
Hosted by Kate Strachnyi
The DATAcated On Air podcast is focused on providing the audience with interesting content for the data community. Episodes will include interviews with experts in the space, as well as presentations on various data science, analytics, machine learning and artificial intelligence topics.
108 episodes · publishes daily · latest 2026-03-22 · ~40 min/episode
Rank
#4070
Substance
57.0
/ 100
Breakdown
Scored 2026-07
Updated monthly
Across the index
#4070 of 6219
Substance
Top 65%
outscores 35% of the index
DATAcated On Air ranks #4070 on The B2B Podcast Index with a substance score of 57.0 out of 100, scored across 1 recent episode. It scores highest on guest caliber and specificity & evidence. Paul is a genuine, long-tenured product leader who has worked on S3 since 2018 and at Amazon since 1997 - he's a real practitioner, not a career podcaster. The promotional format, however, prevents his expertise from going deeper than public messaging, which caps the score.
Averaged across 1 recently scored episode, with cited evidence.
There are a handful of concrete nuggets - Intelligent Tiering saving $5 - 6B, conditional writes reaching 2% of all S3 writes, and a reasonably clear explanation of S3 Tables/Vectors/Metadata - but the episode is heavily padded with giveaway segments, mascot chat, birthday trivia, and platitudes like 'S3 just works.' The actual insight-per-minute rate is low for a 46-minute runtime.
“intelligent tiering which uh, launched Now I think 2019...I think we're above 5, $6 billion at this point that customers have saved”
“it's like 2% or something like that of writes today in S3 are conditional rights”
The episode is essentially a product marketing session; every point made - Iceberg for analytics, RAG for AI, elasticity, 11-nines durability - is standard AWS messaging freely available on the product page. There are no contrarian arguments, no first-principles reasoning, and no unexpected claims.
“90% of what we build comes directly from customers. And that's one of the cool things about working here, is that we don't overthink strategy and vision”
“S3 just works”
Paul is a genuine, long-tenured product leader who has worked on S3 since 2018 and at Amazon since 1997 - he's a real practitioner, not a career podcaster. The promotional format, however, prevents his expertise from going deeper than public messaging, which caps the score.
“I started Amazon in 97...worked in the first, one of the first data centers...came back to AWS in 2018 and have been working on S3 ever since”
“I left on S3's birthday, the first”
The episode offers several concrete figures - 500 trillion objects, 200 million requests per second, 11 nines durability, Intelligent Tiering saving $5 - 6B, 2% conditional writes - and correctly attributes Iceberg to Netflix circa 2017. However, there are no named customer case studies, no architectural specifics, and no real data on AI workload performance benchmarks.
“I think we're above 5, $6 billion at this point that customers have saved by just wow, opting into intelligent tiering”
“Apache Iceberg, invented a few years ago at Netflix. It's an open data format...I think, 2017, something like that, at Netflix”
The host is personable but repeatedly breaks conversational momentum for giveaway draws, mascot trivia, and hashtag promotions. Questions are generic and promotional ('top three accomplishments,' 'favorite launch'), and no claim is ever challenged or probed beyond a surface follow-up.
“Without S3, do you think AI and big data would be where it is now? That's a good question”
“I'm gonna spin the dial here. Okay, here we go. We're gonna go ahead and draw again for one of these cool S3 squishies”
First period on the Index - history builds from here.
1 scored on substance · 60 tracked in total.
How to Build a Scalable Analytics and AI Foundation with S3
2026-03-22 · 46 min
The logical path to data
2025-10-31 · 47 min
Bridging Gaps with AI: How Good360 and Salesforce Empower Nonprofits
2024-11-22 · 21 min
Ask Anything, Solve Everything with Altair
2024-10-22 · 40 min
How to Read Gartner’s Magic Quadrant + Critical Capabilities Report
2024-08-15 · 42 min
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