March 13, 2025
I did some research on data analytics consulting and the prospect seems more negative than positive. Anyway, I think some thinking is alright but I wouldn’t want to worry about the competition or the challenges at this point. My goal is to find a niche based on my interests. So, I don’t want the negative vibe to influence me at this point.
To be an entrepreneur, you need some naivety. Going into the beast’s belly on your own, you can never be realistic or logical. I was thinking about the process and what it takes to start this project.
Here is a recipe that I put together based on my observations. It’s a family recipe from my maternal grandfather:
Ingredients:
- 1/2 cup Madness
- 1/2 cup Aspiration and the willingness to give
- 2 tbsp Common sense
- 2 cups Self-trust
- 2 cups Faith
- 1 cup Good luck
- Unlimited gratefulness
Instructions:
- Lock focus on the destination (vision) until all else is a blur.
- Mix all the ingredients.
- Stir clockwise at a steady pace.
- Set a Pomodoro timer and an Excel sheet and then: measure, measure, measure.
- Maintain a steady pace. Collect and celebrate a few success nuggets.
- Add more ingredients if needed or throw away the mixture to start over.
- Repeat the process until one day you start to see the wheels turning in your favor.
Steps to get there:
- Planning and creating a system
- Learning Journey
- Developing a portfolio
- Packaging offerings and services
- Marketing
- Pre-sales steps
- Sales
Planning and creating a system
I set up a Trello board with a list of things that I need to go through for the next couple of months. The columns are my steps in the project as I see it now. I’ll fill the stacks as I move forward.
Power ups and add-ons enabled:
Learning journey
Everything changes in the technology field on weekly basis, new libraries, changing functionalities. So, my approach has been to not learn everything in the beginning. Instead, I learn my way though navigating help files and documentations.
Technology stack to learn or review:
- Data handling and cleaning: Pythons, Pandas, Numpy, SciPy, SQL, Excel, DAX
- Visualization: Seaborn, Matplotlib, PowerBI, Tableau
- Statistics: Basics
My to do list:
Join Kaggle:
https://www.kaggle.com/learn/python
Notes: Kaggle has some fun and interesting introduction on Python courses. They were hands on and short.
Learning Python and libraries: Python’s documentation is the first thing to look at. Different documentations have a different writing structuring and visual format. I read one or more functions all the way to the end to get a sense of how they are organized and where to find things. This helps me to quickly find what I need later.
https://docs.python.org/3/contents.html
W3School
I have an affinity for W3School. Back in the day, I used it to learn JavaScript and CSS. I noticed that they have many more tutorials now. It’s clean, and I like the frame-based navigation and content organization. Here is a link to its python course: https://www.w3schools.com/python/default.asp
Note: This is what I was looking for. Nice and clean and I could try what-if scenarios in its editor. W3School seems to has the right mix of details and big picture ideas. So, I am going to stay here for a little while and explore their content.