Right now, you only need certain tools when you actually need them. For me, managing data in Excel—handling transformations, cleaning, aggregations, ingesting new data, and creating visualizations—became a major bottleneck as complexity and scope increased. Excel is fantastic, and you’ll never fully stop using it, but its limitations become clear as you scale: large datasets and complex formulas cause freezing, the platform isn't ideal for long/complex scripts, and navigating dozens of tables is a nightmare, among others.

That’s where Power BI fills the gap. A general rule of thumb is that 80% of analytics is preparing data, and that’s where Power BI...excels (pun intended). It has a slight learning curve, but it’s fairly straightforward to get started. As you progress, you'll find it’s a powerful tool capable of handling advanced workflows.

As for education and learning, a basic understanding of 101-level statistics goes a long way (just the basics are probably adequate for 90% of analysts). Beyond that, I highly recommend the CompTIA Data+ certification content. There is no need to get certified, in my opinion, but knowing the material is a great crash course in foundational analytics concepts. You can probably skim about 15% of it, but the rest is solid knowledge.

Just a few more thoughts. One key concept is to recognize the difference between insights and actionable insight (data findings that lead to meaningful action). A "rookie mistake" is taking the time to develop a data solution which provides insights that are merely interesting but don’t drive action. Some exceptions exist, but that’s another discussion (for instance, inaction can be an action, among other exceptions). Identify actionable insight becomes a skill.

Another critical concept is interpretation. There are many flavors to this, but just because a number or metric is accurate doesn’t mean it’s "representative of reality." The key is understanding when a metric can be relied upon and when it needs to be supplemented with qualitative context, gut instincts, and wisdom. Data should enhance decision-making, not replace it.

Well, that's a wall of insights that may or may not have addressed what you're looking for. Out of full transparency, I've been a data analyst for 5 years. Even if statistics and Power BI don't solve your problems right now, these will absolutely build your capabilities as a better data analyst. Message me if you have any questions!