The summer before I graduated with my MBA I took CIS 5355: Database Management Systems with Dr. Mayur Mehta, a graduate-level elective course. I was intimidated about taking a graduate elective in data that was outside the purview of the MBA planned curriculum.
Some thoughts before the class:
Sometimes you have to say the bold things out loud.
Looking forward,
TL;DR: This blog will be a professionally personal outlet to track my data visualization and data analysis skill progress in pursuit of a business analyst or data analyst job position.
Some thoughts before the class:
I can't code!
I don’t know how computers work!
And the loudest most unspoken fear, I may fail at this!
Which at its core means, I’m afraid I’m not smart enough to do this!
But I understood and liked the material. I was surprised to find how logical the coding language structure was- I thought of it like technical poetry. I was excited to tackle the assignments and flex my newfound SQL skills. I learned how databases were structured, how to create them from nothing, how to link different forms of data intake, and how to use SQL to draw up information from these organized sets of data.
The most surprising thing of all was that I did really well. For a class I thought I could fail miserably, I actually excelled. This was one of my favorite classes in my MBA program and I only took it because the previously required data class had been phased out and I needed a data-based credit to graduate.
I had a couple surprising regrets after taking this class:
I realized that I love doing work that uses data to drive decision making. I started thinking back to that database management class and again asking myself why couldn’t I pursue a career using these skills? So then I started looking online at SQL and Tableau courses and found a plethora of data analysis certificates and classes aimed at bringing new people into the field. There are hundreds of thousands of data analytics job openings and there will only be more as organizations continue collecting massive amounts of consumer data. There is room for career growth as you gain more skills. The salary is competitive at an entry level and has a tall ceiling to work up through. And there is a lot of opportunity for remote or hybrid work in the field.
I’ve started the Google Data Analytics Certificate through Coursera to refresh and review my R, SQL, and Tableau skills from the MBA, and to get an introduction to Python. Once I finish that course, I plan to continue taking courses to hone data-specific software skills. I also plan to use these developing skills to accomplish goals and improve constituent communication at my current employer. I will use this blog to document different projects and highlight helpful resources I use along the way.
As I write this, I’m asking myself what’s the end goal of all of this- the blog, the classes, the skills? Continued professional growth. Building relevant technical skills. Entering a career field with growth opportunities. Landing an analyst position by the end of 2022.
But I understood and liked the material. I was surprised to find how logical the coding language structure was- I thought of it like technical poetry. I was excited to tackle the assignments and flex my newfound SQL skills. I learned how databases were structured, how to create them from nothing, how to link different forms of data intake, and how to use SQL to draw up information from these organized sets of data.
The most surprising thing of all was that I did really well. For a class I thought I could fail miserably, I actually excelled. This was one of my favorite classes in my MBA program and I only took it because the previously required data class had been phased out and I needed a data-based credit to graduate.
I had a couple surprising regrets after taking this class:
- The class was brutal because it was a full semester class taught in June = two five-hour classes/week. Inevitably, some things were skipped that I wanted to learn. I wish I had taken the class in the regular school year so I could have learned more and spent more time on the materials and with Dr. Mehta.
- I wish I had been introduced to SQL and database management work earlier in the program. I assumed that I missed the opportunity to pursue a career in data because my undergrad was in secondary education, and I was too close to finishing my MBA to alter the concentration. I assumed that without a degree I couldn’t be competitive in a data analytics field so I abandoned the idea.
 |
| [Posing with my parents at Texas State before my MBA graduation, Dec. 2020.] |
After reviewing what I accomplished in the first year of my post-MBA job, my favorite projects used our organizational data to create efficiencies, drive outreach, improve engagement, justify program needs, and more. Though I was involved in a lot of other projects in the organization, these stood out as my favorite.
I realized that I love doing work that uses data to drive decision making. I started thinking back to that database management class and again asking myself why couldn’t I pursue a career using these skills? So then I started looking online at SQL and Tableau courses and found a plethora of data analysis certificates and classes aimed at bringing new people into the field. There are hundreds of thousands of data analytics job openings and there will only be more as organizations continue collecting massive amounts of consumer data. There is room for career growth as you gain more skills. The salary is competitive at an entry level and has a tall ceiling to work up through. And there is a lot of opportunity for remote or hybrid work in the field.
I’ve started the Google Data Analytics Certificate through Coursera to refresh and review my R, SQL, and Tableau skills from the MBA, and to get an introduction to Python. Once I finish that course, I plan to continue taking courses to hone data-specific software skills. I also plan to use these developing skills to accomplish goals and improve constituent communication at my current employer. I will use this blog to document different projects and highlight helpful resources I use along the way.
As I write this, I’m asking myself what’s the end goal of all of this- the blog, the classes, the skills? Continued professional growth. Building relevant technical skills. Entering a career field with growth opportunities. Landing an analyst position by the end of 2022.
Sometimes you have to say the bold things out loud.
Looking forward,
LBG
TL;DR: This blog will be a professionally personal outlet to track my data visualization and data analysis skill progress in pursuit of a business analyst or data analyst job position.