We live in a time when “Data Science” is a ubiquitous conversation topic. As far as we’re concerned, “everyone” encompasses every company, every organization, and essentially every economy on the planet. The swell of interest in data science has carried the technology revolution to unprecedented heights.
There is concern that Data Science will devalue the role of Data Scientists. Others, however, are concerned that it will quickly deflate. On the contrary, many in the know agree that Data Science is here to stay, and for the better, for a very long time.
What’s the current state of data science?
“Uncertainty” of the future is one of the most perplexing things for humans. It would be a miracle if they could find a means to predict the future. To put it simply, Data Science does this.
For this reason, everyone is eager to spend money on “trend analysis,” the practice of predicting the future by analysing the present. Big Data is the foundation of data science; this data can be either static or constantly changing (a voluminous variety of dynamic data that can be structured or unstructured). It provides the information needed by algorithms and models to identify trends and make predictions about the future.
This is where Data Science combines with related disciplines, such as Machine Learning and Artificial Intelligence. The critical reasons for this Data Explosion are the increasing number of IoT and social media-connected gadgets.
As of this year (2018), 7 billion gadgets across the globe were connected to the Internet of things, generating an enormous amount of data. It’s anticipated that this figure will hit 21 billion this year. Data from social media platforms shows that in 2012, 72 hours of video were posted to YouTube per minute. As of the year 2020, the average daily video consumption was 65 years.
In today’s world, data science is employed by every company that wants to expand by better understanding consumer preferences, market trends, and other patterns in their data. Companies are currently undertaking the following, demonstrating the significance of data science:
To stay competitive, many businesses unrelated to data science have set up data science teams staffed with data scientists to perform analytics.
Harmonize the procedures: As a result of this standardization process, sound data science systems can be developed, which in turn allow for the development of more accurate models.
People who can think critically are in high demand for every industry and function. For instance, even in HR positions, employers seek out candidates with experience using analytical tools that allow them to segment data and develop conclusions.
Most service providers have developed their own applications; this includes financial institutions, telecommunications firms, and insurance agencies. This improves digital client interaction and simplifies digital operations by collecting data in a centralized location for use in data modelling. These tendencies illustrate, without a doubt, the modern emphasis on Data Science.
Where Does Data Science Go from Here?
In terms of value, the Data Science platforms market is predicted to reach $178 billion by 2025. As an added bonus, this is only the Data Science platform, which gives Data Scientists access to open-source tools and computational resources. This allows them to keep up with the ever-evolving discipline.
The primary driver of this meteoric rise is the fact that, as data volumes expand, organizations are prepared to expend ever more significant sums of money to process both structured and unstructured data and derive value from it.
As a result, businesses are always on the lookout for more effective means of sifting through their data in order to develop prediction models for things like consumer trends, increases in demand, potential drops in direction, and competitive analysis. This will increase their profits, allow them to expand into other markets, and attract more clients.
Experts believe that Data Scientist positions will change from what they are today, despite widespread concern that they will be lost to automation in the future.
Skills will evolve and not be lost forever. Just compare the work done by computers and computer science engineers 15 years ago to the work they do today.
New advances in technology have necessitated a revaluation of the necessary expertise in the subject. In this way, individuals are becoming increasingly specialized. Data Scientists are likely to face a similar situation in the next 5-10 years.
It’s acceptable to share the view that Data Science is the future; by 2025, a great deal more will have emerged. Every sector benefit from data science; this includes defense, insurance, education, healthcare, shipping, retail, and telecommunications.
Today’s methods of getting things done are vastly different from those of yesteryear. We must change with the times in order to take advantage of the rising global demand in this industry.
There is hope that by 2025, today’s engineers will be able to seize this opportunity.