Big data has always been billed as the future of business. But the future is now. Its impact is felt across all sectors of the economy, and with that impact comes some very lucrative employment opportunities. If you are interested in launching a career in the booming industry of big data, take a look at these top five tips to get you started:
1. Pick a Career
Having an end goal is essential to be successful in any walk of life, and launching a career in big data is no different. Clearly defining your career goals before choosing a career focus is an important first step, as there are a lot of different paths in the data science industry.
To get a better feel for the best role for you within big data, talk to some people involved in the industry to figure out what the different roles involve (data scientist, data engineer, data visualization expert, market research, etc). People love to talk about their work, so find a way to network within the industry, and gain some insight and mentorship from an established figure, and ask them important and relevant questions. From there, it will be easier to decide what role best fits your interests and skill set.
2. Learn the Role
Once you’ve figured out your niche in the big data industry, it’s time to build on your expertise and make yourself a top candidate for a position in your chosen area. With the explosion in demand for data scientists has come an abundance of resources for learning the trade. Do a bit of research and you can find a paid or even free training course that will teach you the necessary tools to become successful in your chosen role. Applying yourself with these courses is the best way to gain expertise on your own time, and prepare yourself for the start of your career.
3. Specialize in a Specific Tool
There are a variety of computer languages that are useful within the data science industry. Once you have figured out your preferred career and found some resources to help prepare you for it, it is important to know what computer language is applicable in the given area. You can start with some of the more basic languages to get a better grasp of coding, or ones that you are more familiar with. But don’t stretch yourself too thin trying to master all of the more advanced languages.
Very few positions require an advanced understanding of multiple languages. The figure of speech “Jack of all trades, master of none” applies here, as you are much better suited becoming an expert in one specific language that is valuable to your profession than trying to learn them all.
4. Learn to Be Practical
There is a lot of theory that goes into the world of big data, and it can be easy to get caught up in theoretical work that doesn’t have much practical application in the real business world. It’s important when setting out on your career to stay centered on what you’re trying to do, and how the skill set you are acquiring and refining will be useful in a real-world setting.
One of the best ways to simulate this before landing a position in big data is to apply your learning to available open data sets. This will give you a chance to interpret results and become comfortable with analyzing data, which you can then demonstrate to prospective employers.
5. Find Immediate Opportunities
For those already employed within the business sector, you likely don’t have to look outside of your own company to find a way to contribute as a data scientist. If you are not currently doing data analysis for your company, the best way to do this is to find small, incremental ways to contribute useful insight, and gain the trust of your superiors. Find ways to contribute information that is not currently displayed in your company’s business reports, and it will open the eyes of the bosses. From there you can start implementing more complex analysis like predictive modeling, and move your way through the ranks.
Big data is an industry that is just beginning to reach its business potential. The demand for data scientists continues to skyrocket, and there are both jobs and money to be had in the field. Follow these five tips to launch your career in big data.
Originally published on MeriTalk.