For five years as a data analyst, I forecasted and analyzed Google’s revenue. For six years as a data visualization specialist, I’ve helped clients and colleagues discover new features of the data they know best. Time and time again, I’ve found that by being more specific about what’s important to us and embracing the complexity in our data, we can discover new features in that data. These features can lead us to ask better data-driven questions that change how we analyze our data, the parameters we choose for our models, our scientific processes, or our business strategies.~ Zan Armstrong from, https://stackoverflow.blog/2022/03/03/stop-aggregating-away-the-signal-in-your-data/
This one just has neat graphs in it. And it has some interesting insights about what data analysts do. The phrase “big data” has been tossed around a lot in recent years—the way “quantum mechanics” gets tossed around by people who have no idea about that either. This article isn’t about truly big data sets, but it’s a neat dive into energy usage as an example of some spiffy data analysis.