Everything Barr Moses said on any show that made the record, most notable first. Each card names its show and opens the statement there.
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 …”
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.”
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.”
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”
Moses: Centralized data teams become bottlenecks as data usage scales
“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.”
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.”
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 …”
Moses: Generating actionable data quality alerts without alert fatigue is inherently difficult
“Making alerts meaningful making them ones that your team can actually act on is something that's very hard to do that we've invested a lot to do.”
Moses cites 2022 revenues for BigQuery, Snowflake, and Databricks
“So you're seeing companies like BigQuery with 1.5 billion dollars in revenue, Snowflake with a billion dollars in revenue Databricks with eight hundred million in accelerating.”
Moses: Schema changes are a major culprit for data downtime
“So actually schema changes are a big culprit for data downtime.”
the MAD Podcast 1