14 Nov 2022
Data Scientist - The Game-Changers In Technology Driven World
Ekeeda Moderator
Works at Ekeeda
In this technologically driven world, data floats around in quintillions across the globe. Obviously, there has to be someone who will monitor and convert this enormous amount of data into valuable insights for business, thereby sparking the need for gen-next tech geeks termed as ‘Data scientists’. Wonder how the term ‘Data Scientists’ came into existence? It was coined in 2008 and there are millions of professionals who work in this in-demand field across businesses and industries. The field is so immense that even data scientists themselves struggle to define the exact role of a data scientist and what he or she has to do in the firm.
Also, we are now entering the new era of the information age, in which data sets are growing at an exponential rate due to new tracking mechanisms like smartphone apps, gadgets, wearables, AI equipment like Echo, Siri, etc. to online shopping and social media. In the coming years, Big data will be massive and more complex, massive and untamed.
Thus, in the short-time data scientists have been around, the definition is bound to change and evolve in the big data world. Earlier, being a data scientist required a bit of math and statistics capabilities. You were a genius for companies and businesses. But, today the role includes a unique combination of skills from data mining to statistician and business analysis. The data scientist job has become a multi-tasking activity. Data scientists are always expected to convert the voluminous data into valuable insights on a massive scale – and give real-time data analysis to stakeholders. They will need to give accurate predictions for businesses and convey the right strategies for the team to take action.
It will involve accurate predictions – predictive analytics and prescriptive analysis along with computations at scale – and this in turn will help the business meet its objectives and better customer acquisition and retention.
To be successful data scientists, you will need to learn a host of new and different data science skills. You will have to be familiar with programming skills like Java, Or Python, concepts like Deep learning, supervised & unsupervised algorithms, model performance metrics, Deep learning techniques, MLOps, stats for ML, and more. You will need to command techniques such as machine learning and data mining as well.
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Data scientists will help you manage & analyze the raw but potential data for businesses and companies. They will even know the business implications, communicate results & understand how data insights could be implied to make informed. It requires considerable programming & computer science skills to become skilled data scientists.
Data Science Is Transforming!
Other than building knowledge and know-how in various disciplines & sub-disciplines, data scientists will also need to learn what’s happening around in industries, especially in their area of expertise. When you examine trends and recognize patterns, it will help determine which tools and technologies are priorities to learn. The key isn’t knowing only one technology or practice. Data scientists need to be equipped with a variety of tools, perspectives & approaches. They should quite efficiently identify methods and models best recommended for the specific case.
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Sources: CFA Society Malaysia
Big data, if harnessed rightly, will open new avenues for businesses and ventures. It plays a key role in companies across every industry and across the globe. Data scientists need to evolve and adapt to the changing business demands and new techniques; if they want to deliver on their promises. The ongoing career track program which is industry-focused will help professionals acquire the necessary skills for their new roles, as these skills become more and more business-centric and activities revolve around them.
So, how do you look as a data scientist? In our opinion, it’s a person who has multiple skills; the game-changer in today's technologically driven world.
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