[richardw]

Capture enterprise AI enthusiasm by providing a 1-stop shop for data and AI, optionally hosted on your own cloud tenant. Keep deploying functionality so clients never need another supplier. Partner with SAP, OpenAI, anyone who holds market share. Buy anyone that either helps growth or might help a competitor grow.

Enterprise view: delegate AI environment to Databricks unless you’re a real player. Market is too chaotic, so rely on them to keep your innovation pipeline fed. Focus on building your own core data and AI within their environment. Nobody got fired for choosing Databricks.

[jimbokun]

Can someone translate this to non-CEO speak?

[baggiponte]

You basically pay databricks a “fee” to choose the more appropriate and modern stack for you to build on, and keep it up to date. Never used it, but it handles with lots of the administrative bs (compliance, SLAs, idk) for you so you can just ship.

[forgetfulness]

That does sound, as you allude, like IBM on its long downward spiral of globbing up products to stay relevant and touting them as an integral solution, while in-house development stuck to keeping legacy products alive for their Enterprise contracts. I wonder if they'll be foolish enough to start doing consulting around them, obliterating their economies of scale in the process; so far they are going with the "consulting partners" approach.

Oh well. Databricks notebooks were hella cool back when companies were willing to spend lavishly on having engineers write cloud hosted Scala in the first place, and at premium prices to boot.

[cactusfrog]

A nice UI for a data lake house is underrated. I use AWS Athena at my work and it is just so bad for no good reason. For example, big columns of text are expanded outwards making reading the subsequent columns impossible.

[senderista]

Well UI has never exactly been Amazon's strong suit.