Differentiation key as Sigma Computing raises $200M
The vendor's attempt to broaden BI use within organizations with a no-code spreadsheet interface helps its tools feel familiar while enabling deep data exploration.
Sigma Computing closed on $200 million in venture capital financing, bringing the vendor's total funding to $581.3 million.
Spark Capital and Avenir Growth Capital co-led the Series D funding round, revealed on May 16, with additional participation from a group of past investors including Snowflake Ventures and Sutter Hill Ventures.
Based in San Francisco, Sigma Computing is a cloud-based analytics vendor whose tools aim to help widespread use of analytics within organizations by enabling users to query and analyze data without writing code. Its spreadsheet interface provides users with a familiar format similar to that of Microsoft Excel or Google Sheets, but unlike those tools was built on top of a sophisticated back-end platform that enables deep exploration.
Since launching with its unique interface, Sigma Computing has added features such as collaboration tools and embedded analytics capabilities. Most recently, the vendor's spring 2024 product launch included a set of AI tools such as forecasting capabilities, an AI copilot and a notebook interface for users who prefer a code-first environment.
That evolution -- along with close ties to data cloud vendor Snowflake as evidenced by Snowflake Ventures' continued investment in Sigma Computing -- has led to growth, said Wayne Eckerson, founder and analyst at Eckerson Group.
Growth, meanwhile, helped Sigma Computing attract new investor capital despite a difficult funding environment for technology vendors over the past two years.
"Sigma has ridden the growth of Snowflake, and its spreadsheet interface -- always popular with many business users -- has now been supplemented with a notebook interface for writing SQL and Python," Eckerson said. "So, [Sigma] is not standing still."
Sigma Computing's Series D funding round comes after the vendor raised $300 million in Series C funding in December 2021 when venture capital funding was easier to attract.
Finding funding
With capital markets rising steadily for more than a decade, data volume exploding and analytics gaining popularity as more enterprises recognized the need for advanced analysis to inform decisions, funding was plentiful for data management and analytics vendors to find through late 2021.
Late that year and in early 2022, however, events conspired to create uncertainty for investors. The stock market dipped, fears of a recession rose, tech layoffs multiplied and worldwide events such as the ongoing COVID-19 pandemic, repeated supply chain problems and the war in Ukraine all combined to make investors wary.
In 2021 alone, Aiven, Confluent, Databricks, Reltio, Sigma Computing, SnapLogic, ThoughtSpot and TigerGraph were among data management and analytics vendors that raised $100 million or more. Databricks, in fact, raised $1 billion in a single funding round and Confluent's was over $800 million.
During the next two years, however, such funding rounds were rarer.
Among data management and analytics vendors, only exceptions such as Databricks and Denodo proved able to raise more than $100 million.
Simultaneously, the climate for IPOs dried up. Vendors such as Qlik, SAS and ThoughtSpot that had publicly discussed plans to go public all put those plans on hold; none has yet conducted its initial public stock offering.
Aerospike raised $114 million in April, and Ocient and Coalesce each raised about $50 million in funding this year. Now Sigma Computing joins them by raising $200 million in a move that shows investors support the vendor's spreadsheet interface as a means of broadening BI adoption within organizations, according to David Menninger, an analyst at ISG's Venata Research.
Recent venture capitalist investments in data management and analytics have tended to go to vendors focusing on generative AI to make data easier to use, he noted. Sigma Computing has the same goal but is taking a different approach.
"If you look at the trends behind generative AI, it may shed some light on what investors might see in Sigma," Meninger said. "Enterprises still struggle getting analytics into the hands of the majority of their workforce. Generative AI is one way to address that issue. Sigma's cloud-based, familiar spreadsheet-style interface is another."
Donald Farmer, founder and principal of TreeHive Strategy, similarly said the funding is a signal that Sigma Computing is doing well.
"Their focus on collaborative analytics … is an important alternative take on traditional BI," Farmer said.
Beyond differentiation, Sigma Computing revenue growth was a factor in attracting the new funding, according to Mike Palmer, the vendor's CEO.
Sigma Computing remains privately held so does not publicize its financial statements. But Palmer said the vendor has posted significant growth over the past four years. In addition, customer feedback played a critical role in demonstrating Sigma Computing's worth to venture capitalists, according to Palmer.
"While [customer sentiment] shows up in … gross and net retention rates, it is felt most viscerally in the words they use to describe [the] value we provide on top of their cloud data transformation," he said.
Capital plans
In its early years, Sigma Computing tended to develop new tools one at a time.
For example, in 2020 the vendor added a tool that enabled in-data warehouse editing and in 2022 boosted its collaboration capabilities with a new feature.
Now, as evidenced by a spring 2024 product launch that not only included multiple tools but also different types of capabilities such as AI and embedded analytics, Sigma Computing is developing new features at a faster pace.
Part of the vendor's Series D funding will be used to continue adding new features and improving existing ones, according to Palmer.
Specifically, the vendor will use some of the funding to develop and improve tools features that address AI and machine learning, workflow automation, data application development, collaboration and user adoption.
Global expansion is another focus, Palmer continued, noting that Sigma Computing launched operations in Europe, the Middle East, and Africa about six months ago.
Enterprises still struggle getting analytics into the hands of the majority of their workforce. Generative AI is one way to address that issue. Sigma's cloud-based, familiar spreadsheet-style interface is another.
David MenningerAnalyst, ISG's Ventana Research
Using some of the funding to expand product development is an intelligent use of the new capital, according to Menninger.
Although Sigma Computing has produced capabilities that have garnered the respect of the investment community and helped the vendor grow since being founded in 2014, its platform is not as full-featured as more established analytics vendors such as MicroStrategy, Qlik and Tableau.
Sigma Computing's spring 2024 product launch was a move toward being more full featured but the vendor still lacks some of the broad analytics functionality of competitors that have had more time to develop their platforms.
"To be competitive, they will need to add more product features as they did this spring when they added more AI capabilities," Menninger said. "It's a competitive market and enterprises have come to expect many features in business intelligence products, ranging from all varieties of visualizations to automatically generated insights."
Beyond product development, Sigma Computing would be wise to invest some of the funding in sales and marketing, according to Menninger.
Integrations with not only Snowflake but also vendors such as Alation, AWS, Databricks and Google show that the vendor's platform is known by peers. However, Sigma Computing has not yet been included in analyst reports such as the Gartner Magic Quadrant or Forrester Wave and doesn't have the brand recognition of more established vendors.
"For any company at this stage, sales and marketing resources are critical," Menninger said. "They need to fight to get attention among a crowded field filled with many large and established software providers."
Eckerson similarly suggested Sigma Computing should use the new funding to expand sales and marketing efforts to make the vendor's brand more well known.
In addition, geographic expansion is good use of the funding, he said.
Looking forward
After unveiling its AI toolkit as part of the spring 2024 product launch, Sigma Computing's roadmap includes adding new capabilities that enable customers to use traditional AI as well as generative AI to inform decisions, according to Palmer.
Initial toolkit capabilities included Sigma Copilot, AI Forecasting in Sigma for Snowflake Customers and AI Functions to enable administrators to govern use of AI.
"Weill keep adding to the AI toolkit as AI use cases evolve within the data space," Palmer said.
Menninger, meanwhile, said that just as Sigma Computing has been able to differentiate itself from other analytics vendors with its spreadsheet interface, the vendor must also continue adding core features that more established vendors already have as part of their platforms.
"It's always good to see a vendor taking a different approach than others," he said.
But there have been many vendors through the years that have developed innovative capabilities, he continued. To truly compete as a standalone analytics platform that doesn't require customers to use a second platform as a complement, innovators also need to have basic features that enable self-service use.
Menninger noted that he was once in attendance at a vendor's user conference and the audience applauded when color-coding values -- which has been available for 20 years in other platforms -- were unveiled as part of the vendor's product line.
"Because it is such a competitive market, they will need to build out a number of features other products have to try to retain their differentiation," Menninger said. "We've seen this over and over again as new vendors capture market attention."
Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.
