As the demand for skilled data scientists only continues to grow, big data courses are increasingly seen as one of the most effective ways to improve employability and help ensure a fulfilling career in our tech and data driven society. In fact, in a recent publication from IBM, it was predicted that there will be a 28 per cent increase in the number of employed data scientists in the next two years.
1. Diversification
No longer confined to certain key industries, businesses across the map are now looking to capitalize on the vast increase in data and the new big data technologies which are offering new ways for analyzing and adding value. With new opportunities presenting themselves every day, big data offers great prospects for anyone looking for a well-paid career in an exciting and highly dynamic field.
2. Flexibility
Although the traditional academic route is one way into the universe of big data, there are now also lots of alternatives ways to gain valuable training without the cost and administrative necessities of attending a formal university. Any motivated individual can find the right program for them.
3. Employability
Across the board, employers are realizing that employees who have the skills necessary to manipulate data and analytics to solve business problems are increasingly valuable. Regardless of former background or even position in a company, many employers are looking to invest in their team and get them trained properly in a field which they realize is only going to grow.
4. Streamlined
The original methods for data driven work could be quite tedious and often involved a lot of repetition. Advancements in the field mean that a lot of these less interesting tasks have been removed due to self-service infrastructure and tools designed to automate many of the steps involved with data cleaning, preparation and analytics. This allows workers to perform complex data-driven operations such as predictive modeling and automation without needing to engage with the arduous process of coding complex algorithms from scratch.
5. Options
Of course, there is still a huge range of specializations that exist within the field of big data, and it worth doing some research and even reaching out to potential or current employers to figure out what course of action might best help you get the results you want. Generally speaking, you’re going to want to familiarize yourself with the fundamental principles, including statistical programing in R, cluster analysis, natural language processing and practical applications of machine learning.
Although this might all sounds pretty abstract to someone new to the field, it is important to remember that creative data products are all about solving real-world problems, and that once you speak the data language, you will see how these skills can make a real impact on the world around you.
6. Finding your fit
Whether you’re more intrigued by data-driven decision making or machine learning, realize that any course you take will provide you with a foundation to continue growing upon and developing. A good place to start might be exploring the material found in a “Data Science Essentials” or “Data Science Fundamentals” course and see what most peaks your interest.
7. Don’t be intimidated
Depending on the specific program, those students with experience in computer science or mathematics will likely progress more quickly through these programs, but with a little patience and determination a complete beginner can still become proficient in a short amount of time. These courses are all designed to start from the top and cover all the material you need to know to work effectively throughout the entire process. Additionally, with the added support of the supplementary resources being made available online, big data really can be your gateway into an exciting new career.
