In the 18th and 19th centuries, economies and nations were fueled by coal and steam engines. The 20th century was ushered in with the noise of big guns and bombs. In the 21st century, data is the language of the world.
Data is the fuel that powers the world’s industries. Never before has it been possible to collect, analyze and store such large amounts of information.
As a result of the global digitization, alternatively known as the Internet of Things, data is important to every innovation and enterprise. Thus, it’s no surprise that the big data market is statistically speculated to grow to over $100 billion by 2027.
Getting into the data science career path
If you’re looking to get into big data as an analyst, you need to have a good basic understanding of what it’s about.
As opposed to normal data, big data refers to large and complex data sets that cannot be processed using traditional methods. For this reason, they have high variety, volume, and variety. With innovations like AI (artificial intelligence), data sets have become more dynamic and complex.
As a result, newer methodologies like data mining and predictive technologies have evolved to analyze the data and reach productive inferences.
What is your job description as a big data scientist?
As a big data scientist, you’ll be tasked with analyzing and gathering big sets of unstructured and structured data. You’ll have to combine a good knowledge of statistics, computer science, and mathematics to do this.
Big data scientists spend considerable time analyzing the data to formulate accurate predictive models that help corporations, enterprises, and cloud-based solutions innovate better, solving business challenges.
In addition, data scientists can work in an executive capacity, tasked with communicating the vague and unstructured language of raw data and interpreting systematically for positive-driven decision-making.
Data scientists also have to work interoperably with multiple teams, collaborating with business operations for effective marketing and customer success.
Academic requirements
To become a data scientist, you need an undergraduate data science degree or a degree in a related field like Mathematics, Statistics, and Computer Science.
At the senior level, a Master's degree is a plus at the senior level and will give you the edge over other applicants. To complement your professional standing, relevant internships, additional academic qualifications, and networking experience will serve you well.
If you’re interested in being a big data scientist but lack the relevant bachelor’s degrees, you should focus on mastering the raw analytical skills skills via online courses, bootcamps, and intense personal studies.
What skills are required to become a big data scientist?
As with any other career path, there are some required core skills to go professional:
Machine learning systems
Risk analysis
Research
Software engineering
Effective communication
Cloud systems
Data structures and warehousing
Data mining
How much do big data scientists earn?
As per the U.S Bureau of Labor Statistics, big data scientists can expect to earn over $100,000 annually.
So, if you’re looking to get into this career path, you can be rest assured that the effort will be worth it.
To learn more about this career path and interlinked disciplined, check out ElementX.