Is Data Analytics Hard to Learn?

Because the skills needed to perform Data Analyst jobs can be highly technically demanding, data analysis can sometimes be more challenging to learn than other fields in technology. But with those challenges come rewards; with the current global shortage of data professionals, the role of Data Analyst is in demand, meaning higher pay and better job security. A 2017 IBM study forecasted that demand would rise by another 28 percent by 2020, an increase of 364,000 jobs (to 2.7 million), further heightening that demand.

Yes, you can learn the fundamentals of data analysis on your own. As data analysis leans heavily on very focused knowledge of a discrete range of programming languages, as well as a range of easily developed soft skills, committed professionals with a knack for scripting can develop job-ready data skills over a relatively short period of time.

The basics of SQL, for instance, can take as little as two to three weeks for a beginner to pick up. Programming languages are a bit more complex. Someone with a good grasp of programming fundamentals can usually pick up the basics of Python in about eight weeks. To learn R, a person with programming experience may need only a week of part-time study, while a beginner will likely need closer to three weeks of full-time study.

Of course, none of these skills are used in isolation. To learn all of the above at a beginner level—as well as a battery of other skills every Data Analyst should know—typically takes at least 12 to 14 weeks. The fundamentals you can acquire in that time will equip you to enter the field and begin working right away; to become fully proficient at a grandmaster level (something that can really only be done on the job) may take years.

It’s also worth mentioning that acquiring this knowledge isn’t one-and-done; as the industry continues to evolve, Data Analysts will likewise need to stay committed to ongoing learning to stay on top of changes and updates to languages, tools, and trends.

Developing the skills needed to become a Data Analyst can take anywhere between 10 weeks and four years.

This range can be explained by the fact that there are many different paths to a career as a successful Data Analyst. A bachelor’s degree in computer science has traditionally been the starting point for many data professionals (that’s the four-year method), but it’s becoming increasingly common for Data Analysts to land positions directly from data analytics bootcamps and courses, which can be completed in as little as 10 weeks.

It can take anywhere from five to 10 weeks to learn Python programming for data analysis, although this depends on how much experience you have with programming languages and web development.

Generally speaking, though, Python can be considered very beginner-friendly, as it is known for its readability and ease of use. It’s also easy to install the language and run it from anywhere on your machine, which makes it easy to learn it on your own.

Yes, data analytics courses are an increasingly worthwhile investment and can help you master relevant programming languages like Python. These accelerated courses have many advantages over four-year degrees, as they allow for more hands-on learning and targeted skills development.

What’s more, the demand for data professionals has never been higher and is only expected to keep on growing. In addition to the number of new positions being created in data analytics – which number in the millions – employers also reward up-to-date data training in their existing employees, ensuring that they’re keeping up with the pace of change.

Salaries for data roles already compare favorably to other careers in tech, but even if you’re already working in the data field, boosting your skillset and gaining new specializations could bump your salary further. BrainStation’s data certificate courses were created to help professionals take advantage of these opportunities, allowing them to gain hands-on experience uncovering new insights from data sets, making data-driven predictions, and generating striking data visualization.

It’s worth emphasizing, however, that while Data Analysts enter into the field from a wide range of educational and experiential backgrounds, these positions do require a certain level of technical skill and good working knowledge of various programming languages. Though specialized, it’s still a very technically demanding field. In other words, be ready to embrace lifelong learning, as the industry changes rapidly.