Have you wondered why it is used in industries and how these even started? Before you get thinking, there are few case studies you should read for a better understanding.
Data science is used in several industries today. From the manufacturing sector to education and even healthcare. Data science is used to boost their production, gain better insights, make proper business decisions or develop innovative products for the needs of the customer. Moving ahead, we’ll discuss more on the present scenario and how data science future will look like.
Let’s read a case study on data science: predictive modelling for maintaining oil and gas supply
Most of these industries tend to face major challenges and equipment failure which usually happens due to the inefficiency of oil wells. However, with the adoption of better strategic management that helps predictive maintenance, operators in charge of the oil wells can easily be alerted of crucial damages, doing so will give these operators enough time to shut down and can be notified when the well is undergoing maintenance.
As a data scientist, you’re responsible to develop PdM strategy that further help in avoiding hazards and predict machine failures before anything drastic takes place.
Data science is still an arguable topic and it is one of the most complex and challenging careers in the present scenario. But what will be the status of the industry tomorrow?Nonetheless, tech professionals are now drawn toward the data science career.
Where is the data science industry moving today?
Technology has led to different changes across societies, economies and even the workforce. Though data science job roles have reformed a small segment in the current workforce, the demand for data science professionals will grow exponentially.The core idea of digital transformation is to overtake the corporate world – in simple terms, upgrading the system, processes, and building solutions for the modern age. Thanks to cloud computing, mobiles, service-based solutions. Most importantly, synchronizing the data channels across organizations will lead to better development and productivity of revenue and other related tasks.
For instance, you can quote an example of inventory management. Earlier paper-based records were used for tracking but this has now changed. It is digital oriented today. Online retailers can now track their consignment or distributors can track what’s in their storage.
Are we there yet?
How does the future for a data science professional look like?
The need for an expert specialist in extracting data and predicting insightful results will not cease. A professional having a data science career is considered a rarity which organisations have been fighting to get hold.It is predicted that 80% of UK companies would be hiring data science professionals or perhaps seek data science consultancy in 2019. However, in the future, a data scientist with domain knowledge might not necessarily be hired. Domain knowledge is useful and it can be learned as well, but to future proof your data science career it is mandatory for employees to have broader skill sets encompassing data and analytics.
The future data scientists need to be more specialised and equipped with their skills. However, a full-stack data scientist role will always be in demand.
The advancement of technology will give these professionals more capabilities, but this does not mean their roles will become redundant in the foreseeable future. In addition to this, a certified data science professional will always be a priority by industries. Thus, with the latest expertise, data scientists can help business revolutionise in leaps and bounds.
Data science will come to better usability in the coming future. How do you plan to capitalise your skills and ride the growth wave tomorrow?
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