You can have data without information, but you cannot have information without Data-Napoleon Bonaparte, French political leader.
Unbolting the power of data is the top priority of modern businesses. The inexplicable tsunami of data that has flooded today’s organizations is a blessing in disguise which enables them to explore the boundless potential in their own businesses that were unknown to them all this while. The solidity of data seems unreal to many but it is definitely not to be underestimated. The events in sci-fi movies that we have all watched while growing up and wished that were true can actually be turned into reality by unlocking our doors to the illimitable world of data science.
Data science is making waves everywhere and the unique quality which makes it a swift pacing field is its similarity to a curious child who is always asking ‘Why’? The essence of data science lies in going deep into facts and pulling out relevant insights. Dissecting data and understanding its whys and hows is the top selling point of this field of knowledge.
Today, organizations are submerged in tons of data which, if utilized in the right manner, can bring unimaginably high volumes of profits. In simpler terms, large sets of data also called ‘Big Data’, highlight the ‘Big picture’ of a business that leads to ‘Big profits.’ We have numbers to prove it. Experts say that the United States have potential to save around $300 billion-$450 billion in healthcare spending using Big Data solutions.
That brings us to the question — What is Data Science?
Data science is a catchall term encircling a wide array of processes and systems that revolve around limitless knowledge that has the strength to change the world. The principal goal is to identify hidden patterns from complex, raw and horrendous data and produce pertinent insights to add value to business and determine the occurrence of a specific episode in the future. As each year passes by, new developments take place and each time, it transforms itself into something better.
In 2017, businesses introduced themselves to the know-how of Data Science along with machine learning while artificial intelligence and deep learning had just begun to take off. The same themes were prevalent in 2018 and new buzzwords like Blockchain, Digital Twins, and Serverless Computing echoed dramatically in the entire Data Science space.
Here are the budding trends that shall bring exciting opportunities in 2019.
1. Integration of Machine Learning and Data Science
2019 will witness the physical and virtual worlds merging together. Businesses all across the globe will go through a changeover mode by adopting state-of-the-art data technologies. They will modify their traditional processes and infuse efficacy into the whole system to attract steeper profits.
However, this also will mean that data scientists will get to face high-degree, perplexing challenges and encompass a plethora of other roles. They will have to reinvent, explore baffling problems and gain prowess in modern technologies.
And, as business analytics will get impacted by data science in not just one but several ways, firms will give even more importance to big data scientists. Though organizations will hop on the path to automation, it will not lead to the extinction of human role. That being the case, employers will continue to acquire dexterous professionals holding big data certifications who are considered to be best-in-class.
Besides, predictive analysis will reach to a whole new level with support from automated machine learning while extended reality and chatbots will revamp the face of service product marketing. AI technologies offer a never-before-seen customized experience to customers, therefore, visualization of traditional solutions, live simulation, and interactive demos will become mainstream.
2. The Drifts in the AI realm
2018 was abuzz with Artificial Intelligence. With a doubt, it was the most-talked-about application of the analytics world. AI is making human conversations a trend of the yesteryear and elevating consumer satisfaction through technology-enabled conversations.
However, technical experts believe that AI is still in infancy phase and providing personal assistants like Alexa and Siri is just a trailer of what it is capable of achieving in the future. Alan Turing, computer pioneer says that real AI has not come into existence as yet and a similar opinion is shared by Gary Marcus, a Neuroscience and psychology professor at NYU who once conveyed that people who think that we are close to AI are under a profound misconception.
On that account, Artificial Intelligence is expected to pick up pace and gain more relevance in 2019. Over and above, the trend of earning AI certifications will speed up since there is an intense need for laborious people to unravel the mysteries of this realm.
3. The Amplification of Data Science jobs
With the swelling of data science deployment rates, the job market seems like a double-edged sword as organization will magnify the utilization of modern technologies and tools which shall perform the jobs of a Data Scientist while, at the same time, it will be worrisome for businesses to comprehend machine-directed solution without any intervention from human experts.
Going by the reports from the United States of Labor Statistics, there will be a 19% hike in the employment rates of Information research and computer scientists which is judged to be way faster as compared to the average for other professions. Close to 5,400 jobs will be produced over the decade.
4. Data Scientist Salaries will shoot up
The soaring demand for data scientists shall lead to a trend of competitive salaries. From entry-level to mid-career to topline scientists get remunerated as per a just pay scale. Payscale reveals that, on average, a data scientist will earn around $91,000 per annum. Amongst them, the top 10% will get $120,000 and the bottom 10% will make approximately $62,000 per annum.
The year of 2019 will be marked by aggressive use of Artificial intelligence in addition to a deep focus on solving security and privacy issues. Interpreting new algorithms to come to certain conclusions will gain prominence. Boot camps and MOOCs will be commonplace for individuals aspiring to learn data science. Skilled analytics professionals will be in high demand. Automation through Data science will continue at a rapid pace, nevertheless, data scientists are still safe, at least until 2030. If there was a best time to become a data scientist, then it is now.
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