Satya Ramachandran

Director of Software Engineering, Intuit · 1 appearance on the record.

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

engineerexecutivefounder@satyar73 ↗LinkedIn ↗satyaramachandran.blogspot.com ↗

He specializes in enterprise marketing technology, large-scale distributed systems, and predictive decision-support architectures powered by AI and machine learning. Prior to Intuit, he co-founded jovianDATA, held engineering roles at Sybase and 3PARdata, and served as VP of Engineering at MarketShare and Neustar after MarketShare's acquisition.

9statements → 7claims → 1claims resolved → 4.11/5average certainty → 1.56/5average debate potential →

0 supported 1 partly supported 0 contradicted 6 not checkable as stated how the 7 claims stand · each chip opens the sources

7 assertions · 2 insights · every statement was checked. The predictions and assertions are the 7 claims: statements the public record can support or contradict. 1 is resolved, and 6 name 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 Satya 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? →

263 words/min while actually speaking · 50.7 um and uh per 1k words

No argument clarity score for Satya Ramachandran: 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: 3,351 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 →

What they said9 Episodes1

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

Assertion Partly supported

Neustar acquired MarketShare for $500 million in 2015

“About a couple of months back, we were acquired by Newstar for half a billion dollars.”

Satya Ramachandran Feb 21, 2016 ▶ 2:05 Large Scale Decision Support Systems // Satya Ramachandran, Neustar (Hosted by FirstMark Capital)

Insight

Engineering teams should never build custom technology that already exists

“One philosophy we have, ah, for the past year, ah, first five years building the system, what we have learned is to never build what's already there.”

Satya Ramachandran Feb 21, 2016 ▶ 12:37 Large Scale Decision Support Systems // Satya Ramachandran, Neustar (Hosted by FirstMark Capital)

Assertion Not checkable as stated

Most current business intelligence tools lack a real-time simulation engine

“And the second big focus, and this is where most of the current BI tools lack, is to provide that real-time simulation engine.”

Satya Ramachandran Feb 21, 2016 ▶ 14:33 Large Scale Decision Support Systems // Satya Ramachandran, Neustar (Hosted by FirstMark Capital)

Insight

Systems break at data management when attempting to productize analytics

“The most important lesson that we had learned in productizing, in analytics thing like that, is to have control on data management. I mean, data management is where it kind of breaks. As long as you have control on data management, the modeling piece becomes a…”

Satya Ramachandran Feb 21, 2016 ▶ 16:55 Large Scale Decision Support Systems // Satya Ramachandran, Neustar (Hosted by FirstMark Capital)

Assertion Not checkable as stated

Neustar served as the exclusive dynamic pricing agent for Ticketmaster

“So, so we're also doing price. So we basically, we have a pricing tool, also. Right now it's exclusively with Ticketmaster, where we are the dynamic pricing agent, we have Ticketmaster”

Satya Ramachandran Feb 21, 2016 ▶ 18:33 Large Scale Decision Support Systems // Satya Ramachandran, Neustar (Hosted by FirstMark Capital)

Assertion Not checkable as stated

Enterprise decision support systems still require heavy back-and-forth with modelers

“Today, even the best systems, you see, this involves a lot of back and forth between the business person and actually the back-end folks, which are the modelers and data scientists, right?”

Satya Ramachandran Feb 21, 2016 ▶ 3:24 Large Scale Decision Support Systems // Satya Ramachandran, Neustar (Hosted by FirstMark Capital)

Assertion Not checkable as stated

The analytics industry remains mostly limited to simple reporting

“We are still working on just doing reporting, pure reporting, or very simple, simple analysis as opposed to analysis like this.”

Satya Ramachandran Feb 21, 2016 ▶ 10:43 Large Scale Decision Support Systems // Satya Ramachandran, Neustar (Hosted by FirstMark Capital)

Assertion Not checkable as stated

MarketShare ran sub-second simulations on 4.5 billion data points in 2015

“And then in 2015 we worked with online data, about 4.5 billion data points Close to six hundred million possible variables in our model, and we can run these simulations in sub seconds.”

Satya Ramachandran Feb 21, 2016 ▶ 11:18 Large Scale Decision Support Systems // Satya Ramachandran, Neustar (Hosted by FirstMark Capital)

Assertion Not checkable as stated

Neustar maintained data partnerships with Facebook and Twitter for predictive analytics

“We have a partnership with Facebook. We have a partnership with Twitter also. We use their data, ah, to be able to run our analysis as such.”

Satya Ramachandran Feb 21, 2016 ▶ 19:59 Large Scale Decision Support Systems // Satya Ramachandran, Neustar (Hosted by FirstMark Capital)

Appearances (1)

Episode	Date	Speaking time
Large Scale Decision Support Systems // Satya Ramachandran, Neustar (Hosted by FirstMark C	Feb 21, 2016	17m

Satya Ramachandran

The record, in short

How they sound: speaking style how? →

Appearances (1)

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