Moving to Data Analytics From a Different Career
Can you switch things up professionally and move from accounting or risk management to data analytics? The first question you should be asking is, do you really want to? Have you done the research to fully understand what it will be like to work in data analytics? Or are you just interested in the trendy sounding AI and machine learning job titles?
Why Data Analytics?
Most data analysts must put in some hard graft before they’re handling the cutting edge technology you’re fantasising about. So think very carefully, and take the time to consider what part of a data analyst’s role interests you, rather than the job title itself. This will help guide you in the right direction as you reroute your career path.
Understand what a data analyst does: they use technical tools to parse through large quantities of raw information in order to generate meaningful insights. Essentially, anything data-related will fall under their remit, whether it’s removing corrupted data or preparing reports for the business.
Good on Paper
Think about the roles you’ve previously held and the skills and experience you’ve acquired that could be repatriated into a data analytics role. Move any specific data analytics experience, projects or certifications to the top of your CV, and refresh the wording across your resume to reflect transferable skills and experience that make you a good data analyst candidate. Do the same with your LinkedIn account. Optimise your profile and emphasise your skills section, highlighting those that pertain to data analysis.
Data analysts require strong critical thinking and communication skills. So, at the very least if you can demonstrate the ability to think analytically about data, look beyond the numbers to the patterns beyond, and clearly and effectively convey your findings, you’ll be in with a good chance.
Think about building a professional data analyst portfolio. Simply put, it is a website which tells employers a bit about you and provides links to projects you’ve worked on. Wordpress is a popular hosting option as well as Wix, and Squarespace, where you can create your portfolio from scratch or use a pre-built template. Make it concise, easy to navigate and aesthetically pleasing.
Use the homepage to introduce yourself, your relevant data analytics experience and what drives you. Then come the projects. This should have a dedicated section, showcasing projects you’ve worked on. You can host your projects on your website or provide links to where they’re hosted elsewhere, e.g. GitHub, depending on the nature and technicalities of each project.
If you don’t know where to start with your projects, the idea is to work within an area to compose a data set that you can analyse. If you’re into boxing, for example, you could collect data on a particular boxer and see what factors identify how likely they are to win their next match. Previous wins, injuries, recent life events, previous matches and so on.
Get to grips with Python, R and SQL. If you can speak the language, quite literally, you will be able to navigate a career in data analytics. You need to develop the technical tools to be able to prepare and analyse raw data, create visualisations and share your insights. Get familiar with concepts such as data mining, data cleaning and ethics, and bone up on Excel and Tableau.
In the Know
Depending on where you are in your career, you have various options open to you in your pursuit of data analytics roles. If a return to university to complete a second undergraduate degree or master’s does not appeal to you, then look into a data analytics boot camp. A quicker and more affordable option, these courses will give you a good grounding in preparation for a data analyst career. Bear in mind, though, you may need to have developed some basic data analysis knowledge first. The universities of Oxford and Warwick also offer short courses in data analytics and data science, both under £3,000.
Data Analyst jobs are a great way to break into the realm of say data science, down the line. If you do pursue it, working in data analytics will instil you with core data science skills like SQL and Python that you’ll need to effectively collect, manipulate and implement data in future roles.