days are less productive, yet I’m learning to stay patient.
• Take notes while taking courses.
I’ve written around 80 pages of Word notes over the five weeks.
• Redo labs as practice to become more comfortable with coding.
• Discuss questions with ChatGPT to dive deeper into the course material.
• Review frequently.

These habits have mattered more than any single “productive” day.

A Small Experiment with Word Clouds

I tried to create a word cloud of all my class notes in Python. However, it returned mostly auxiliary words (such as column, data, print) instead of meaningful theme words (such as Binomial, Poisson, histogram).

This experiment reminded me that frequency does not equal importance. Just like in real data analysis, meaningful signals often require deliberate feature selection rather than raw counts.

Because of this, I decided to manually select the keywords and concepts as a summary of my recent studies. The keywords are summarized manually, and the word clouds are autogenerated. Most of them represent tools I can now actively use, not just terms I’ve seen once.

Key Concepts Learned

SQL

Since many SQL concepts involve long phrases, this section is shown as text rather than a word cloud.

• coalesce
• date_format
• dense_rank
• sum() over (order by …)
• date_sub
• sum(a = 'b')
• avg(a = 'b')
• trim
• cast(… as signed)
• range between 2 preceding and current row
• recursion
• least / greatest
• gaps and islands problems
  • method 1: lag + case when + sum
  • method 2: id - row_number
• lead

Python

Data Analysis

Looking Ahead

I am very much looking forward to Course 6, The Nuts and Bolts of Machine Learning, in the Google Advanced Data Analytics Professional Certificate. I’m only three learning modules away from starting the course, and I will keep going!