In Conversation with Dave Burgess, Head of Data Engineering, Pinterest

Pinterest is near and dear to our hearts at FirstMark because we had the good fortune of being the first institutional investor back in 2009 when the company was just getting started (fun fact: the founders were in New York for a brief moment in time before moving to the Bay Area). Pinterest has had a remarkable ride ever since, and it’s a $49B market cap public company at the time of writing.

So it was a particular pleasure to welcome Dave Burgess, Head of Data Engineering, to come and talk to the Data Driven NYC audience about all things data at Pinterest.

We covered a bunch of interesting topics, including:

  • Pinterest’s newly open sourced project, QueryBook
  • The stack Pinterest uses to manage is 400 petabytes of data
  • The use cases for data analytics and machine learning at Pinterest

Below is the video and below that, the transcript.

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In conversation with Arjun Narayan, CEO, Materialize

Real-time data streaming is an increasingly crucial part of the data ecosystem. While financial services (trading) initially represented the bulk of the demand for streaming, the emergence of more mature technology in the space has unlocked more use cases, which in turn created more demand for better technology.

At a recent Data Driven NYC, we had a very interesting conversation with Arjun Narayan, CEO of Materialize, “the only true SQL streaming database for building internal tools, interactive dashboards, and customer-facing experiences”. Materialize is headquartered in New York and has raised $40M in venture capital money (with a new round rumored to be announced soon, at the time of writing).

This was a very educational discussion, where we covered the following topics:

  • What is streaming? What is Kakfa?
  • Why is there a need for a streaming database for analytics?
  • Why is SQL underrated?
  • What is Materialize?
  • Partnering with DBT to make streaming ubiquitous
  • Materializes’s roadmap

Below is the video and below that, the transcript.

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In conversation with Chip Huyen, Writer and Computer Scientist

At our most recent Data Driven, we had the great pleasure of hosting Chip Huyen, a writer and computer scientist who also teaches machine learning design at Stanford, for a fascinating and fun conversation.

We covered a range of topics, including:

  • What is machine learning design?
  • The MLOps landscape, and how it’s both overdeveloped and under-developed
  • What is online machine learning?
  • The divergence between East and West for machine learning and data infrastructure
  • A couple of book recommendations

Below is the video and below that, the transcript.

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In Conversation with Jack Hanlon, VP Data, Reddit

While it’s been around for 15+ years, Reddit has been on a tear lately: a $367M Series E round announced a few weeks ago, rumors of an IPO, and plenty of Internet action with r/wallstreetbets in particular.

Interestingly, there was a major gap for many years between the central role Reddit has been playing on the Internet and its relatively small team size. While companies like Facebook are largely AI companies (see our conversation with Jerome Pesenti, Head of AI, Facebook), Reddit’s data team was tiny.

Enter Jack Hanlon, VP Data at Reddit and our guest at our most recent Data Driven NYC event. Jack has been tasked with leading the data team into rapid growth, and we had a really interesting conversations, in particular around the following points:

  • How is the data team at Reddit organized? (preview: data science, data platform, machine learning, search)
  • What’s the data stack? (preview: switch from AWS to GCP, Kafka, Airflow, Colab, Amundsen, Great Expectations, Druid/Imply…)
  • What are the key use cases for data science and machine learning at Reddit?
  • A book recommendation: “Invisible Women: Data Bias in a World Designed for Men”

Anecdotally, Jack is our second speaker in recent memory who was a regular attendee in the early years of Data Driven NYC, before ascending to leadership responsibilities in a major Internet company! (the other being Alok Gupta, who spoke about leading data at DoorDash).

Below is the video and below that, the transcript.

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In conversation with Guy Podjarny, Founder & President, Snyk

In just a few years of hyper growth, Snyk has become a $2.7B unicorn, most recently raising $200M in September 2020. A developer-first security company, it has also helped usher the “DevSecOps” category.

At our most recent Data Driven NYC, we had the pleasure of hosting its Founder & President, Guy Podjarny, zooming in late at night from Israel.

We covered many interesting topics, including:

  • What does DevSecOps mean?
  • How did Snyk initially get developers to care, and how did they expand horizontally from there?
  • What is infrastructure as code?
  • Thoughts Snyk Code and Snyk’s vulnerability database
  • The nuances of combining a bottoms-up, freemium motion focused on developers, with an enterprise motion focused on economic buyers of Snyk’s products.

Below is the video and below that, the transcript.

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Introducing Kedro: Yetunde Dada, Principal Product Manager at QuantumBlack

If you follow the various talks at Data Driven NYC, and the data ecosystem on general, it’s plenty apparent that the overall tooling for data, data science and machine learning is still in its infancy, particularly compared to the software stack.

While this may feel ironic (yes, I really do think) given the billions in venture capital money that have been poured in the space, it’s worth remembering that the data stack (at least in its “big data” phase) is relatively recent (10-15 years), while the software stack has had several decades of evolution.

In many organizations, the data science and machine learning stack looks a collection of various tools, some open source, some proprietary, glued together with one-off scripts. Teams started experimenting with one tool, then another, then created ad hoc pathways to make it all work together over time, and before you knew it, you ended up with complex environments that are painful to manage.

In response to this situation, various machine learning frameworks have emerged to make abstract away the complexity. Several of those frameworks were developed internally at large tech comapanies to solve their own problems, and then open sourced.

Kedro is one such example. It was developed and maintained by QuantumBlack, an analytics consultancy acquired by McKinsey in 2015. It’s McKinsey’s first open-source product.

Kedro is somewhat hard to categorize. If it had its own category, it might be considered a Machine Learning Engineering Framework.  What React did for front-end engineering code is what Kedro does for machine learning code. It allows you to build “design systems” of reusable machine learning code.

At our most recent Data Driven NYC, we had the great pleasure of hosting Yetunde Dada, a Principal Product Manager at QuantumBlack, who has been the key driving force behind Kedro.

Below is the video and below that, the transcript.

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In conversation with Alok Gupta, Head Of Data Science & Machine Learning at DoorDash

Hosting Alok Gupta at our most recent Data Driven NYC was special for a couple of reasons.

First, because Alok is the very talented head of data science and machine learning in a company that has all sorts of really interesting use cases for AI and just had a phenomenal IPO, valuing it at $60B at the time of writing.

Second, because it was a homecoming of sorts for Alok, whose journey in the field of data science was inspired in part by Data Driven NYC – as he puts it:

This also feels like it nicely completes my journey starting 8 years ago when I was working on Wall Street in 2013 and started coming to your monthly evening talks at the Bloomberg building to learn more about ‘Data Science’. That was really a launching point for me to switch from trading to DS, and I’m grateful to be able to give back in a small way :).

One of those stories that brings joy to the heart of the organizers of this community!

Here are the video, as well as a full transcript for easy perusal:

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In Conversation with Tristan Handy (Fishtown/DBT) and Jeremiah Lowin (Prefect)

As we close an incredibly active year in the world of data infrastructure, it was a particular treat to host at Data Driven NYC two of the most thoughtful founders in the space, for an in-depth conversation about key trends.

Tristan Handy, is the Founder & CEO of Fishtown Analytics, makers of DBT. DBT is one of the most popular, open-source, command-line tools that enable data analysts and engineers to transform data in their warehouse more effectively. Based in Philadelphia, the company raised both a $12.9M Series A and a $29.5M Series B, back to back in 2020. Tristan also does a great weekly newsletter, The Data Science Roundup.

Jeremiah Lowin, Founder & CEO of Prefect. Prefect is the new standard in dataflow automation, trusted to build, run, and monitor millions of data workflows and pipelines. As another leader in the open-source world, Prefect powers data management for some of the most influential companies in the world.

We had a wide ranging conversation, covering lots of topics: the modern data stack, data lake vs data warehouse, empowering data analysts, workflow automation etc.

Video and full transcript below!

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In Conversation with Amit Bendov, CEO, Gong

It wasn’t a walk in the park. Today, Gong is a super hot company. But at that time, we got a lot of no’s, by not stupid people.  There were a lot of objections, like salespeople are going to hate it as a big brother, and Google and Amazon will compete with you“, says Amit Bendov, the CEO of Gong.

From those early days of facing skepticism, Gong has indeed become a hot startup loved by customers and ushering its own category, revenue intelligence. It’s also had tremendous fundraising success with VCs, raising $305M in less than 18 months, including a $200M round on a $2.2B valuation, announced in August 2020.

We were thrilled to welcome back Amit at Data Driven NYC, where he had spoken a few years ago, when he was CEO of SiSense.

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In Conversation with Ashley Kramer, CPO/CMO, Sisense

Sisense is a fast-growing business intelligence startup that was ranked #31 in this year’s Forbes Cloud 100, and reached unicorn status at the beginning of 2020 through a $100M Series D led by Insight Partners.

We’ve had Sisense speak twice at Data Driven NYC over the years, first CEO Amit Bendov (now CEO of Gong) (video of the talk here) and then new CEO Amit Orad (video of the talk here).

With all the recent progress, we were particularly excited to hear the update and welcome Ashley Kramer, who recently joined Sisense as Chief Product and Marketing Officer, after a very impressive run at Amazon, Tableau and Alteryx.

We covered a bunch of topics, including:

  • What does “Business Intelligence” actually mean?
  • The convergence of BI and data science
  • How does Sisense position in the context of the consolidation of the BI industry (hint: multi-cloud and focus on different personas, including business users, data analysts and more technical folks)
  • Where Sisense sits in the modern data stack
  • How Sisense has been building data network effects with its knowledge graph
  • Dashboards are great, but embedded analytics are better

As always, Data Driven NYC is a team effort – many thanks to Jack Cohen for co-organizing, Diego Guttierez for the video work and to Karissa Domondon for the transcript!

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In Conversation with David Cancel, CEO, Drift

David Cancel puts the “serial” in serial entrepreneur. David has founded a total of five software companies over the years, which he says make him “certifiable”. The list includes Performable, which was acquired by Hubspot, where David subsequently spent three years as Chief Product Officer.  

In 2015, David left Hubspot to start Drift, a Boston-based conversational AI platform for marketing and sales. The company has grown very rapidly and now has a whopping 50,000 customers. Drift has raised a total of $107M from a number of  venture firms including Sequoia, General Catalyst and CRV. The company has also been recognized as a Forbes Cloud 100 company.

David also has built a very strong presence and brand in the entrepreneurial community. He writes a popular newsletter, ‘The One Thing’ and hosts a long-running podcast, ‘Seeking Wisdom’. He’s very involved in a number of startups as advisor and angel investor. He’s also an Entrepreneur-in-Residence at Harvard Business School.

David and I had a really interesting, wide-encompassing conversation at our most recent Data Driven NYC event, where we covered a range of topics including:

  • Building a global SaaS brand with 50,000 customers in an astonishingly short amount of time
  • How Drift was founded to take advantage of a fundamental paradigm shift
  • Creating a new type of CRM, driven by conversational data, with automation at the core
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In Conversation with George Fraser, CEO, Fivetran

One of the biggest recent trends in the data world recently has been the rapid emergence of the “modern data stack”.

This stack is largely centered around the cloud data warehouse, with its massive scalability and elasticity capabilities. Snowflake’s blockbuster IPO this week, and the underlying performance of the company, demonstrate the level of excitement from both customers and investors about the data warehouse.

But the modern data stack is more than just the data warehouse, there’s a whole pipeline involving other technologies, where data gets collected, stored and analyzed. Downstream from the data warehouse, you find business intelligence solutions, as well as some machine learning platforms, to analyze the data. Upstream from it, you find solutions that focus on extracting data from various sources and loading it into the data warehouse (ETL/ELT).

This is where Fivetran comes in. A fast-growing company with a unicorn status, it automates data integration from source to destination, through a large library of connectors.

It was very fun to host Fivetran’s CEO, George Fraser, at our most recent Data Driven NYC event. We had a great conversation, both very approachable for a non-technical audience but also interesting for more technical folks.

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From Student Project to Unicorn: In Conversation with Alexander Rinke, CEO, Celonis

Celonis was founded in 2011 by three students who didn’t know they wanted to start a company, but fell in the love with a school project.

Today, Celonis is a Forbes Cloud 100 company, and the leader in a very interesting category, enterprise performance acceleration software, leveraging a company’s data exhaust to understand which processes work and which need to be be optimized, through process mining technology.

It’s also a unicorn startup with $367 million raised to date, most recently at a $2.5 billion valuation from investors such as Accel, 83North, our friends at Arena Holdings (who kindly introduced us to Alex) and Qualtrics founder Ryan Smith, who spoke at Data Driven NYC a few years ago, and then famously went on to sell his company, Qualtrics, to SAP for $8 billion.

We had a really fun chat at our most recent Data Driven NYC, with Celonis co-CEO Alexander Rinke:

  • How Celonis started as university consulting project when the founders were 21
  • How Alex waited several hours outside the VIP area of a tech event, until he was able to talk to the founder of SAP, which resulted in a transformative partnership
  • How the company was bootstrapped for 5 years before taking any VC money
  • What it takes for a startup to successfully expand internationally
  • What is process mining software and how does it work
  • Go to market strategies – horizontal vs vertical
  • And a lot more

Here’s the video, and below is a full transcript of the chat:

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In Conversation with Nate Stewart, Chief Product Officer, Cockroach Labs

While we miss the special energy of having 350+ people in a room every month, it’s been fun to settle into the routine of hosting the online version of Data Driven NYC — our 19,000 person community focused on all things data, AI/ML and enterprise software. Our events are free and open to all, and having them online has enabled many more folks around the world to attend them live – to the point that my co-organizer Jack Cohen and I have been mulling renaming the event “Data Driven Global”.

At the most recent event a few days ago, we had the pleasure of hosting Nate Stewart, Chief Product Officer, and newly appointed Board Member, at Cockroach Labs.

Cockroach is an exciting, fast-growing startup. Named to the 2020 “Future Unicorn” list by CB Insights and Fast Company, it is the company behind CockroachDB, a distributed database with standard SQL for cloud applications. The company has raised $195m to date, from a long list of great investors such as Benchmark, GV, Index, Redpoint, Altimeter, Tiger, Bond, Work Bench – and our firm FirstMark, since the very first round of funding.

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Facebook as an AI company: In conversation with Jerome Pesenti, VP of AI, Facebook

While AI may seem like a futuristic goal for most companies around the world, Facebook has already been there for a while. “There’s pretty much a deep learning system in every single Facebook product and they are very much at the core of them” says our guest Jerome Pesenti, VP of AI at Facebook.

Jerome leads the development of artificial intelligence at Facebook, and oversees hundreds of scientists and engineers whose work shapes the company’s direction and impacts our world.

We had had the pleasure of welcoming Jerome at Data Driven NYC in October 2017, in his prior role as CEO, BenevolentAI, and we had chatted about using AI for drug discovery.

It was wonderful to welcome him back in his new capacity at our first **online** Data Driven NYC, courtesy of the coronavirus. It was a fascinating, in-depth conversation.

Below are: a) the video, b) some highlights and c) the full transcript.