We’re modern-day gold miners. You may already understand the need for a Data Scientist but in this post, I’ll talk through why Data Engineers should be regarded as just as important.
The growth of data experts in the past 5 years has been exponential. More and more companies are realising the importance of data and its ability to enhance all areas of their business, both customer-facing and internally.
In 2020, Data Engineer was listed as the 8th fastest-growing job in LinkedIn’s emerging job report. Another two data roles made the list too: Data Scientist (3rd) and Artificial Intelligence Specialist (1st). This is no coincidence and each of these roles has a deep connection with each other.
You may already understand the need for a Data Scientist but in this post, I’ll talk through why Data Engineers should be regarded as just as important.
A Gartner post in 2019 reported that data is the key driver in company growth yet wasn’t receiving the attention it deserved.
“Data and analytics are the key accelerant of an organization’s digitization and transformation efforts. Yet today, fewer than 50% of documented corporate strategies mention data and analytics as fundamental components for delivering enterprise value.”
I think it’s safe to say that we all understand that companies need to be data-driven yet many are only just brushing the surface. With less than 50% of companies documenting it within their strategies, why are data roles ranking so high on growth lists?
The Gartner post also holds the answer to this question.
Find out here. Although data science job descriptions require a range of various skillsets, there are concrete prerequisites that can help you to become a successful data scientist. Some of those skills include, but are not limited to: communication, statistics, organization, and lastly, programming. Programming can be quite vague, for example, some companies in an interview could ask for a data scientist to code in Python a common pandas’ functions, while other companies can require a complete take on software engineering with classes.
What is the most important thing to do after you got your skills to be a data scientist? It has to be to show off your skills. Otherwise, there is no use of your skills. If you want to get a job or freelance or start a start-up, you have to show off your skills to people effectively.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
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