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#5626The Data Crunch42.0 / 100Get badge
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The Data Crunch

Hosted by Ievgen & Vadym

Welcome to the Data Crunch Podcast, brought to you by the OWOX team. Dive into the digital age of data as we talk about data, analytics, new marketing strategies, and the latest trends in tracking and privacy that affects every business.

40 episodes · publishes weekly · latest 2025-08-21 · ~13 min/episode

Rank

#5626

Substance

42.0

/ 100

Breakdown

Scored 2026-07
Updated monthly

AI & Data rank

#471 of 495

Best B2B AI & Data Podcasts →

Across the index

#5626 of 6219

Substance

Top 90%

outscores 10% of the index

Why it scores where it does

The Data Crunch ranks #5626 on The B2B Podcast Index with a substance score of 42.0 out of 100, scored across 1 recent episode. It scores highest on insight density and specificity & evidence. The episode names five real pain points (corporate restrictions, procurement lag, data ownership loss, punitive pricing, vendor lock-in) but all are well-known grievances in the data space. There is virtually no non-obvious insight per minute; the content reads as a checklist any data analyst would already recognise, with surface-level treatment of each.

The five-dimension breakdown

Averaged across 1 recently scored episode, with cited evidence.

Insight Density

10.0 / 20

The episode names five real pain points (corporate restrictions, procurement lag, data ownership loss, punitive pricing, vendor lock-in) but all are well-known grievances in the data space. There is virtually no non-obvious insight per minute; the content reads as a checklist any data analyst would already recognise, with surface-level treatment of each.

“Data analysts do not hate tools. They hate tools that take away the control over the processes that they are responsible for.”

“By the time the tool is approved, the problem it was meant to solve has either changed or been patched manually 10 different ways.”

Originality

8.0 / 20

Every argument here - bureaucratic procurement, opaque SaaS black boxes, Supermetrics-style punitive pricing, vendor lock-in - is a recycled industry talking point. The conclusion ('use open source/self-managed tools') is the standard counter-narrative with no novel framing, no contrarian angle, and no first-principles reasoning.

“open source options like Airbyte, Matomo and of course Oax datamarts”

“do not rely blindly on vendor black boxes like supermetrics”

Guest Caliber

7.0 / 20

Both speakers are marketers (a growth marketing manager and a head of marketing) at the same company whose product is being promoted throughout. There is no external practitioner, no data analyst or analytics engineering leader who has actually built systems at scale. This is internal branded content, not expert testimony.

“I'm Vadim, um, growth marketing manager at Oax”

“Joining me for this one is Yevgen, our head of marketing here at Ox”

Specificity & Evidence

10.0 / 20

A handful of named tools (Supermetrics, Looker Studio, DBT, Airbyte, Matomo) and one reasonably concrete anecdote about SQL query duplication in Looker Studio give the episode some grounding, but there are zero data points, no named companies (other than Ovox itself), no dollar figures beyond a vague '$50 per month tool', and anecdotes are anonymous and underdeveloped.

“Supermetrics is a great example of this kind of pricing model”

“Someone from the same marketing team that helped yesterday decided to use ChatGPT to edit your query. And you know that happens all the time”

Conversational Craft

7.0 / 20

The exchange is clearly scripted and coordinated between two colleagues; every host question is a leading prompt that hands the floor back for product promotion. There is no pushback, no genuine follow-up, and no moment of productive disagreement anywhere in the 18 minutes.

“And the solution, well the first solution that comes in my mind is using the self managed tools”

“Awesome. I love you. Again, how in depth you were describing”

Standout episodes

  • Season 2: Episode #30 | Top 5 Reasons Data Analysts Hate SaaS Tools (And What They Really Want)

    2025-08-21

    42

Rank over time

First period on the Index - history builds from here.

Episodes

1 scored on substance · 40 tracked in total.

  • Season 2: Episode #30 | Top 5 Reasons Data Analysts Hate SaaS Tools (And What They Really Want)

    2025-08-21 · 18 min

    42 / 100
  • Season 2: Episode #25 | Building a Reusable SQL Library: Best Practices & Pitfalls

    2025-06-27 · 10 min

    Not yet scored
  • Season 2: Episode #23 | Version Control in Analytics and Why It Matters

    2025-06-12 · 11 min

    Not yet scored
  • Season 2: Episode #21 | Facepalm Moments in Analytics and What They Teach Us

    2025-05-30 · 13 min

    Not yet scored
  • Season 2: Episode #20 | Building Trust Through Data Lineage

    2025-05-22 · 12 min

    Not yet scored

Frequently asked

What is The Data Crunch's substance score?
The Data Crunch scores 42.0 out of 100 for substance and ranks #5626 on The B2B Podcast Index. That puts it ahead of 10% of the B2B podcasts we rank and #471 of 495 in AI & Data. The score reflects insight density, originality, guest caliber, specificity and conversational craft across recent episodes - not downloads.
Is The Data Crunch worth listening to?
The Data Crunch is ranked on The B2B Podcast Index with a substance score of 42.0/100. See the five-dimension breakdown above to judge whether it fits what you're after.
Who hosts The Data Crunch?
The Data Crunch is hosted by Ievgen & Vadym.
How often does The Data Crunch publish?
The Data Crunch publishes weekly, has 40 episodes, released its most recent episode on 2025-08-21.
Which The Data Crunch episode should I start with?
Our highest-scoring recent episode is "Season 2: Episode #30 | Top 5 Reasons Data Analysts Hate SaaS Tools (And What They Really Want)" (42/100) - a good place to start.

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Guests who've appeared

Yevgen

Topics this show covers

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

dbt · 3Google SheetsMatomoLooker StudioSoC2 complianceVendor lock-inGoogle Apps ScriptOax datamartsSupermetricsAirbyteBigQueryDataformGitHub ActionsMetabase modelsLooker PDTsOxData martsSQL naming conventions

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