Data Engineers: Myths vs. Realities

Data Engineers: Myths vs. Realities

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).

data science big data data data analytics myth busters

What is Geek Coin

What is GeekCash, Geek Token

Best Visual Studio Code Themes of 2021

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Data Science vs Big Data: Difference Between Data Science & Big Data

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.

Big Data vs Data Analytics: Difference Between Big Data and Data Analytics

What is Big Data? What is Data Analytics? And What is the difference between Data Analytics and Big Data? Let's explore it with us now.

Silly mistakes that can cost ‘Big’ in Big Data Analytics

‘Data is the new science. Big Data holds the key answers’ - Pat Gelsinger The biggest advantage that the enhancement of modern technology has brought

Big Data Analytics: Unrefined Data to Smarter Business Insights -

For Big Data Analytics, the challenges faced by businesses are unique and so will be the solution required to help access the full potential of Big Data.

Get Started With Big Data Analytics For Your Business

Everything we do generates Data, therefore we are Data Agents. The question is: how we can benefit from this huge amount of data generated every day?. This post Get Started With Big Data Analytics For Your Business