Discover and read the best of Twitter Threads about #Current22
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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
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
coalesce.getdbt.com/agenda/keynote…
coalesce.getdbt.com/agenda/keynote…
Intentional learning: How and why you should learn Data Jawn, from @notamyfromdbt
I loved chatting to Amy at #Current22 and I also need to find out what a Jawn is :D
coalesce.getdbt.com/agenda/intenti…
I loved chatting to Amy at #Current22 and I also need to find out what a Jawn is :D
coalesce.getdbt.com/agenda/intenti…
Can’t wait for this panel discussion at #current22 with @takidau @notamyfromdbt @krisajenkins @AdiPolak @esammer - it’s gonna be awesome!
(and it’s being live-streamed - make sure you tune in!)
(and it’s being live-streamed - make sure you tune in!)
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
A scary list of all the things that could go wrong with data flows #Current22
Apparently data people are really boring people, so the hype around big data dying down fitted well #current22
The most boring diagram in IT. We’ve standardised the tooling around all this (except BI) #current22
Fivetran, dbt, snowflake are the boring defaults #Current22
Benn got into big data in 2012 at Yammer, right at the beginning of the hype
Recounts the story of Target using data science to send coupons to customers who were determined to be pregnant based on purchasing habits
“A lot of the time you don’t need real time” *gasp* #current22
Dan Sotolongo at #current22: RDBMS and SQL have stood the test of time. Sets the scene for stream processing by covering core concepts of tables and steams
#current22 handling event time joins in SQL using functions.
For a conference about data, you'd rightly expect that we use data when evaluating sessions and building the program for #KafkaSummit and #Current22. It starts with the program committee (confluent.io/en-gb/blog/int…) reviewing all the submissions with this: en.wikipedia.org/wiki/Elo_ratin…
The output from the session reviews is a single score for each talk, which then forms the basis for the first pass of building the program. Some talks are obviously great … whilst others are obviously not
This is just the beginning of the process. If we built a program on abstract score alone it probably wouldn't be a very balanced program. There are many more factors to take into account.
