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#4070DATAcated On Air57.0 / 100Get badge
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AI & DataNEW this period

DATAcated On Air

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

AI & Data rank

#375 of 495

Best B2B AI & Data Podcasts →

Across the index

#4070 of 6219

Substance

Top 65%

outscores 35% of the index

Why it scores where it does

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.

The five-dimension breakdown

Averaged across 1 recently scored episode, with cited evidence.

Insight Density

11.0 / 20

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”

Originality

8.0 / 20

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”

Guest Caliber

16.0 / 20

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”

Specificity & Evidence

13.0 / 20

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”

Conversational Craft

9.0 / 20

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”

Standout episodes

  • How to Build a Scalable Analytics and AI Foundation with S3

    2026-03-22

    57

Rank over time

First period on the Index - history builds from here.

Episodes

1 scored on substance · 60 tracked in total.

  • How to Build a Scalable Analytics and AI Foundation with S3

    2026-03-22 · 46 min

    57 / 100
  • The logical path to data

    2025-10-31 · 47 min

    Not yet scored
  • Bridging Gaps with AI: How Good360 and Salesforce Empower Nonprofits

    2024-11-22 · 21 min

    Not yet scored
  • Ask Anything, Solve Everything with Altair

    2024-10-22 · 40 min

    Not yet scored
  • How to Read Gartner’s Magic Quadrant + Critical Capabilities Report

    2024-08-15 · 42 min

    Not yet scored

Frequently asked

What is DATAcated On Air's substance score?
DATAcated On Air scores 57.0 out of 100 for substance and ranks #4070 on The B2B Podcast Index. That puts it ahead of 35% of the B2B podcasts we rank and #375 of 495 in AI & Data. The score reflects insight density, originality, guest caliber, specificity and conversational craft across recent episodes - not downloads.
Is DATAcated On Air worth listening to?
DATAcated On Air is ranked on The B2B Podcast Index with a substance score of 57.0/100. See the five-dimension breakdown above to judge whether it fits what you're after.
Who hosts DATAcated On Air?
DATAcated On Air is hosted by Kate Strachnyi.
How often does DATAcated On Air publish?
DATAcated On Air publishes daily, has 108 episodes, released its most recent episode on 2026-03-22.
Which DATAcated On Air episode should I start with?
Our highest-scoring recent episode is "How to Build a Scalable Analytics and AI Foundation with S3" (57/100) - a good place to start.

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Frequently discusses

Companies, products and tools that come up most across this show's episodes.

Amazon · 2Dedicated · 2Oracle · 2Salesforce · 2AWSS3HadoopApache IcebergAmazon AthenaEMRNetflixBucketsDenodoUniversity of MichiganInformaticaO'ReillyRise of Logical Data ManagementGood360

Guests who've appeared

Paul MeganChristopher GardnerAlberto PanDr. Ingo MjersvaAnn Lapkin

Topics this show covers

The themes that come up most across this show's episodes.

Retrieval Augmented Generation (RAG)Vector embeddingsApache IcebergAmazon S3S3 TablesS3 MetadataS3 VectorsAmazon AthenaEMRHadoopData governanceSemantic LayerData lakesDenodoData warehousesData fabricO'ReillyData mesh

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