Let's understand a typical day in the life of Data engineers and debunk some of these myths and misconceptions revolving around their lives and work. Surely you will have a completely different view after reading our article.
From self-driven cars to automatic tagging in images, data science has come a long way. Data scientists and analysts have become an integral part of any organisation because of the value they add. But, in all honesty, a data scientist is only as good as the data they work with. Most of the organisations today have their data stored in a variety of formats and across numerous platforms. Here comes a need for data engineers!
Data engineers are people who make this data workable for the data scientists and analysts. Data engineers are responsible for building pipelines that transform the heaps of data into a format that is usable for data scientists. They mostly work behind the scenes and hence are devoid of all the glamors of a data scientist/analyst – but mind you, they’re equally (if not more) essential to the functioning of any organisation.
If data scientists are race car drivers, data engineers are race car builders. The former gets the excitement of speeding along a track and thrill of winning in front of an applauding crowd. The latter, on the other hand, gets the joy of tuning engines and creating a powerful, robust machine. A race car builder makes the job of the driver a lot easier (or tougher, depending on the quality of the builder).
In the digital era that we live in, data has become the biggest and most valuable asset for most organisations. Data is rapidly transforming the way we live and communicate, and it is by collecting, sorting and studying this data, that organisations across the world are looking for ways to impact their bottom lines. In this post, we'll learn Data Science vs Big Data: Difference Between Data Science & Big Data.
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