Insight certainty 4/5 debate potential 2/5

Moses: Centralized data teams become bottlenecks as data usage scales

Barr Moses · Unlocking Data Observability with Monte Carlo's Barr Moses · Apr 12, 2022 · at 11:07

Barr Moses, co-founder and CEO of Monte Carlo, discusses the shift toward decentralized data architectures like Data Mesh as organizations scale data usage.

0:00 / 0:09exact quote · 9.7s
▶ Watch the full episode on YouTube → 720p mp4 · rendered on demand · StarZero watermark
“Today you have like hundreds of people working with the data. It does not make sense anymore that there's one team that sort of has the keys to it and is really actually just ends up as a bottleneck.”

quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →

More from Barr Moses

Assertion Contradicted
Moses: Monte Carlo uniquely offers out-of-the-box cross-system observability
“So we're actually the only sort of product and market that you can connect today to those sort of different systems and sort of automatically out of the box, get an overview of what the health of your data looks like and sort of observability for your data on …”
Barr Moses Apr 12, 2022 ▶ 13:15 Unlocking Data Observability with Monte Carlo's Barr Moses
Opinion
Moses: Traditional data catalogs are dead; long live automated data discovery
“We actually wrote a blog post not too long ago called data catalogs are dead. Long live data discovery.”
Barr Moses Apr 12, 2022 ▶ 18:26 Unlocking Data Observability with Monte Carlo's Barr Moses
Assertion Not checkable as stated
Moses: Public companies accidentally report incorrect financial numbers to Wall Street
“Companies actually report numbers to the street and accidentally report, report the wrong numbers, or about to report the wrong numbers.”
Barr Moses Apr 12, 2022 ▶ 2:42 Unlocking Data Observability with Monte Carlo's Barr Moses
Insight
Moses: Validating data at a single pipeline point is no longer sufficient
“And so making sure that your data is accurate at only one point of the pipeline is just no longer sufficient”
Barr Moses Apr 12, 2022 ▶ 9:52 Unlocking Data Observability with Monte Carlo's Barr Moses
Insight
Moses: Machines cannot infer semantic business logic without human input
“I don't think that a machine can actually infer that we can infer something without knowing that business knowledge. It's not possible, and that's also not what we attempt or attempting to do at Monte Carlo.”
Barr Moses Apr 12, 2022 ▶ 19:26 Unlocking Data Observability with Monte Carlo's Barr Moses
Prediction Not checkable as stated
Moses: Automation can resolve 80% of data downtime causes
“By introducing that level of automation, we can reduce our customer's team's work. Work from, you know 80% manual work to 20% manual work. So we can actually, you know, with the automation cover, cover 80% of reasons for why data downtime incidents happen and …”
Barr Moses Apr 12, 2022 ▶ 19:39 Unlocking Data Observability with Monte Carlo's Barr Moses
Made with StarZero

Turn any episode into a week of clips.

This entire site, over 400 conversations transcribed, diarized, checked and made playable, runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the moments worth sharing, cuts them, captions them, and reframes them for every feed.