Founded in 2014 by Rob Woollen (Formerly CTO at Salesforce) and Jason Franz (MapR, Clustrix), Sigma is a startup that provides access to data directly, providing tools for businesses to gain a range of insights.
Sigmas’s cloud data analytics product originated out of the work Rob and Jason did as entrepreneurs in residence at Sutter Hill Ventures. Sigma Computing raised $30 Million in a momentum-driven finance round in November 2019, nearly four years after raising its $8 million seed round led by Sutter Hill Ventures. This round follows the B round with an infusion of cash from the same investors.
To gain an insight into how to run a pioneering tech startup, Digital Journal spoke with Rob Woollen CEO / Co-Founder of Sigma Computing.
Digital Journal: How important is data for businesses?
Rob Woollen: We live in an increasingly digital, data-driven world. No matter where you look—whether it’s our personal or professional lives—data helps people make better decisions about everything from product development to marketing campaigns and business strategy. Today’s most innovative companies have a strong backbone of data. Every click, transaction, and customer touchpoint provides insights. But if that data isn’t accessible, it’s not going to help employees make smarter decisions.
Businesses are stifling their most powerful competitive advantage by not granting everyone access to data and the ability to explore it on their own terms. IT and data teams need to understand that it is possible to give business leaders and domain experts access to data without giving up control or governance.
In fact, by not giving them access, they are actually increasing the chances, albeit inadvertently, that people will extract the data they need and analyze it on their desktops in a format they are comfortable with – a spreadsheet. Then they have certainly lost control and opened the company up to an array of potential security threats.
DJ: How can businesses best leverage data analytics?
Woollen: My team and I truly believe that data belongs in the hands of the domain experts and business leaders making the critical decisions. They shouldn’t have to rely on pre-built dashboards or predefined reports that were created by someone that doesn’t necessarily understand the intricacies and nuances of the line of business, campaign, or initiative.
We believe in providing teams with access to their company’s data and giving them the tools to explore it securely and safely. We give businesses a single source of truth that is easy for domain experts to navigate, via a spreadsheet-like interface, while simultaneously delivering the extensive security, governance, and control that companies need.
Controlled data exploration is undoubtedly the future of Analytics and Business Intelligence (A&BI), but any data and the insights derived from it, need to be accessible in real-time. Companies need to be able to make decisions quickly and they need to make decisions based on data from across their company. Just about everything today is time sensitive because the world is moving at such a rapid, always-on pace.
Real-time analytics means that you can immediately process and query new data as it is created to inform decisions in the moment and guide your business decision making. Unlike on-demand analytics, which waits for users or systems to request a query and then delivers the analytic results; continuous real-time analytics is more proactive and fit for purpose, alerting users or triggering responses as events happen.
DJ: How can data be used to develop predictive models?
Woollen:All that data coming in can be a treasure trove for your business, so you want a way to make the most of it. You’re also investing in collecting and storing it, so it makes sense to maximize the return on these investments. Whether you’re already using data modeling and want to improve the process to include more users, or whether you haven’t started due to the complexity of it all, a simpler data modeling solution can be the answer.
Organizations that are fueled by curiosity-driven insights are more likely to flourish in this era of self-service data cultures and technologies. Fortunately, tools have evolved to accommodate users of all kinds. Adopting such a tool and following data modeling best practices will allow the domain experts in your organization to capitalize on your data.
DJ: How important are cloud solutions?
Woollen:Most analytics solutions on the market already offer some sort of cloud version. The problem with these hybrid solutions is that they are not really made to analyze data in cloud data warehouses. Cloud-built analytics solutions offer unique real-time data access and information sharing within an organization.
The cloud provides the infrastructure necessary to handle large volumes of data that is also changing rapidly. Sigma doesn’t just add value to what real-time business intelligence has to offer; Sigma, in conjunction with the rest of the cloud analytics stack, makes real-time A&BI actually possible, because it enables business leaders and domain experts to explore and analyze that data faster.
Cloud analytics tools help businesses in many ways. First, they tap into data from a cloud warehouse without ever removing the data, so all relevant information is available to those who need it. Next, modern analytics tools are built with the needs of different users in mind. Spreadsheet-like interfaces along with drag-and-drop components allow anyone to conduct advanced queries without writing code. Security risks are reduced because a cloud analytics tool connects directly to the cloud data warehouse. There is no additional router that stores data and moves it from one place to another. Finally, because all of this analysis can be done in a browser, there is no need to save data locally. Cloud analytics tools like Sigma eliminate the need to download spreadsheet files to local PCs or email documents. Every worksheet can be accessed in Sigma and shared in team workspaces.
DJ: What is the Sigma technology?
Woollen:Sigma is a cloud A&BI solution with a spreadsheet-like interface, which makes it easy for a wide spectrum of business users, analysts, and data scientists to all use the same tool to query data because no code is required. SQL is automatically generated for any actions taken in the Sigma Spreadsheet. Of course, if someone does know SQL, they are still able to query the warehouse using SQL if that’s their preference.
This increased access to data and ability for anyone to analyze it, especially by the lines of business users that have the questions, eliminates the bottleneck caused by ad hoc queries, rescues the data team from report factory hell, and accelerates time to insight. The Sigma Spreadsheet also allows the business intelligence process to be iterative because you don’t have to go back and change the data model when you want to explore a new path.
While we believe that more people should have access to data and the freedom to explore it, we also know that extensive security, governance, and control is critical. Data teams need to be able to ensure that everything within the cloud data warehouse, and by extension within Sigma, is correct and create a single source of truth of data for the entire company. This is all possible in Sigma. Essentially, we want to balance openness with security, providing controlled data exploration.
DJ: How does your technology differ from your competitors?
Woollen:Legacy A&BI tools require coding experts to deliver insights to the many, which creates an organizational chokepoint that drives lines of business leaders to export data into Excel so they can do their own analysis and discovery. This causes governance issues, security breaches, data inaccuracies, and information silos.
Conversely, Sigma eliminates the need for static, vulnerable Excel extracts because the Sigma Spreadsheet is inspired by the same familiar interface that knowledge workers have been using for decades so it’s easy for them to jump right into the data conversation. Sigma also enables teams to multiply intelligence by supporting real-time collaboration and the ability to build off one another’s work, which helps accelerate time to insight because you don’t have to recreate the wheel.
Finally, Sigma was built for the cloud from the start – not reverse engineered, like so many other A&BI options out there. Sigma seamlessly sits on top of your cloud data warehouse, which means that your data never actually leaves the warehouse and additional security vulnerabilities are never even introduced. Sigma really helps you get the most out of your data cloud data warehouse investment.
DJ: Are there any case studies you can share of businesses using Sigma?
Woollen:We have an impressive and rapidly growing list of customers, including Volta Charging, Blue Bottle, Zumper, Fictiv, and Olivela, who are all using Sigma to quickly and accurately solve their biggest data challenges.
Each of our customers’ stories and use cases are pretty unique, but one thing all of our customers have in common is that they came to the realization that they can no longer take the ‘Ivory Tower’ approach to their A&BI. They discovered that a siloed model is not scalable and would likely contribute to their demise – or at least a significant loss in potential revenue. It wasn’t realistic for them to expect everyone at their company to learn SQL, so they could run their own queries in a traditional A&BI tool, nor was it safe to do that from a security, governance, and compliance standpoint.
For such a longtime, BI was focused on the traditional lines of business: finance, sales, marketing, and supply chain. Indeed, this is a big focus for our solution as well. But we are seeing interesting new use cases, some of which simply weren’t achievable in the past because the data was too large and BI solutions too arduous. One such use case is security analytics leveraging Sigma to identify and diagnose security threats on massive amounts of data.
We also have clients using Sigma to process claims and align this data with other third party sources for 360 degree insights. Our customers and prospects are demanding more as they leverage data at scale with Snowflake and other cloud data warehouses.
The future is bright as compute power continues to grow, allowing Sigma to demystify massive amounts of data and insights. This is driving better business decisions by empowering the domain experts to do their own analysis securely, easily, and quickly themselves.
Volta Charging is a great example of Sigma working in practice and I’m sure that they would agree that Sigma transformed Volta’s BI capabilities. When they came to use they were awash with data, and their team turned to us to close the gap between their data experts and their business experts. Their challenge was probing all their various data sources to gain insights from that data, without knowing beforehand exactly what they were looking for.
Volta had all the necessary information, but finding the data and then putting it in a digestible form was painstakingly slow. Queries had to be submitted to engineers, and those engineers then had to write code to transform the data before delivering a report. Any slight change required an entirely new query, which involved more coding, time and labor for the engineers.
Domain experts at Volta now have easy access to the data they need across all their data sources and the ability to discover answers to their questions and explore new questions as they arise and on their own terms. An iterative BI process is easy with Sigma because users can add new logic to their explorations at any point, even at the end of a deep dive analysis, without retracing their steps. Last, but not least: Since deploying Sigma, Volta has reduced the time it takes for engineers to do standard weekly reporting by 90% because they are now able to automate reports that previously had to be created by hand each week.
