How to Know When to apply for Interviews ?

21 May 2026 · 1 min

Watch on YouTube

1:22

In this concise career‑advice video, the speaker outlines two essential steps for aspiring data analysts to determine when they are ready to start applying for jobs. First, they stress the importance of understanding what “great” work looks like by reverse‑engineering high‑quality projects—such as business dashboards on Tableau Public—and attempting to recreate them. This helps learners form a concrete benchmark for competency. Second, they argue that traditional multiple‑choice quizzes are insufficient for evaluating real‑world data‑analysis ability. Instead, they recommend a realistic skill audit: joining a community or finding a mentor for feedback, or, if that’s unavailable, using AI tools like ChatGPT or Claude as a surrogate tutor to review dashboards and visualizations. The overall message is that practical, benchmark‑based practice and authentic feedback are the true indicators of interview readiness.

Chapters

When you're learning data analyst skills, when do you know that you're good enough to start applying for interviews? I'm going to break down the 2 key things that you need. You have to know what great looks like and then reverse engineer from there. When we're first learning anything, we have no idea what actually good skills look like. What does a good level of skills look like? Great way to do this is finding very high-level projects online and then reverse engineering them. For example, if you go on Tableau Public, look up business dashboards, you can literally reverse engineer the projects, try to build or emulate them yourselves. Doing stuff like this is a must. Because we really don't know what great work looks like if we're still very new to the field. The second thing is you have to audit your skills. So when you're self-learning, a common audit or evaluation tool that we go through are these multiple choice quizzes whenever we're taking courses. But that's just not how it works when it comes down to data analytics and building these skills. Multiple choice exams and quizzes are just not enough. The actual data analyst role is not like a standardized test. So you have to simulate a more realistic way to audit or evaluate your skills. The absolute best way to do that is to join some sort of community and get some sort of mentor. But if you don't have that, what you can do is utilize AI, ChatGPT, or Claude, and just make your own tutor skill auditor and give it dashboards, give it pictures of your visualizations, and ask it to evaluate your skill. It's not close enough to actually having a real person audit it, but it's better than nothing.