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Neha Narkhede

Co-founder & CEO, Oscilar · 1 appearance on the record.

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

founderexecutiveengineerinvestorauthor@nehanarkhede ↗LinkedIn ↗nehanarkhede.com ↗Wikipedia ↗

She co-created the open-source event-streaming platform Apache Kafka at LinkedIn and co-founded Confluent, where she served as CTO and CPO. She is currently the co-founder and CEO of Oscilar, an AI-powered fraud prevention and risk decisioning platform, and actively invests in startups.

9statements → 4claims → 2claims resolved → 4.44/5average certainty → 2.22/5average debate potential → 1said about them ↓

2 supported 0 partly supported 0 contradicted 2 not checkable as stated how the 4 claims stand · each chip opens the sources

4 assertions · 2 opinions · 3 insights · every statement was checked. The predictions and assertions are the 4 claims: statements the public record can support or contradict. 2 are resolved, and 2 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 Neha argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable supported claim

Assertion Supported
Narkhede: Apache Kafka powers over 1.2 trillion written messages daily at LinkedIn
“You know, Kafka powers more than, ah, 1.2 trillion messages, ah, written per day. It is, ah, it powers more than 3.4 trillion, ah, messages, ah, read per day. All that amounts to more than one petabyte of streaming data. And that is across thousands of produce…”
Neha Narkhede Jun 16, 2016 ▶ 9:48 A Kafka-Powered Real-Time Streaming Platform // Neha Narkhede, Confluent [FirstMark's Data Driven]

How they sound: speaking style how? →

217 words/min while actually speaking · 50.1 um and uh per 1k words

No argument clarity score for Neha Narkhede: 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: 3,889 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 Neha Narkhede said on the MAD Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Opinion
Narkhede: Central streaming platforms like Kafka replace legacy enterprise service buses
“Fundamentally, companies want to collect all sorts of data, and there isn't just a database and a warehouse anymore. There are lots and lots of distributed systems, which means that we need to move to a sort of platform-centric approach, and this will, this is…”
Neha Narkhede Jun 16, 2016 ▶ 20:23 A Kafka-Powered Real-Time Streaming Platform // Neha Narkhede, Confluent [FirstMark's Data Driven]
Insight
Narkhede: Stream processing behaves like microservices, not faster MapReduce jobs
“What we learned is that, ah, stream processing is in fact much more than a faster MapReduce layer. It, in fact, most of the applications that do stream processing look much more like a microservice of an application, and less like a faster version of a batch o…”
Neha Narkhede Jun 16, 2016 ▶ 24:16 A Kafka-Powered Real-Time Streaming Platform // Neha Narkhede, Confluent [FirstMark's Data Driven]
Insight
Neha Narkhede: All enterprise data can be represented as event streams
“My bold claim here is that all your data can be represented as event streams.”
Neha Narkhede Jun 16, 2016 ▶ 3:04 A Kafka-Powered Real-Time Streaming Platform // Neha Narkhede, Confluent [FirstMark's Data Driven]
Opinion
Narkhede: Non-Kafka stream processing systems are complex and limited to niche problems
“Kafka Streams is, Extremely powerful, but very simple because it builds on top of primitives in Kafka. A lot of other systems are powerful, but, ah, not so simple. They're only applicable to a niche set of problems.”
Neha Narkhede Jun 16, 2016 ▶ 15:16 A Kafka-Powered Real-Time Streaming Platform // Neha Narkhede, Confluent [FirstMark's Data Driven]
Assertion Not checkable as stated
Narkhede: Companies are shifting from batch processing to real-time data
“A lot of companies are making a fundamental shift towards leveraging data in real-time, and moving away from that style computing Ah, which is essentially once a day data processing.”
Neha Narkhede Jun 16, 2016 ▶ 0:49 A Kafka-Powered Real-Time Streaming Platform // Neha Narkhede, Confluent [FirstMark's Data Driven]
Insight
Neha Narkhede: Stream processing generalizes request-response and batch paradigms
“Stream processing is often thought about as something that is just real time in nature, but it is really a generalization of these two extremes, request, response, and batch.”
Neha Narkhede Jun 16, 2016 ▶ 14:17 A Kafka-Powered Real-Time Streaming Platform // Neha Narkhede, Confluent [FirstMark's Data Driven]
Assertion Not checkable as stated
Narkhede: Banks are leading non-tech enterprise adoption of Apache Kafka
“In fact, banks is are definitely leading the way in terms of putting Kafka To you know, very sort of ambitious applications.”
Neha Narkhede Jun 16, 2016 ▶ 19:10 A Kafka-Powered Real-Time Streaming Platform // Neha Narkhede, Confluent [FirstMark's Data Driven]
Assertion Supported
Narkhede: Apache Kafka powers over 1.2 trillion written messages daily at LinkedIn
“You know, Kafka powers more than, ah, 1.2 trillion messages, ah, written per day. It is, ah, it powers more than 3.4 trillion, ah, messages, ah, read per day. All that amounts to more than one petabyte of streaming data. And that is across thousands of produce…”
Neha Narkhede Jun 16, 2016 ▶ 9:48 A Kafka-Powered Real-Time Streaming Platform // Neha Narkhede, Confluent [FirstMark's Data Driven]
Assertion Supported
Narkhede: Apache Kafka is used by thousands of companies worldwide
“Since we open sourced it, you know, roughly five years ago, Kafka is used in thousands of companies worldwide, from Uber, and LinkedIn, and Netflix, all the way to traditional enterprises like eBay, and PayPal, and Cisco, and Goldman Sachs.”
Neha Narkhede Jun 16, 2016 ▶ 10:13 A Kafka-Powered Real-Time Streaming Platform // Neha Narkhede, Confluent [FirstMark's Data Driven]

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

Who brings them up most Mike Volpi 1

Every mention by year

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2019 1 mention in 1 episode

Appearances (1)

EpisodeDateSpeaking time
A Kafka-Powered Real-Time Streaming Platform // Neha Narkhede, Confluent [FirstMark's Data Jun 16, 2016 20m
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