As a data professional, be it data scientist, data engineers or machine learning engineers, we are solution providers. We design solutions, based on the nature of the challenge, the business model, the revenue model. ALL PROJECTS ARE UNIQUE. :)
In order to earn our keep and provide the best solution possible, we need to
Be exposed to as many tools as possible
Read up to be updated with the latest available tool.
Attend community meetups as well, because you can learn from the speakers’ experience, know what are the tools being used currently
Understand the Strengths and Weaknesses
Try to understand the strengths and weaknesses of the tools, what circumstance its strengths and weaknesses arise, find projects to apply and experiment with the tool. Check out the documentation, Stackoverflow, and personal blogs to be informed.
There is NO SINGLE BEST TOOL
If there is it will have been mentioned often and used widely. You can then focused on that tool alone. However, even if there is THE BEST tool, who can guarantee that it will be the BEST tool forever or at least throughout your career?
With these steps, hopefully, it can allow you to design, and engineer the best data solution for your project.
I wish you all the best in your data learning journey! :)
Thanks for taking the time to read till here. Please feel free to link up on LinkedIn or Twitter (@PSkoo). Do consider signing up for my newsletter too. I just started my YouTube channel, do consider subscribing to it to give support! Thank you! :)
Consider supporting my work by buying me a "coffee" here. :)