Having said that, we are working on triggering table builds from watching changes to consumed data sets, which paired with an incremental table build would allow you to reliably achieve latency of under a few minutes.
Near realtime (say sub 1-minute) feeds can be leveraged to extract a lot of value out of the data you're collecting. Perhaps maybe not for your typical SaaS startup, but for free-to-play video games you end up leaving so much value on the table if you can't quickly (automatically) respond to spend or churn indicators.
I think a good rule of thumb for this is looking at how fast your decisions are made. If you're making decisions daily then refreshing your data every 24 hours is probably good enough. If you're making decisions every hour, then every 60 minutes is probably good enough.
Another factor is scale. When you're dealing with 6-figure CCUs and are trying to optimize conversion or retention through split-testing, figuring out which variants are anomalously poorly performing quickly can save you a whole lot of money.
I reckon there's at least a 50 titles that can benefit from streaming analytics, which immediately affects anywhere from 100-500 employees (analysts, engineers) and likely influences over 1000 (broader company). That's a significant portion of the field.