Job opportunities: Data Engineer VS Data Scientist?

AMSTERDAM - Oct. 30, 2018 - PRLog -- Big Data has changed the face of the world!

With 2,3 trillion gigabytes of data created each day, companies have access to valued information on their users, market and much more.
This Data allows companies to constantly improve their product/service.

Companies have understood the issues of investing in Big Data. The soar of Data Engineer and Data Scientist jobs show it to us.

In 2011, Harvard Business Review has even elected Data Scientist the sexiest job of the 21st century!

However, this job field being not being fully mature yet, Data jobs are still subject to misunderstandings. The Data field could appear for many as a blurry technical 'thing' which could potentially implement and have an impact on a business.

This misunderstanding could result in failure in a good use of resources.  Let's get back onto the fundamentals of these professions and decrypt the value of each.

I - What are the differences between a Data Engineer and a Data Scientist?

1- Understand the hierarchy of the Data Process.

Fig.1 - THE DATA SCIENCE HIERARCHY OF NEEDS

When a company makes a product/service, they need valuable information.

This information was difficult to find two decades before. Today, data is the best way to understand the ecosystem where they evolve.

So here is the thing: Data Engineers and Data Scientists are part of a bigger plan. This pyramid illustrates well the process necessary to use Data in a company.

At the base, Software Developers will be working on the collection of all relevant Data for the Data Engineers.
Then, Data Engineers will move and transform this Data into "pipelines" for the Data Scientists.
Finally, Data Scientist will analyze, aggregate and optimize the data for the company.

Read more here: http://www.digitalsource.io/data-engineer-vs-data-scientist