Data is the new oil. It’s valuable, but if unrefined it cannot be used. It has to be changed into gas, plastic, chemicals, etc. to create a valuable entity that drives profitable activity; so data must be broken down and analyzed for it to have value. — Clive Humby, 2006

One of the most clichéd yet true phrases is that technology changes every day and impacts everything. Artificial intelligence is one of the most prominent disciplines bringing disruptions to every industry around the world. With computing technology being upgraded and improved yearly, artificial intelligence (AI) technology is ushering in a new era of innovation across various industries. From healthcare and wellness to finance and manufacturing, AI-powered solutions are transforming the norm of how businesses operate, offer insights, and make well-informed decisions like never before. However, to be effective on a global scale, AI requires a massive amount of data to learn from and be trained on. Therefore, a robust foundation of data engineering is essential for every successful AI application.