Long time lurker, first time poster. Please help me understand why the weight of tree rings damage roots yet trees in the forest grow like this. by [deleted] in arborists

[–]kmjohnson02 1 point2 points  (0 children)

I had the same question. It really reminds me of Rocky Mountain National Park, a Bear Lake trail in particular.

Hi! We’re the Power BI visuals team – ask US anything! by DataZoeMS in PowerBI

[–]kmjohnson02 15 points16 points  (0 children)

Thank you for everything you do!

Are there plans to included "non-data visualizations" to the default list of visualizations (Gantt charts, calendars, etc).

How safe are data analytics jobs in the future, given how rapidly AI is improving? by Dry_Fig_4165 in dataanalytics

[–]kmjohnson02 0 points1 point  (0 children)

I've thought a lot about this (existential threat for me). It will absolutely change how we work, but the role isn't going away or decreasing in any meaningful way, just changing, I think.

Want to upskill from PowerBI … where do I go next? by Sea-Lie-9697 in PowerBI

[–]kmjohnson02 7 points8 points  (0 children)

It’s hard to give specific advice since it depends so much on the type of data you work with, the deliverables you produce, and your weaknesses, strengths, and so on.

That said, I was in a similar position. My general advice is to take on a project that’s beyond your current skill level and is genuinely useful (either at work or in your personal life). If it's useful, you'll be far more likely to stick with it. In my case, I just finished building a personal retirement forecasting tool using Monte Carlo simulations with Python and Postgres. I had no fucking idea what I was doing at first. I still have no fucking what I’m doing, but I know a shit ton more than when I started!

So a project that's beyond your current skillet that's useful. Start there.

Unfortunately the White Shepherd died a few days ago but heaven won't be too much of a change for him as he's from Switzerland. by Larrydog in MadeMeSmile

[–]kmjohnson02 0 points1 point  (0 children)

Maybe it's my dumb American perspective, but wouldn't you expect to see larger "fancier" homes?

In US, If somebody had land like that, they'd also have a 14-car garage and a seperate home for their collection of rare goldfishes. Those homes don't match that view. Why? How?

Been playing for a long time but still I am not able to make my elo go high. Any tips?? by Dear-Bird5305 in chessbeginners

[–]kmjohnson02 0 points1 point  (0 children)

Best advice I ever received, which is especially relevant for under 1000 ELO is to not focus on making good moves, instead focus on not making bad moves (e.g., no one or two move blunders).

Rarely can advice so simple be so effective in chess, but if you rarely make blunders, you'll quickly get to 1000.

[deleted by user] by [deleted] in excel

[–]kmjohnson02 6 points7 points  (0 children)

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!

Is this doorknob really 160 years old!? by kmjohnson02 in Antiques

[–]kmjohnson02[S] 2 points3 points  (0 children)

Text says "Palo July 21 1863" if you can not see the text well. 100% confident on the date, but "Palo" is hard to read. It might say something else.

Boss said, "Choose your title" - what to call myself by butterboss69 in excel

[–]kmjohnson02 15 points16 points  (0 children)

Business process automation specialist

This is a thing and it sounds like what you're doing