Audience feedback at conference talks is *really* useful for speakers and organisers. It lets speakers understand what they're doing well (and perhaps what they're not). It helps organisers gauge the direction of content (more of this, less of that).
Reading these this morning makes me very proud of all the speakers at #Current22 😁
There's also some fair criticism in there that's great feedback to work with speakers and the program committee on
But when you're leaving feedback… don't be *that* person:
"here, let me correct your pronunciation. You're welcome"
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So does @MySQL Heatwave "Lakehouse" actually act as a lakehouse as defined elsewhere and write *back* to object storage through a table format? Or it's just MySQL that can also query data that's on object storage? The latter is cool of course, but the naming is puzzling me.
The press release is unclear, other than in the fact that OMG OUR BENCHMARK SHOWED WE ARE FASTER, WHO'DA THUNK IT?!! oracle.com/news/announcem…
The technical brief (oracle.com/a/ocom/docs/my…) makes note of "the HeatWave internal format" for working with external data. There's lots of mention of CSV and Parquet and magic fairies^H^H^H^H^H^H^Hmachine learning to guess at schemas.
Looks like a fascinating set of talks at @coalesceconf#dbtcoalesce next week. I'll be firing up my 56k modem and dialling in for several of them including:
Keynote: The End of the Road for The Modern Data Stack You Know, from @jthandy and @margaretfrancis
Are we going to have batch and streaming forever, or will they converge? @esammer says at the heart of systems lambda arch will go away and kappa will eventually win out. Once in DW perhaps batch will remain for its familiarity to analytics engineers.
@notamyfromdbt - Microbatching gets used to simulate streaming but with same toolset for familiarity, but it doesn’t scale