Prepare for a career in data analysis

Data analytics is a great and growing career, increasingly able to command impressive salaries, as more companies realize the many ways data analytics can make a significant difference. in their business operations and results. But what should you do if you feel the call of data analytics and want to make it your career? What steps should you take on the path to your chosen career?

First – be sure. One of the main reasons data analysis is starting to attract the big bucks is that it is by no means easy. This involves intensive study of complex subjects, and you will need aptitude in mathematics and especially statistics, so if these things put you off, it is also wise – and also kind to everyone – to think again and choose a different path.

If you are still convinced that this data analysis is the way for you, then:

Master the basics.

Statistics will be your friends, your companions and your path to progress in data analysis. Learn to master them, interrogate them and get comfortable with them – start with statistics in Excel, BI, whatever takes your fancy, but start and familiarize yourself with the world of analytics and statistical manipulation.

This involves a range of disciplines, such as measuring deviations, determining probability distributions, testing hypotheses, etc. It’s also good to get at least a basic SQL background, because you’ll probably spend a lot of time in your career querying databases, so the sooner you have that under your belt, the better – and most likely , the faster your career will progress.

Choose a language.

Although it may take some time and a sample of the range of languages ​​available, it is wise to find either a base language or a handful of languages ​​that you are really comfortable with. Indeed, data analysis roles often require specialization in a particular language – like Python – or another. By narrowing your scope, you’ll have a better chance of getting your foot on the data analytics career ladder, and there should always be time as your career progresses to add new insights. other languages ​​as they interest you or are necessary for the progression of your career path as it develops.

The school career.

As with most career paths, especially those that lead to higher salaries and more complex and rewarding work opportunities, you will often need to show your certificates to gain entry. This usually means getting at least a bachelor’s degree, and maybe even a master’s degree in data analytics from a college.

Remember the part where we told you to be sure you wanted to go this route? Getting a bachelor’s degree will usually take you 2-3 years full-time, and a master’s degree at least another year more, and these days you can explain paying at least five figures, and maybe up to six, for the training that will prepare you for a life and a career in data analysis.

This means that you should carefully consider your finances before embarking on your data analytics degree.

You can complete online training and certification, which will take a fraction of the time and cost you a lot less upfront. But there are a few things to keep in mind if you decide to go this way. First, the extent to which employers will take your certification seriously will likely depend on the level and “weight” of your qualification. Study data analytics at Harvard for three years, and the qualification you walk away with is likely to open some serious and interesting doors almost as soon as you’re done. Get your qualification on and you’ll likely spend more time in smaller, more routine jobs, building your portfolio of project work to show off to bigger and better employers.

Like many modern disciplines, data analytics is part of the knowledge economy. The different routes you can take are also valid, but give you different routes. The balance between earning your qualifications depends on what you can afford and how much time you are willing to put in to work hard to build your reputation after qualification.

Build your portfolio.

Wherever you get it from, once you have your shiny new degree, technically you are a data analyst and you can call yourself one. But many companies will also want to see your skills in practical application. It means building your portfolio. Work on some projects, solo or in a team, that you think are good steps to show how successful you have been in managing data.

To enrich your portfolio, there are freely available datasets that you can use to create your own projects in your spare time. the elegance you develop in your wrestling and storytelling skills, and the end-to-end skills you have at your fingertips in the language(s) of your choice.

Be prepared for the long climb.

Like all jobs in the knowledge economy, you’re likely to start in entry-level data analysis roles, likely as part of a team. Be realistic in your initial post-qualification job search and focus on roles that use both your skills and qualifications, and that you are passionate about or interested in.

Above all, be ready to climb the ladder – everything you think you’ve learned and accomplished before you actually start To do your job in data analysis, it’s likely to be nothing compared to the experience of working to the demands and deadlines of real-world data analysis work. Learn, keep practicing and developing your skills, and you should have an enjoyable and profitable career in data analysis.

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