Enso Launches to Make Complex Data Analysis More Accessible

Enso, the company making data analysis accessible to everyone, has launched out of stealth with $16.5M in funding “from SignalFire, Khosla Ventures, Day One Ventures, Decacorn Capital, Y Combinator, Samsung Next, Harvard’s Endowment, West Coast Endeavors, Innovation Nest, and more.”

Enso’s open source platform “makes analyzing complex data as simple as using Excel so that non-technical users can autonomously access the insight they need while technical users can accelerate their workflows.”

The platform democratizes data “so that business users can now access the level of insight once reserved for data scientists.”

Data analysts and other business users spend “nearly 20% of their time doing repetitive work like updating spreadsheets every time a dataset changes.”

These users spend time “focusing on how to augment data to fit their analysis inputs rather than the analytical problems they want to solve.”

They spend most of their time in spreadsheets “where data lacks interactivity, meaning users can’t easily test their ideas while working.”

When trying to perform advanced analyses with large datasets, spreadsheets “become prohibitively slow and need to be manually updated every time a dataset input changes.”

Spreadsheets are also fragile as they can “break with the slightest change in input data formatting.”

Further, advanced spreadsheet analysis often “requires data scientists to organize and prepare datasets – of which there is an enormous workforce shortage.”

Businesses are generating more data than ever “with vast volumes of product usage analytics, advertising metrics, market data, user attributes, and more which are stored in massive databases.”

The number of data engineers and data scientists entering the workforce “isn’t keeping up with demand, with three times the number of job postings by businesses than searches by candidates for data science roles.”

Enso enables anyone – technical and non-technical users alike – “to build and automate data-driven processes simply, by connecting visual components.”

It is a self-service tool that is “as powerful as programming languages, yet as easy to use as Excel.”

Because Enso makes analysis so accessible, businesses “no longer need to spend extensive resources recruiting data scientists and dedicated engineers to support business analytics.”

Data analysts and business users “can directly run complex analytics processes while data scientists can work more efficiently.”

Enso works using components that “process data and output results.”

For instance, one component can “consume a dataset of advertisement locations across a city, the next component can filter out only those advertisements on bus stops, which is available as a rendered map of the city with plotted advertisements.”

Enso analyzes the whole network of components, “looks inside the data and suggests the best next steps for users, allowing users to work on data, see it change live, understand it in real-time, and modify it by mapping visual components, rather than writing code.”

Enso was co-founded by Wojciech Danilo, an engineer “with over a decade of experience developing for the VFX space … who previously founded two other companies, alongside Sylwia Brodacka, a physicist and computer scientist who previously designed materials to build rockets and implemented image processing libraries for VFX needs.”

The pair claim to have “spent eight years working together before co-founding Enso.”

Wojciech, co-founder, CEO, and CTO of Enso stated:

“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. It became clear to us that there existed a severe pain point, largely driven by the shortage of data scientists.”

Sandhya Venkatachalam, Partner at Khosla Ventures, remarked:

“Enso is alleviating much of the pressure on companies struggling to hire enough data scientists to keep up with today’s massive amounts of data. It’s a game changer for companies in the many industries that rely heavily on deriving insights from data for competitive advantage.”

Oana Olteanu, Partner at SignalFire, added:

“I believe that 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. The founders’ background in visual effects data processing helped them to make Enso so intuitive. Sylwia, is playing a big role in attracting top talent. Good people are often very diverse people. Hiring a diverse pool of talent brings a diversity of perspectives that mirrors the diversity of the customers and builds a sustainable business. Sustainable companies give the highest returns to the employees, founders and ultimately investors.”

Enso lets “anyone build and automate data-driven processes simply, by connecting visual components.”

Working in a visual environment allows users to think about their data transformations “rather than thinking about how computers and algorithms crunch data.

While Enso’s primary interface is visual, it also is “a real polyglot programming language, making it easy for users to extend its library of functions to create custom functions in languages like Java and Python.”

Before Enso, the current primary tool for data analysts and business users “were spreadsheets, which lack data interactivity, version control and debugging, and must be manually updated in collaboration between data engineers and business users any time a data format changes.”

Enso seamlessly integrates “with version control systems like git, continuous integration systems, and all kinds of code-based workflows, meaning that Enso graphs can be integrated into production without the need for being rewritten into other languages.”

The company raised “a total of $16.5M from SignalFire, Khosla Ventures, Day One Ventures, Decacorn Capital, Y Combinator, Samsung Next, Harvard’s Endowment, West Coast Endeavors, Innovation Nest, and more.”

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