If you’re figuring out your career goals or looking to change track, there is a lot to be said for training in data science. In 2018, Forbes highlighted that we use 2.5 quintillions of data every day, and two years on, that figure is likely to be even higher. It’s no surprise, then, that demand for data experts is on the rise.
How to Qualify in Data Science
If you’re analytical, logical, and great at problem-solving, a certification in data science could open you up to a range of potential careers. The first step down any of these career paths is completing a graduate certificate in data science. Studying with a trusted institution, you’ll have impressive credentials to set you on the right track in as little as 24 weeks, which means your ideal career in data could be just a few months away.
Data experts hold the coveted skills needed to collect, organize and analyze data in a way that helps organizations and consumers alike to make data-driven decisions. There are many ways that these skills can be put to use.
Qualified data scientists are in high demand throughout every industry because almost every time we interact with technology, there is data to be processed. Whether it’s the traffic-free route you use on Google Maps or the perfectly tailored music recommendations on your Spotify account, a data scientist behind the scenes has made your day to day life more efficient and enjoyable and been paid very well to do so.
As a data scientist, you will sift through huge amounts of raw and complex data, searching for patterns that will help to streamline processes and help businesses to make informed decisions about their products and services.
Data architects design and maintain data systems based on the specific needs of their organization or client. The models they build need to improve the performance of data processes, present the collection of information from customers in a smooth and efficient manner, and streamline the secure storage of such data.
A data architect must have one eye on the big picture at all times, as they’re responsible for the end-to-end storage, collection and performance of their models. It’s a highly involved and specialized role, but for most professionals, the challenge and the considerable compensation make it all worthwhile.
A statistician focuses on the application of statistics to real-world problems in ways that will help their employers to more efficiently conduct their business. They collect and analyze statistical data, drawing conclusions to aid practical decision-making for their organization.
Though the role has similarities to that of a data scientist, statisticians are more concerned with the mathematics driving the data. Statistics have applications within every industry and the demand for professionals with the skill sets needed to handle this data is expected to grow by an impressive 30% in the next few years.
Whatever path you choose, data science is a growing and fruitful industry, with plenty of opportunity for growth and the potential for a long and satisfying career.