In the world of data infrastructure, dbt Labs has undoubtedly been one of the most exciting startups to watch. The company is the creator and maintainer of dbt, a data transformation tool that enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Beyond this, the company is empowering a new generation of data analysts and enabling them to create and disseminate organizational knowledge.
dbt’s CEO, Tristan Handy, is also one of the most thoughtful and interesting CEOs in the space, having played a pivotal role in the emergence of what’s often referred to as the “Modern Data Stack”, a suite of tools and processes that leverage the power of cloud data warehouses to bring data processing to the modern era.
We had the pleasure of hosting Tristan once during the pandemic in 2021 for a greatonlinechat with Jeremiah Lowin, CEO of Prefect. It was a particular treat to welcome back Tristan, this time for our first in-person event since 2020!
As enterprises around the world deploy machine learning and AI in actual production, it’s becoming increasingly critical that AI can be trusted to produce not just accurate, but also fair and ethical results. An interesting market opportunity has opened up to equip enterprises with the tools to address those issues.
At our most recent Data Driven NYC, we had a great chat with Krishna Gade, co-founder and CEO of Fiddler, a platform to “monitor, observe, analyze and explain your machine learning models in production with an overall mission to make AI trustworthy for all enterprises”. Fiddler has aised $45 million in venture capital to date, most recently a $32 million Series B just last year in 2021.
We got a chance to cover some great topics, including:
What does “explainability” mean, in the context of ML/AI? What is “bias detection”?
What are some examples of business impact of “models gone bad”?
A dive into the Fiddler product and how it addresses the above?
Where are we in the cycle of actually deploying ML/AI in the enterprise? What’s the actual state of the market?
In the ever vibrant world of the “Modern Data Stack” (an ecosystem of mostly young tech startups that represent the rising generation of data software vendors, and integrate well with one another), Hex has been getting increasing visibility and momentum. At its core, Hex is a collaborative data platform where teams can explore, analyze, and share. It aims to bring together the best of notebooks, BI & docs into a seamless, collaborative UI.
The company was founded in 2019 and you raised a total of $73.5 million in venture capital to date, including most recently a $52 million Series B.
CEO Barry McCardel joined us at Data Driven NYC for a deep dive in to the product, the company, the data space and his journey from doing “unholy things in Excel” as a young consultant to building a great startup.
Meltem is one of the most visible and most thoughtful personalities in the crypto / web3 world and it was a real pleasure to welcome her at Crypto Driven.
In addition to running her always entertaining Twitter account, Meltem is Chief Strategy Officer of CoinShares, a digital asset investment firm that manages $4B in assets on behalf of a global client base. She previously played a senior strategic and investing role at Digital Currency Group (in which my firm FirstMark is a proud investor).
We covered some great topics including:
The three phases of evolution of the crypto market
How crypto is impacting culture
Why Bitcoin has a unique place in the pantheon of crypto currencies
Why Meltem is a shitcoin minimalist
Why Meltem is excited about BitFi (DeFi on top of bitcoin)
Are we witnessing a major VC pullback? Is it temporary? What does that mean for startups? Certainly the topic du jour in startup circles.
Here’s what I’m seeing.
IS THE PULLBACK REAL?
Yes. The market is a bit all over the place, not everyone fully agrees on what’s happening, and certainly a number of financings are still taking place. But the pullback is real and already starting to show in the data (CB Insights Q1’22 report).
My sense is that the current reality of the market is a lot worse, because deal data is a trailing indicator – financings are often announced months after they closed.
We’ve rapidly, perhaps brutally, transitioned from a hyper frothy VC environment to a world where many deals are not getting done.
As more and more companies around the world rely on data for competitive advantage and mission-critical needs, the stakes have increased tremendously, and data infrastructure needs to be utterly reliable.
In the applications world, the need to monitor and maintain infrastructure gave rise to an entire industry, and iconic leaders like Datadog. Who will be the Datadog of the data infrastructure world? A handful of data startups have thrown their hat in the ring, and Monte Carlo is certainly one of the most notable companies in that group.
Monte Carlo presents itself as an end-to-end dataobservability platform that aims to increases trust in data by eliminating data downtime, so engineers innovate more and fix less. Started in 2019, the company has already raised $101M in venture capital, most recently in a Series C announced in August 2021.
It was a real pleasure to welcome Monte Carlo’s co-founder and CEO, Barr Moses, for a fun and educational conversation about data observavibility and the data infrastructure world in general.
Chainalysis has been been playing a key role in the crypto ecosystem. As the leader in the blockchain data and intelligence market, it’s made it easier for many financial and government institutions to feel more comfortable with the space.
Chainalysis has been growing fast, having raised $360 million of venture capital to date, including most recently in Series E at $4.2 billion valuation.Before founding Chainalysis, he was the COO of Payward, the leading Euro to Bitcoin exchange. Importantly he was also a co-founder of the crypto exchange, Kraken, in San Francisco. He holds a PhD in quantum mechanics, no big deal.
Our business lives are full of optimization problems – scheduling, time management, resource planning, pricing, routing, risk management, network optimization, financial engineering, etc. Simply defined, optimization is the science of making the best decision possible, given a set of constraints.
Historically, optimization has been the province of PhDs with deep backgrounds in mathematics, using a generation of software that was developed for academia and large defense contractors.
Enter Nextmv (proncounded “Next Move”), a company in which I’m a proud investor. Nextmv is reinventing the space for the cloud era, making optimization and simulation technologies available to every developer.
It was great to welcome Nextmv’s CEO, Carolyn Mooney, at our most recent Data Driven NYC to talk abotu the space and the company.
What is decision intelligence, and how does it differ from business intelligence and data science?
What is the overlap with the area known as “operations research”?
How decision intelligence is broadly horizontal area
How Nextmv is democratizing decision intelligence with its cloud product
Bonus: Nextmv’s policy of radical transparency on team compensation
The world of data governance is not the most visible part of the data revolution, yet it is of critical importance. As more and more data floats into the enterprise, and its role is ever more mission critical, one needs to be in full control of it – understand where data resides, who can have access to it, which datasets can be trusted or not, etc.
Enter Collibra, a startup that has had a long march towards success, as it was founded in 2008. Collibra has now become an impressive industry leader and raised a $250 million Series G at a post money valuation of $5.25 billion last year.
We had had the chance to host Stan Christiaens, the co-founder and CTO of Collibra at Data Driven NYC in 2017 (video here), and this time we got a chance to chat with the company’s CEO, Felix Van de Maele.
We had a great conversation, starting with a round of definitions that should be interesting to anyone curious to better understand that side of the data world.
In a crypto industry that outsiders often like to criticize for its supposed lack of clear use cases, Helium stands out. The New York Times recently recognized this reality in a recent article, saying “Maybe There’s a Use for Crypto After All.”
Helium is a decentralized wireless network, powered by cryptocurrency. Mostly focused on powering “internet of things” devices for now, it’s been rapidly evolving towards 5G.
The Helium network has experienced remarkable success over the last few years – it’s built a global network of almost 670,000 hotspots deployed around the world (see discussion to understand more about hotspots).
As most “overnight successes”, however, Helium has been many years in the making. I’ve had the honor of being part of (almost) the whole journey, as I wrote on behalf of FirstMark the first institutional check into the company back in 2013 (what would be known today as a pre-seed), and reinvested a number of times since.
Along the way, we’ve had Helium speak at our FirstMark events several times, which is a fun reminder of the journey: then CTO Sean Carey in 2014 (here), and CEO Amir Haleem in 2017 (here) and 2018 (here).
So it was great to welcome Amir back once again to chat about the latest.
For all the excitement about the explosive pace of progress in AI and technology that many readers of this blog will share, there’s an undeniable feeling of uneasiness: things are perhaps moving too fast and having second order effects across society that we are just beginning to truly appreciate.
The Exponential Age is one of the best books I’ve read in a while. It’s a bold exploration and call-to-arms over the widening gap between AI, automation, big data and other emerging technologies, on the one hand, and our ability to deal with their impact, on the other hand. Those technologies are growing at an exponential pace but our society is not. This “exponential gap” explains many problems of our time – from political polarization to ballooning inequality to unchecked corporate power.
It was a real pleasure to host at our most recent Data Driven event its excellent author, Azeem Azhar, an entrepreneur, investor, renowned technology analyst and host of the global tech podcast Exponential View.
The last couple of years have seen a dramatic acceleration in the adoption of graph databases, a category of databases that stores nodes and relationships instead of tables, or documents. That acceleration has clearly benefited Neo4j, which had a banner year in 2021, surpassing $100M in ARR and closing a $325M series F financing round at over $2B valuation, which it calls “the largest funding round in database history”.
That would make Neo4j an overnight success, except for the fact that Neo4j started in 20007, pioneered the space and literally coined the term “graph database”.
Neo4j’s CEO, Emil Eifrem, had spoken at Data Driven NYC back in 2015 (the same night as the CEO of Snowflake and the CEO of Airtable, a pretty stacked line up considering those three startups combined went on to represent many billions of market cap/valuations).
So it was particularly fun to have Emil back at the event and exciting to hear about the major progress the company has experienced over the last few years. Emil spoke from Sweden at around midnight his time, bringing impressive energy despite the late hour and it was a great conversation.