Data, as we know is the new global currency. It rules the world we live in and has been often referred to as the “oil” of the 21st century. In fact, as Eric Schmidt of Alphabet claims, we are producing and collating more data in 48 hours than we have done since the beginning of the human civilization till 15 years ago. Thanks to the prevalence of social media, smartphones and Internet of Things, it is difficult to even wrap our heads around how much data is at our disposal. If that is the case, how do we make sense of this massive amount of data? And who does it for us?
Data science is the culmination of a few streams of learning: mathematics, programming, statistics, data analysis, and machine learning. A combination of these streams of learnings allow data scientists to extract information and insights from both structured and unstructured datasets. With Big Data and Machine learning making their foray into the technology scene, Data Science today is being used across all industries and their parallels like business, healthcare, finance, and education.
The most pervasive use of Data Science has been in the Recommendation engine. This has crept into every app and every website that we use without us even noticing it. When you see the personalised recommendations on Netflix or Amazon, it is a great example of data science tracking and “understanding” your search and buying patterns and putting together a recommendation list for you.
As data continues to be the ever-present force ruling our lives, quite evidently, jobs in this field are also multiplying and increasing like never before. The top three emerging jobs on LinkedIn for example, are Big Data Engineers, Machine Learning Engineers, and Data Scientists. Since 2012 the increase in position for data scientists has been 650% creating on of the most sought-after professional fields at present. Thus, it isn’t surprising that professionals from various related fields are upskilling and cross – skilling themselves to move into the field of Data Science.
Before the advent of the digital revolution, the data at our disposal was relatively small in size and well structured. Subsequently, traditional business intelligence tools were quite sufficient and capable of analysing these data sets that were small and structured. However, the recent years have seen an uphauling of that entire equation. This was a result of a result of the generation of a massive amount of unstructured data from sources as diverse as social media and financial transactions and logs and online shopping portals. It is estimated that currently, more than 80% of the world’s data is unstructured.
As years pass and data accumulates and increases exponentially, it will be impossible for traditional business intelligence software to analyse these vast amounts of unstructured datasets. It will become imperative, if it has not already become so, to have more intelligent and advance tools for storing, processing, and analysing data. This is where Data Science will play the pivotal role.
The demand for Big Data, AI, and ML in more and more organisations is leading to a higher demand for Data Science professionals. Quite recently, the job of a Data Scientist was hailed as the Sexiest Job of the 21st century by none other than the Harvard Business Review.
Data science is not only opening up new and exciting possibilities every day, but it is also contributing to changing human lives for the better every day by influencing how we see the world around us.
Currently we don’t even think about the suggestions that advanced algorithms offer us when we shop online by understanding our tastes and preferences. Recommendation lists are created based on individual tastes changing the way we shop and even “impulse” buy. Financial transactions have become so secure that we actually prefer them over physical transaction so that there is a proof of payment. This has been largely possible due to the Fraud and Risk Detection algorithms of Data Science. We expect to be able to monitor and manage our house and what is happening around it even in our absence by simply connecting our smartphones to the IoT hub.
Data science is going on to become an inseparable part of the healthcare sector too. Genomics, Drug Development, Medical Image Analysis, Remote Monitoring are all using Data Science algorithms and applications.
Let us take a look at some of the evolving trends of Data Science that promise to change how the future looks.
- The future of IoT might, in all probability be an Intelligent Digital Mesh of all devices, just like the internet connects the world. Imagine a hub of all apps, devices and people working together.
- Chatbots, virtual reality and augmented reality will take over all the areas of customer service and sales wherever they can fit and you can expect to encounter humans less and less in these jobs. Live demos and simulations will probably be the order of the day rather than aberrations.
- Blockchain might take over other sectors like healthcare, banking and insurance rather than just being limited to currency.
- Predictive analytics might take leap of technology with the help of Automated ML systems and Augmented Analytics and change the face of healthcare and other industries that depend on prediction of human behviour.
- The understanding of the job role of a Data Scientist will be overhauled and it will come to include diverse roles and responsibilities. Data Scientists will have to evolve to keep pace with the dynamic learning of the field as technology, Data Science, and AI continue to advance.
These are only a few obvious changes that Data Science will bring into our world in the next few years. There would be countless things to come as with any major change in technology that is impossible to predict sitting at this juncture.
Why then should you not learn Data Science? In case you need more reasons still, here are a few:
Data is the fuel of the 21st century
Simon Quinton said, “If Analytics is the Engine, then Data is the Fuel of the 21st century.”
Businesses today run on data. Without data it is not possible to have insights to streamline businesses in the global scenario of the 21st century. It is imperative to analyse customer data to not only stay ahead of the game and one’s competition but also to provide continuously improving customer satisfaction in an increasingly competitive world.
While the demand for skilled Data Science professionals, including Data Scientists, ML and AI Engineers, is on the rise, the supply of skilled professionals is not. IBM states that by 2020, Data Science will take up 28% share of all digital jobs, however, job vacancies in this field remain vacant for as high as 45 days due to the lack of talented applicants.
“Machine learning, big data, and data science skills are the most challenging to recruit for, and can potentially create the greatest disruption if not filled.”
This is the time to upskill yourself and fit in to the vacancies being created every day!
A lucrative and high-paying career
Data Scientists are very much in demand and since it is an advanced and exclusive field it is without a doubt that data scientists make more than a decent amount of money. The best part though, is that all the job roles in Data Science have similar pay scales and you will never have the fear of stagnation as it is still an evolving field. There will always be plenty of opportunities to learn, upskill and increase your income.
Highly flexible with an abundance of positions
Data Science is a very flexible field that is still finding its applications in every industry like healthcare, banking, e-commerce, business, and consultancy services. However, only a few individuals actually possess the skills to make it big in this field. Additionally, Data Science roles have a certain amount of overlap required in terms of skills that make it easier for Data Scientists to shift roles to those positions that are still not getting filled due to a lack of the right candidate.
Data Science is helping businesses to plan their manoeuvres but more importantly it is bringing businesses closer to their customers with the help of the data.
All in all, Data Science is a promising field that shows great opportunities for aspirants. It is a field that is high paying and yet not entirely saturated that guarantees continuing growth and development for professionals committed to it.
Data Science & Machine Learning Techniques program at Thinklogix has been designed to help students learn about complex theory, algorithms, and coding libraries for Machine Learning and their applications. This course provides a broad introduction to machine learning, data science techniques, and statistical pattern recognition. A certificate of completion is provided by Thinklogix at the end of the course.