CoffeeStudyTalk

In regards to my Technical Domains, I've had quite a few 'dead-ends' where I chose to quit at some point or am taking quite a bit of time to complete my studies (i.e. stop/start).  This is not a bad thing and demonstrates my ability to know when to 'stop' and change paths accordingly.  Whatever I can glean from my studies is still good, albeit not to the levels and depths of knowledge I would initially desire. At same time, my non-technical domains is quite healthy and reading numerous books over the years to keep my brain fresh and stimulated as purely technical pursuits can get repetitive and boring. My Past Study Patterns (Technical Domains): 2014 T-SQL Pro // Quit MCSA - SQL Server // Stop/Start for years 2016 MCSA - Window Server // Quit MCSA - SQL Server - Success! 2017 MCSA - Web Apps // Quit 2018 MCSE - R // Stop/Start Art of R - Matloff Book // Done! MTA - Python // Stop/Start Python - Lutz // Done! Statistics WMU Book // Do

One of the biggest eye-openers was the realization that 'Data Science' really means 'Statistics' and there is a time honored college major and discipline that focuses on statistics.  In many ways, data science is not new, but rather it appears to be so as it leverages modern computing technology with statistical analysis software like R or SAS. To that end, studying programming languages and writing code is one thing, but to understand why is probably equally important.  I'm spending some time to study statistics textbooks and found some decent, free material online. I've retooled my Study Plan for 2019 accordingly (original 2018 plan was more Language/Platform specific, but weak on Theory/Technique).  My Study Plan // Eventual Skillset: I. Domain: Statistics DW/BI (Data Warehouse / Business Intelligence)  Math II. Tools: SQL Tableau R Python I. Domain A. Statistics: Statistics and Data Analysis (WMU - Statistics 160 Textbook)  //

I adopted a minimalist wardrobe several years ago and went from 175 articles of clothing to under 38 pieces.  I've been fine-tuning that number and have 45 items as of 2018 with a planned increase to 48 items in 2019. My initial approach was to drop the total count and now the fine-tuning process is to identify specific colors and types of clothing to ensure a proper balance across my entire wardrobe ensemble. Core Colors I've settled on three core colors:  Black, Blue and White.  They constitute roughly 70% of my total wardrobe and I'm slowly increasing different color choices in 2019; notably a Red Adidas Track Jacket. Brand Quality I've been experimenting with various types of clothing and color choices and when I'm satisfied with a certain type or color I then seek out the best brand quality that I can reasonably afford.  In general, I spend on better brands for work attire and limit my discretionary budget for casual clothes on mostly fast fashion