Something that sounds obvious but is easy to forget: Emotions are a useful indication that something is off, not just something to push past. Ignoring emotions in the name of objectivity is a sure-fire way to alienate your stakeholders, churn your team open.substack.com/pub/robert…

So is the Modern Data Stack tenable at scale? The MDS seeded a beautiful idea that we deserve usable tools. But it's not clear where we'll land at scale: UX isn't a key purchasing criterion for CDOs, but cost is. No answers, but worth a discussion imo. win.hyperquery.ai/p/does-the…

Should we be more persuasive? A friend claimed that stakeholders would always fit your work to their story. While I don't completely agree, I do think we could be more intentional about how we present work to stakeholders. One of the biggest hurdles in involving ourselves in more strategic discussions with stakeholders is that it's hard to thread the needle between (a) rigorous complacency on the one hand, and (b) Aristotelian persuasion on the other. On the one hand: I'm a scientist -- I should therefore stay above the fray. On the other: if I'm arguing in the service of what I *know* is the right answer, isn't it okay if I exaggerate the truth? We need to avoid ends-justify-the-means persuasion, but still maximize the impact of your work. IMO, two behaviors can help: - Always come to discussions with a recommendation in mind (but don't be dogmatic about it). - Understand how your work will be used. win.hyperquery.ai/p/should-w…

Well-designed deliverables are more impactful. 💪 Good design enhances comprehension, persuasiveness, and impact, but the rub: well-designed deliverables can only be created in well-designed products. This is a core tenet we've held since starting @hyperquery, and why I've obsessed so much over the last few years over building the perfect data notebook . I know every incremental ounce of energy I spend making sure the app looks presentable is just that much more impactful for our users. But this is also why I'm so excited to announce our first guest post on @winwithdataio by @blazamatt, where he talks about the crisis that our industry is facing around UX: that data tools tend to have terrible UX. win.hyperquery.ai/p/analytic…

It's such an ambiguous time for analytics. With AI, the sem. layer, and new tooling, it’s hard to predict (or even understand) what'll happen w/analytics. Read my latest post in Win With Data for my takes on some of the finer points 🙂 buff.ly/3FyFq4n

I published a blog post in the @hyperquery blog that covers some of these points. Take a look if you're interested 😁 buff.ly/3JsK05d

The world's first serverless python backend is now out in @Hyperquery. 🙂 ... you probably won't notice a difference, but it's freaking cool, okay? So amazed that our team was able to innovate on this in such a game-changing way.

Analysts are ecosystem-builders. We craft environments that yield better decisions, strategy, alignment, a data-driven ethos. And there are 3 variants: 1. 📊 Data ecosystems (dashboards) 2. 📕 Knowledge " (analyses) 3. 🧠 Truth-seeking " Read more: win.hyperquery.ai/p/analysts…

The IDE is a terrible tool for analysis work. We should use it less. This was the original impetus behind @hyperquery, but I've been thinking about this more lately. What are the holidays for other than hot takes, after all? 🙂👇

"Run your data team like a product team" This was gold from @emilieschario and @tamurphy, but I've heard it misinterpreted often. IMO the core idea is: product teams have great processes that data teams would do well to adapt and adopt. (1/n)

Why analytics sucks: It's transactional. And while our processes need to improve, it doesn't help that our SQL tools are themselves transactional. Dashboards/IDEs make data the deliverable, w/o the narrative (& this is why we built @hyperquery). More 👇 medium.hyperquery.ai/why-ana…