Fundamentals of Data Engineering
Years ago, when I initially entered the world of data analytics, I used to think data was clean – clean in terms of readiness and neatly organized. I was so excited to experiment with machine learning models, find unusual patterns in data, and play around with clean data. But after years of experience working with data, I realized that data analytics in big organizations isn’t straightforward.
Most of the effort goes into collecting, cleaning, and transforming the data. If you have had any experience in working with data, I am sure you’ve noticed something similar. But the good news is that we know that all processes can be automated using proper planning, designing, and engineering skills. That was the point where I realized that data engineering would be the most critical role in the future of the data science world.
To develop a successful data ecosystem in any organization, the most crucial part is how they design the...
