Introduction
Welcome to Analytical Ascent! Today, I want to take you on a journey through my professional path and how it led to my passion for data science and Python. This story sets the stage for an upcoming blog series – “Python Foundations: A Beginner’s Guide,” where I aim to share my knowledge and help others embark on their programming journey.
Early Fascination with Data
My fascination with data began in the early years of my career. I was introduced to inferential statistics through Statistical Process Control (SPC). Predicting future outcomes based on current trends in raw data was revolutionary to me.
This exposure motivated me to pursue further education in mathematics and computer science. I realized that understanding computational methods would enable me to harness data’s full potential.
Discovering Python through a Real-World Challenge
A pivotal moment in my journey happened during a project involving an ERP system transition. Specifically, I needed to check about 76,000 part numbers to see if they existed in the new ERP system. This required pasting a part number onto the end of a URL string and checking the returned string for a True or False result. While the web application setup was rudimentary and could have been improved to allow for searching more part numbers simultaneously, modifying it was not an option.
Determined to find a better solution than manually checking each part number, I turned to Google. I don’t recall the exact words I used in that search, but it was something like “automate navigating to a URL and reading result.” This led me to Python. After writing my first Python script, experiencing poor performance on the first execution, and applying adjustments to improve efficiency, I developed an algorithm. It could loop through each part number and add a True or False value into a new column based on the result read at the URL. Remarkably, the algorithm completed the process in under an hour. This was a huge win considering the time it would take an individual to perform the same action manually.
This experience was eye-opening, especially since most of my colleagues were primarily using Microsoft Excel and had no experience with Python. They were as amazed as I was.
Immersing in Python
Following this success, I immersed myself in Python. I deployed web applications to automate processes and used the language to handle redundant tasks. My solutions ranged from automating pivot tables that employees previously handled manually to automating data calls and email alerts. I even automated entire ETL pipelines. In business, time is money. Automating these tasks led to significant time savings and cost avoidance. Consequently, this was a win-win situation: employees were freed from mundane tasks to engage in more meaningful work, and the organization benefited from cost avoidance. It felt great to feel the appreciation from my co-workers and executive management. We were adding tangible value through simple Python automation solutions.
Lifelong Learning and Sharing Knowledge
Throughout my career, I’ve considered myself a lifelong learner. Working with data has provided incredible opportunities to learn from experts across various fields. These include corporate real estate, finance, engineering, manufacturing, and project management. As a result, these experiences have enriched my understanding and broadened my perspective.
Moreover, I feel a strong responsibility to give back to the community by sharing as much knowledge as I can. My hope is that by doing so, I can help others in their own journeys while continuing to grow through discovering even more perspectives. This ongoing exchange of knowledge and ideas fuels my passion and drives my continuous learning.
The Decision to Share Knowledge
My passion for Python and data science grew alongside this desire to share what I had learned. I saw the impact that knowledge sharing could have, and I wanted to contribute to the community. Consequently, this led to the creation of Analytical Ascent, a platform where I could reach out to others who are just starting their journey or looking to expand their skills.
Looking Ahead: Python Foundations: A Beginner’s Guide
I’m excited to introduce the “Python Foundations: A Beginner’s Guide” series that will be published on Analytical Ascent. It is designed to guide you through the basics of Python programming from the vantage point of a data professional. Whether you’re completely new to coding, looking to brush up on your skills, or seeking a different perspective, this series will provide practical insights and hands-on examples to help you succeed.
Conclusion
The journey into data science and Python has been incredibly rewarding. I’m thrilled to share it with you. Stay tuned for the first post in the new Python Foundations blog series. Let’s climb the peaks of data innovation together. Feel free to subscribe, comment, or share your experiences. Welcome to the community!
Congratulations on launching your blog! It’s great to see how your passion and dedication have brought you to this point. I can’t wait to follow along and learn from your experiences and insights. Keep up the fantastic work!