Breaking into data analytics can feel overwhelming.
Where do you start? What tools do you learn first?
Don’t get me wrong; there’s plenty of advice out there! But is all of it good?
My general recommendation is this: develop an understanding of how to think like an analyst, learn the basics like Excel and SQL, and choose a data visualization tool to focus on.
As someone who transitioned into data a few years ago, I've created a video to walk you through the exact roadmap I'd follow if I was getting started today.
Take a look:
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Lauren Rosenthal
Customer Success Lead & Analytics Specialist
As an Account Exec and Data Analyst on the Maven Team, Lauren plays an integral role onboarding & supporting our B2B teams, helping analyze our key success metrics, and producing great content.
Frequently Asked Questions
What is Maven Analytics?
Maven Analytics is an online learning platform that helps professionals and organizations build practical data and AI skills in analytics, business intelligence, and data science. Our hands-on courses are designed to help learners stay competitive and future-proof their careers in the age of AI.
Are data analysis and data science still good career paths?
Absolutely. As long as companies collect and use data, they need people who know how to turn that data into results. Roles are changing, and so are the skills needed to succeed, but the career paths remain strong. Focus on data literacy fundamentals, business thinking, communication skills, and learning how to use modern data and AI tools, and you can build a strong career.
Will AI replace data jobs?
AI is changing how data professionals work, but it is not replacing the need for skilled analysts and data scientists. Instead, AI is becoming another tool in the data workflow. Organizations still need people who can ask the right questions, interpret results, communicate insights, and apply data to real business decisions. The most successful professionals will be those who learn how to combine core data skills with modern AI tools.
How can I future-proof my career in analytics?
Future-proofing your analytics career means building strong core data skills, understanding business context, and learning how to work effectively with AI rather than compete with it. The goal is to become a better analyst, problem solver, and decision-maker.
How long does it take to build job-ready data skills?
That depends on your starting point and goals, but many learners can build meaningful skills over a few months with consistent practice, even when studying part-time. The most important factor is applying what you learn through hands-on projects and real business problems.
