My Tech Adventure: Week #2 Recap
MySQL is the little engine that could. Read Part I here.
I just completed Week #2 of my BrainStation Data Analytics course and I’m learning so much about the field. I now recognize the integrative connection between MS Excel, SQL, and Tableau.
Programming Over the Years
My history with programming languages is quite sporadic. I have a non-STEM background but was fortunate to take a few introductory computer science courses in college, including Python. When I was a student at Startup Institute, I dabbed in JavaScript. I took a on-site SQL 101 course sometime later, but I didn’t retain not one bit of information. And then before BrainStation, I attempted SQL again with Udacity. At least this time around, some of the easier SQL clauses like LEFT JOIN and SELECT stuck with me. A BrainStation alum recommended that I should review SQL before this class because everything was going to go by super fast — and was she right!
If anyone knows me, I love researching topics I’m passionate about very intensely on the Internet. I came across Mosh Hamedani’s YouTube MYSQL Tutorial for Beginners course on the#BlackTechTwitter thread and went through about 1/3 of the course before my SQL class this past weekend. Although, I took Python years ago, some of the fundamentals stayed with me and helped me adjust to SQL. Most, if not all, programming languages operate on the same context, regardless of syntax: Coders are going to need to access libraries or schemas outside the main program to execute certain complex tasks with data. I’m glad that I‘m progressing quicker with SQL because I felt very discouraged with learning new programming languages in the past. The more I absorbed, the more coding errors I encountered. I think I didn’t have the right foundation and temperament at the time to sit down, correct and learn from those errors, and continue refining my skill set. I think at some point, I had given up. But this time, I’m more relaxed and prepared for the uphill battle ahead of me.
So What in the Hell is SQL?
SQL stands for “Structured Query Language” — it’s the primary programming language for query databases. MYSQL is a type of Database Management System (DBMS) software that is built on SQL so that data specialists can store multitudes of their user data. Data is categorized into multiple tables (as shown above) that are linked together through foreign keys. Think of foreign keys as spider silk that connects one spider web to another. The silk will eventually form a centralized network that the spider can use to catch its prey, recuperate, and perform its other “spidey” functions. If data analysts cannot properly extract the necessary information from these tables through these foreign keys, then they’ll have a much harder time transforming that data into the appropriate business insights that their organizations need.
Our financial institutions, the new Mom & Pop shops down the block, or the new unicorn Y-Combinator startup could all benefit from installing relational DBMS software like MYSQL to keep track of their current and potential customers’ online behavior. The major issue is that we are facing a national and global data science talent shortage. When you don’t have these individuals advising key business executives on how they should redefine high-level product requirements for their development and design teams, then organizations’ profitability and productivity potential become limited.
Trust me, when Web 3.0 and the multiverse ecosystems start looking like Tron or Ready Player One in the foreseeable future, companies are going to need all the data experts that they can get. There will be a new treasure trove of untampered, unformatted user data waiting to be explored.
Key Class Highlight
Coding on MYSQL WorkBench has been very kind to me so far. Since I was more prepared, I took the initiative to share my screen on Zoom with my peers to work on our problem set. The best part of the exercise was methodologically analyzing each question. We even caught small syntax errors together, which mitigated my anxiety. We didn’t finish the last question, but we did a great job expanding our SQL knowledge together with the time that we were allocated. Learning a new programming language can best be described by the famous proverb, “Slow and steady wins the race”.
This week, my assigned team and I hope to finalize the dataset and topic that we will be present virtually in the next 2–3 weeks. Our instructors will continue with SQL and then venture out to Tableau — the place where data visualization dreams come true. :)
