Taking Stock:
How did it start?
The year was 2016, and at this point, I had no idea which space in Tech I wanted to get into, so many advancements were coming up, and at that point, I was doing a Certified Mobile Developer Certification, it was not for me š but of course, I saw it through and passed all my exams. Tableau Software happened to be part of this package being offered by iLab Africa. Yes, it fell in my lapā¦ I loved the colors, the storytelling, and the user-friendliness, the rest was what was to come.
What has the journey looked like?
Slowly after the program, I started surfing the internet, just like any other techie would, YouTube became my best friend, and teaching myself got easier by the day. I would slowly practice, and figure it out as I mastered it, so I was self-taught for the most part. I always remembered to seek a lot of help and guidance along the way. Itās not been linear but so fulfilling. These moments in my life assured me that I could do anything I wanted to, especially because my passion came out of it.
As a beginner?
I almost couldnāt see the light at the end of the tunnel, it felt like it was so far, better yet like I would never get there. I canāt emphasize the importance of learning Excel and advancing on the same. I started with Tableau before I realized I needed a lot more groundwork. Self-discipline and motivation are non-negotiables, the field has so much to grasp, and the truth is as anyone advances in any career path, you will always feel like you are being thrown into the deep end but trust me, you WILL swim!
Why did I keep pushing?
At first, it was new and exciting, and still is…but the idea of being able to tell stories with data on such digestible insights was very intriguing. The color, the variation of visualizations, and the drag and drop just allowed for a dynamic learning environment. Every day was a learning day and the communities in some of the applications were so motivating because of the featured work. Being a perfectionist and striving to want to get better was a constant, I have also met such brilliant minds along the way who have imparted their knowledge and skills collaboratively. I have received so much support along the way and returning the favor is my pleasure.
What challenges did I experience?
As mentioned, it was never a straight path, sometimes I would feel like I hadnāt learned anything despite the strides I was making, especially when it came to concepts, for example, dashboard development. You will always see a better one but put effort into yours. Donāt make me reiterate that famous English quoteā¦haha, but really āthe grass is never greener on the other side!ā Ā š or many other things here and there. Python as a language was also something I had to put a lot of effort into. I must admit though, I might have struggled earlier because it was more of a mindset issue. After my undergraduate, if anyone told me I would have to learn a programming language again? No! But weāre here now and Python has helped with building Predictive Models and understanding Predictive Analysis.
My future in Data Science?
In a world where data is steering a lot, I have become very open minded, there are so many current advancements, talk about Artificial Intelligence and Machine Learning, Big data DataOps and MLOps practices, Cloud Computing, Data bricks, the focus on Data Privacy and Governance e.g., GDPR, CCPA. The future of data science and engineering holds exciting prospects driven by advancements in technology, evolving business needs, and emerging trends. AI and machine learning (ML) will continue to play a central role in data science and engineering. Advanced ML algorithms will enable more sophisticated data analysis, pattern recognition, and predictive modeling.
As a Data engineer focus will shift to building scalable infrastructure and pipelines to support the training and deployment of ML models at scale.
With the proliferation of IoT devices, social media, and other sources of real-time data, there will be an increasing demand for processing large volumes of data in real time.
I hope to be able to design edge computing architectures and implement edge analytics solutions to extract actionable insights from data collected at the edge.
This space is characterized by innovation, collaboration, and a relentless pursuit of leveraging data to drive business value and societal impact. As a data professional who stays abreast of emerging technologies and industry trends, I hope you can see my focus, as I better position to thrive in this dynamic landscape.