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Satyen Sangani

CEO and Co-Founder, Alation · 1 appearance on the record.

computed by AI from the episodes · how this works → · full disclaimer →

founderexecutivehost@satyx ↗LinkedIn ↗alation.com ↗

Satyen Sangani is the CEO and co-founder of Alation, which he launched in 2012 to develop data intelligence and governance software. Before founding Alation, he spent nearly a decade at Oracle managing analytical applications.

8statements → 1claims → 0claims resolved → 3.88/5average certainty → 2.38/5average debate potential → 2said about them ↓

1 not checkable as stated how the 1 claim stands · each chip opens the sources

1 assertion · 4 opinions · 3 insights · every statement was checked. The predictions and assertion are the 1 claim: statements the public record can support or contradict. 0 are resolved, and 1 names no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Satyen argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

How they sound: speaking style how? →

288 words/min while actually speaking · 24.1 um and uh per 1k words

No argument clarity score for Satyen Sangani: no usable question→answer exchanges on raw tape (a fair score needs 8+). We do not score a sample that small. Roundtable and news formats yield far fewer direct exchanges than interviews.

Measured by listening to the audio itself: 4,196 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →

Everything Satyen Sangani said on the MAD Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Opinion
Enterprises suffer from internal fake news and alternative facts
“You have an alternative facts problem that exists inside of the enterprise with as much fake news, with as much lack of understanding, as you do in the public domain.”
Satyen Sangani May 24, 2017 ▶ 3:37 Fake News, Alternative Facts and the Enterprise // Satyen Sangani, Alation (FirstMark's Data Driven)
Opinion
Enterprise data analytics investments create as much noise as signal
“My contention to you in this audience is that the investment in data analytics that every single person in this room is making for the companies that you are making is building as much noise as signal.”
Satyen Sangani May 24, 2017 ▶ 3:00 Fake News, Alternative Facts and the Enterprise // Satyen Sangani, Alation (FirstMark's Data Driven)
Insight
Measuring churn against contracts up for renewal is most accurate
“Churned revenues are the revenues over the things that were up for renewal. Now, in theory, that's the most accurate claim. That's the most accurate metric, because if something wasn't for renewal, then you can't really say that it churned, right?”
Satyen Sangani May 24, 2017 ▶ 9:31 Fake News, Alternative Facts and the Enterprise // Satyen Sangani, Alation (FirstMark's Data Driven)
Insight
Controlling data allows people to construct whatever narrative they want
“You control the data, and you build a narrative in a way that supports the claim that you want to make.”
Satyen Sangani May 24, 2017 ▶ 2:54 Fake News, Alternative Facts and the Enterprise // Satyen Sangani, Alation (FirstMark's Data Driven)
Insight
Information overload drives confirmation bias because parsing data is too painful
“You look for the information that supports the claim that you want to make, because parsing through all the information is just too much of a pain.”
Satyen Sangani May 24, 2017 ▶ 5:31 Fake News, Alternative Facts and the Enterprise // Satyen Sangani, Alation (FirstMark's Data Driven)
Opinion
Organizations must require analytical labeling to clarify data context
“We've got to kind of figure out analytical labeling, right? That it's, that's not accept enough, good enough for us to kind of accept information that's proffered to us without understanding how that information was produced, where that information came from, …”
Satyen Sangani May 24, 2017 ▶ 13:24 Fake News, Alternative Facts and the Enterprise // Satyen Sangani, Alation (FirstMark's Data Driven)
Opinion
The tech industry is far from using blockchain for enterprise data provenance
“I think we're far away from that because most of the tools have very different ways of manipulating data and very different ways of speaking to data.”
Satyen Sangani May 24, 2017 ▶ 20:18 Fake News, Alternative Facts and the Enterprise // Satyen Sangani, Alation (FirstMark's Data Driven)
Assertion Not checkable as stated
Legacy data warehouse projects historically took up to two years
“To stand up a business object's universe and cube in a Teradata warehouse, or a Netezza warehouse, or whatever warehouse could take anything on the order of two years, right?”
Satyen Sangani May 24, 2017 ▶ 6:17 Fake News, Alternative Facts and the Enterprise // Satyen Sangani, Alation (FirstMark's Data Driven)

The other half of the tape: Satyen Sangani's own voice is left out of every number here. Other people bring the name up 2 times in 1 episode on the MAD Podcast. every mention, with the transcript →

Who brings them up most Prat Moghe 2

Every mention by year

tap a year for its mentions
0011212017episodesmentions
0112017episodes it came up in
0010.5212017episodesmentions per episode
2017 2 mentions in 1 episode

Appearances (1)

EpisodeDateSpeaking time
Fake News, Alternative Facts and the Enterprise // Satyen Sangani, Alation (FirstMark's Da May 24, 2017 18m
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