If you’re looking into the prospect of becoming a data analyst – whether that is in the case of looking for degrees and further education, a decision to make a career change, or a horizontal change from somewhere else in the data space – you could hardly have chosen a better time.
In the last few years, and looking ahead to the next few, the data analytics space has gone through extreme growth and will carry on growing at an exceptional rate. With technology becoming an ever-more present fixture in both the day-to-day life of ordinary citizens and throughout industry, manufacturing, retail, and marketing, just to name a few sectors, the demand for high-quality data analysis has soared.
The more that technology is used in society, and the more it continues to improve in performance, the more data that is available to businesses and consumers alike to make better business and purchase decisions.
That’s why data analysts are in such huge demand – businesses have caught on to the immense potential of data analytics, and they want people like you to provide the service.
According to several metrics, the data science and analytics field is the fastest growing job market in the world, but before you get to work, there are skills that you should learn and knowledge that you should acquire to best prepare yourself.
Read on to find out more about the essential skillsets for future data analysts.
Structured Query Language (SQL)
An essential skill in best preparing yourself to become a data analyst is learning Structured Query Language or SQL. Many describe SQL as an advanced version of Microsoft Excel, as it can perform functions and provide processes that Excel simply cannot.
SQL is considered the industry-wide standard for data analytics, performing the same data management functionality as Excel but with much more power, giving analysts the ability to relate multiple data sets at once, as well as change those data structures altogether.
Specialists in the use of SQL are in high demand, with thousands of job postings for the skillset posted every month, and wages reaching up to $75000.
A huge part of being a successful data analyst, no matter where you are in the development process, from your data analytics training to your 50th year on the job, is utilizing critical thinking.
Of course, the main objective of a data analyst is to spot trends and draw intuitive conclusions from data that are more valuable than just what the average joe can perceive, and this takes considerable perceptive ability.
Making good analytical perceptions is a case of intimately knowing the subject at hand and how the raw data applies, as well as being able to spot patterns in the data and what this means in reality.
Having a solid grasp of the principles surrounding machine learning is an essential part of becoming a successful data analyst, even if you don’t exclusively work with the technology all the time or immediately.
Machine learning is an incredibly powerful tool for data analysis, as it can automatically spot patterns and analyze huge amounts of data in a short time. Having an understanding of the mechanisms will allow you to create machine learning tools that produce better results.