With the exponential rise in the amount of user data, there is a growing demand for specialists who have the skill set necessary to manage that vast and varied amount of data. This budding field of engineering is called Data Engineering.
But the main question to most university students is, why should we learn Data Engineering ?
Here are some of the reasons:
1. Relatively simple learning curve – Data Engineering does not require delving into complex mathematics or technical knowledge. It requires an understanding of fundamentals of Hadoop, Hive and Apache Spark at its core, with additional technologies as desired.
2. Similarities with software engineering – The core of Data Engineering is SQL(or rather HQL). Learning SQL as a part of RDBMS is transferable in the day-to-day job of a Data Engineer. Also, CI/CD tools like Jenkins and Deployment platforms are required for both software and data engineering.
3. Sunrise sector – Increasing demand for Data Engineering Professionals due to exponential growth in user data.
4. Learning data engineering requires time and discipline, not too much technical or mathematical knowledge – As per Data Engineering experts and thought leaders, learning Data Engineering would take up 11 to 12 weeks of dedicated learning.
5. Pretty nifty skill set to acquire in college itself – College is a place of acquiring as many skills as possible. Apart from academics and hobbies, learning Data Engineering is a high in demand skill set for top recruiters.
6. Deviate your mind from competitive programming – While learning how to code through competitive programming is an essential skill, doing it full time will get you nowhere. Instead, learning Data Engineering would definitely give you an edge over others and help you start as a Data Engineer or Big Data Developer off the bat.