Sigma Computing has taken a unique approach to making analytics more accessible to the masses.
In response, the investment community has taken notice, and in December 2021 the vendor, founded in 2014 and based in San Francisco, secured $300 million in venture capital funding co-led by D1 Capital Partners and XN with participation from Sutter Hill Ventures, Altimeter Capital and Snowflake Ventures.
Sigma Computing's Series C round represents a tenfold increase over its Series B round in November 2019.
Studies have shown that when employees are able to use data and given the freedom to make data-driven decisions, it spurs growth. But studies have also shown that only an estimated one-quarter to one-third of employees within most organizations actually use analytics as part of their jobs.
In response, vendors have taken different approaches to trying to make the use of analytics more widespread. Some have developed no-code/low-code platforms. Others have prioritized automatically generated data narratives that essentially offer explanations of data to end users.
But Sigma has taken a different tack, building a spreadsheet interface -- one many business users are familiar with -- on top of a sophisticated back-end platform that enables users to search and analyze data in a familiar environment without requiring them to know code.
It's an approach that has led to significant growth over the past couple of years, according to CEO Mike Palmer, and one that played a major role in helping the vendor attract substantial new funding.
Recently, Palmer discussed how Sigma Computing was able to attract investors and what the vendor plans to do with its newfound capital. In addition, he spoke about how Sigma has improved its platform over the past couple of years -- including introducing Workbooks in June 2021 -- and what the vendor has planned for the future
What does Sigma Computing aim to enable with its platform?
Mike Palmer: Business intelligence is a concept that is evolving, if not being revolutionized. It was so complicated to find data and present data that you had to have a specialty in it. We're moving to a world where the expectation for business performance is going to be predicated on using the best data the fastest. Companies that take multi-week decision cycles down to minutes are going to be the ones we're still talking about in five years.
The core of Sigma's mission is to enable users to directly engage with live data. We're coming from a world where we often have to work through a service center in order to ask and act on a question. We feel that, like all technologies that have evolved, technologies where experts are required to use them need to become simplified over time so we all become those experts, and we are very much on that mission for data.
In two years, Sigma Computing has gone from a $30 million funding round to a $300 million funding round. What led to that tenfold increase?
Mike PalmerCEO, Sigma Computing
Palmer: Product feedback is 100% the reason. We have some truly amazing customers, like DoorDash, which has a very committed data strategy, really requiring employees to directly engage with the data up to and including that they can write SQL. That they would choose Sigma was very relevant for our investors.
Investors are very good at looking at what the next five to 10 years are going to bring, and when you are winning the companies' business that are also looking five years into the future, that says a lot to them. It was all about the product feedback, the adoption rates and the growth we have inside our accounts. They also see us as not necessarily a replacement for the last 50 years of BI, but as a different type of engagement platform for companies that are looking to engage their data.
How does Sigma Computing plan to use the $300 million?
Palmer: We're all about product and engineering. We wake up every day, and the first thing we think about is how to hire more engineers and where to find those engineers. We have very interesting problems that we're trying to solve, whether it's manipulating data at huge scale or rendering simplicity in the user interface against a very complicated back end. We're also heavily invested in a research team that's invested in some machine learning-based technologies related to simplifying highly diverse data sets for end users. So for us, it's very much about the product.
Regarding the product, how is the Sigma Computing platform different than a traditional data and analytics platform?
Mike Palmer: I don't really think of Sigma as a BI platform. Sigma is a platform designed to enable a person with as little as spreadsheet skills to engage with billions of records of live data, be able to do that with the performance, scale and simplicity of a data warehouse, and through that engagement find the data that will help them do their job. It is the spreadsheet interface where they can type the formulas they know and love, where they create scenario models, where they can drill into data, they can build visualizations when they've come to some sort of conclusion, and where they can collaborate with others, whether that be in the spreadsheet itself, whether it includes adding narratives, or creating presentations.
The Workbook is really a platform where data analysis meets collaboration and what you would think of as the traditional business suite. And it's no-code, so a user can find tables and join those tables without having to know any SQL. You can do that directly in the interface, you can write formulas in a formula bar, and do all the other things you've been trained to do for the last 20 years, but you're now able to do them on 5 billion records if you want, in seconds.
There are other platforms that aim to enable self-service analytics, so how does Sigma Computing, as a startup, attempt to stand out from the crowd?
Palmer: Our core differentiator is the spreadsheet interface. I don't know anyone else in the market that's applying that billion-user market to the evolving cloud warehouse market.
One of the other things we'll be talking about in the next 60 days in the ability to input your own tables in Snowflake and input your own data there as well. This idea that you create spreadsheets because you want to input your own data, and because you want to build your own model, is not something BI has ever enabled you to do. BI has always been a read-only interface. But in Sigma, you can write comments, you can write narratives, you can do presentations, and you never have to leave the Workbook format, which means that this product becomes a vehicle to not just do work but take that work to be used.
That combination of live, at-scale data with a spreadsheet interface, done in a collaboration environment with the ability for you to do all of that with your own data and your own tables directly in the warehouse, is fairly unique.
Before this latest funding round of $300 million in December 2021, your previous funding round of $30 million was in 2019. How did the Sigma Computing platform evolve over those two years?
Palmer: In 2019, I think we were just at that early explosion for products like Snowflake, and products like Snowflake have brought a whole new demand to the marketplace enabling you to put together huge data sets of very different types in one place. While one of the core problems solved by Snowflake was infrastructure-oriented, the real revolution is going to come when end users who make decisions using that data can access it for the first time.
In 2019, we saw the beginning, and two years later what we have is a product that integrates seamlessly into the cloud data warehouses from a security permissions point of view and allows end users to visually build their own data sets. We have a product that is, for the first time, incorporating collaboration so you have a synergistic effect between departments, a platform that allows internal and external users to freely drill across all permissioned datasets and do that at super-high performance.
We've evolved the product to something that has not only been enriched from the point of view of the user interface, but we've also evolved it from a collaboration standpoint and performance standpoint.
Has that translated to the balance sheet?
Palmer: From a customer standpoint, you're seeing Fortune 500 companies adopt Sigma, and they're standing alongside cloud-native small and medium-sized business who are looking for the perfect SaaS cloud-based complement to their cloud data warehouse. Financially, we've tripled [revenues] over the last 12 months, and our customer base is up fourfold over the last 15 months.
Companies that are going to be great companies in the next five years are going to do that by being great with data. As they adopt the cloud, and as they adopt data warehouse products like Snowflake, they open new doors in their ability to use that data. They want to empower their employees, and the speed and accuracy of decision-making when you can use live data without intermediaries puts them in position to be better with data over these next five years.
You've mentioned Snowflake a couple of times. Does Sigma Computing have relationships with other cloud data warehouse providers as well?
Palmer: We are actively integrated with Databricks, and we have many customers on Google BigQuery and Amazon Redshift. We are agnostic when it comes to the cloud data warehousing marketplace. Each of these hyperscales have a different partnering strategy, but we view ourselves as an agnostic interface for our customers to use in the data warehouse that they choose.
Looking ahead, what does the roadmap look like for Sigma Computing?
Palmer: Two of the basic themes are speed and security. We are making sure that our customers can operate with any sized data volume and still get their answers back in seconds or less. We want our product to perform like their laptop performs. And we want our customers to know that data in the warehouse is better than data extracted from the warehouse.
We continue to make sure that the spreadsheet experience, from a usability standpoint, meets and beats customers' expectations. One of the key areas for this is inputting your own data. The reason you build a spreadsheet on your laptop is you want to input your own information -- you don't want to just filter information from a central system. You'll see us be among the first companies to enable you to build your own table in Snowflake as an end user and be able to build your own scenario models. This idea of a spreadsheet in the cloud data warehouse as a true replacement for one on your laptop is probably the major focus for us.
And it's really about collaboration. There isn't a product that moved from the data center to the cloud that left collaboration behind. BI used to be service center-driven with a centralized team creating something for user consumption, but we're moving toward a world where end users want to work together in real time by communicating, creating visualizations and building new spreadsheets. Collaboration is a major theme.
Editor's note: This Q&A has been edited for clarity and conciseness.