Mckenzieking Designs

I’ve been working through a data analytics project exploring immigration trends to Canada from 1980 to 2013.

What stood out to me was how clearly the data reflects real-world events. For example, there’s a noticeable spike in immigration from Haiti around 2010, which aligns with the earthquake. Seeing that connection visually really brings the data to life.

It’s been a great way to practice not just analyzing data, but actually telling a story with it.

Github file here: https://github.com/DKTODesigns/immigration-trends-data-storytelling

GitHub - DKTODesigns/immigration-trends-data-storytelling: End-to-end analysis of Canada immigration data (1980–2013) using Python. Includes data preprocessing, exploratory analysis, and time-series visualizations with Matplotlib to uncover... End-to-end analysis of Canada immigration data (1980–2013) using Python. Includes data preprocessing, exploratory analysis, and time-series visualizations with Matplotlib to uncover trends and comp...

Added another small project to GitHub as part of my data analytics journey.
This one focuses on Python file handling and data cleanup — separating active and inactive records while preserving structure and formatting.

It’s a simple use case, but a good reminder that a lot of real-world data work starts with cleaning and organizing raw data before any analysis or AI comes into play.

Also validated the solution with a test to ensure data integrity.
Learning a lot through hands-on practice and building as I go.

It’s a simple use case, but a good reminder that a lot of real-world data work starts with cleaning and organizing raw data before any analysis or AI comes into play.

Here’s the project: https://github.com/DKTODesigns/member-data-cleanup

More to come as I continue building.

GitHub - DKTODesigns/member-data-cleanup: Python script for cleaning and organizing membership data by separating active and inactive users. Python script for cleaning and organizing membership data by separating active and inactive users. - DKTODesigns/member-data-cleanup

Starting to share more of what I’m building as I work through my data analytics + AI learning journey.

Just pushed a small project to GitHub, my first time posting code there, so definitely a learning experience on that front as well.

I built a simple text analyzer in Python that:
• cleans and normalizes text
• counts word frequency
• surfaces patterns in unstructured data

It’s a basic example using sample text, but it helped me understand how raw text can be structured and analyzed.

As a product designer, I’ve always worked with qualitative insights. Now I’m exploring how to approach that kind of data more systematically using code.

Here’s the repo:
https://github.com/DKTODesigns/text-analyzer-python

GitHub - DKTODesigns/text-analyzer-python: Simple Python text analyzer for word frequency and preprocessing Simple Python text analyzer for word frequency and preprocessing - DKTODesigns/text-analyzer-python

Excited to share a new milestone — I’ve officially completed my Introduction to Data Analytics certificate on Coursera.

This program focused on the fundamentals of the data analytics process, from understanding different data roles to working with data structures, sources, and visualization techniques. I also strengthened my skills in data cleansing, dashboards, statistical analysis, and big data concepts using tools like Hadoop and Hive.

For my business, this means bringing even more data-informed thinking into the work I do — combining strategy, design, and analytics to help projects move from ideas to measurable outcomes.

Always learning. Always evolving. Thank you to everyone who continues to support the journey.

Completion Certificate for Introduction to Data Analytics This certificate verifies my successful completion of IBM's "Introduction to Data Analytics" on Coursera

🎯 New Milestone in Conversational AI

I’m pleased to share that I’ve completed the Mastering Dialogflow: Build Smart Chatbots using Dialogflow certification through Udemy. That's 2 new certificates on this long Thanksgiving weekend!

This course expanded my practical knowledge of designing intelligent conversational systems — from defining user intents and managing dialogue context to integrating APIs that make chatbots more dynamic and responsive. It reinforced my commitment to creating human-centered, transparent, and accessible AI experiences that can scale across industries like healthcare, fintech, and public service.

Each new certification builds on my goal of blending UX design, accessibility, and conversational AI to shape interactions that feel natural, helpful, and trustworthy.