Enso exits stealth with $16.5M funding to help everyone do complex data analysis

Enso is exiting stealth mode today on a mission to democratize data analysis and help business users to run complex analytics processes without relying on experienced data scientists.

The startup said today it has raised $16.5 million in funding from investors including SignalFire, Khosla Ventures, Day One Ventures, Decacorn Capital, Y Combinator, Samsung Next, Harvard’s Endowment, West Coast Endeavors and Innovation Nest in order to make that happen.

Enso, which is officially known as New Byte Order Inc., has created an open-source platform that makes it possible to conduct advanced data analysis simply by connecting visual components. The company believes it will be a big hit with office workers because, until now, it says data analysis remains a bridge too far for many of them.

Advanced analysis generally requires expert data scientists to spend hours of time organizing and preparing datasets for use. But data scientists are in short supply and compounding this problem is that companies today are generating more data than ever before. So there simply aren’t enough data scientists and data engineers to keep up, Enso says.

Data analysis is a struggle anyway with cumbersome tools such as Excel. Enso said data scientists are forced to spend up to 20% of their time manually updating spreadsheets every time a dataset input changes, just to be able to do their jobs. Spreadsheets are fragile too, often breaking with the slightest change in data input format.

These are the problems Enso says it can solve with its automated and open-source approach to easier data analysis. Its platform works by using components that process data and output the results. So one component might consume data on advertising billboard locations across a city, while another will filter out only those ads placed near bus stops and make that data available as a rendered map of the city.

Enso’s platform analyzes all of these components together and visualizes it in a way that’s easy to understand and suggests next steps. Users can then dig inside their live data and modify things by mapping visual components as opposed to writing code.

Enso Chief Executive and Chief Technology Officer Wojciech Danilo said that in its current iteration, some coding skills are still required to make the most of Enso. He explained that Enso has three main components — the Engine, the user interface and cloud services — and that so far the team has been focused on building the actual engine. However, the plan is to launch a commercial-ready version of Enso early next year that will deliver on the company’s goal of making data analysis available to anyone.

That version will have a “much more user-friendly interface that will not require you to understand coding or scripting,” Danilo said. “Instead of writing expressions on nodes, you will be presented with interactive widgets — buttons, sliders, drop-down menus — that would allow you to define the workflow with no coding at all.”

Analyst Holger Mueller of Constellation Research Inc. said Enso can be thought of as a kind of visual programming tool and that it has the potential to cater to a large audience of people who are visual learners. “Many people prefer to express themselves visually, so it’s good to see Enso catering to that and moving demanding data preparation and processing tasks to a visual programming-based platform,” he said.

Danilo explained that he and his co-founder Sylwia Brodacka spent eight years working alongside each other, assisting clients with data processing in the visual effects industry.

“When my co-founder, Sylwia, and I were in our previous roles helping VFX artists process data, we were repeatedly asked by companies in other industries if it was possible to use our tools for their data,” he said. “It became clear to us that there existed a severe pain point, largely driven by the shortage of data scientists.”

Enso says it will alleviate that pain point, making data analysis so accessible that businesses will be able to reduce their reliance on data scientists.

“The founders’ background in visual effects data processing helped them to make Enso so intuitive,” said SignalFire Partner Oana Olteanu. “I believe there is a large group of nontechnical users who can benefit from accessing the data analysis and visualization capability that was traditionally limited to data scientists and analysts.”

Read more at: https://siliconangle.com/2022/04/19/enso-exited-stealth-16-5m-funding-help-everyone-complex-data-analysis/