One of the biggest challenges enterprises face is processing all the data that they gather. According to a report, 85% of organizations have low business intelligence maturity. Even as companies invest more capital in data initiatives, the situation hasn't changed much. A survey by Databricks and MIT found that only a small percentage of organizations are delivering on their data strategy.
The Brodacka brothers are well-acquainted with the struggle. Film visual effects tools that help to simulating particles have been authored by the cofounders of Enso.
It might seem like the data processing needs of most businesses are different from the needs of the visual effect industry. The reality is not as it seems, according to Danilo via email. A realistic sand simulation requires a table containing particle data and a simulation of physical rules such as collision rules and attraction forces.
The idea of applying their visual effects tools to other areas was brought up by Brodacka. Enso, a data analysis and visualization startup that came out of stealth with $16.5 million in funding, is the result of this.
The capital is being put toward improving Enso's platform with better documentation and onboarding, increasing the number of data processing modules on the platform, and releasing a software-as-a-service product called Enso Cloud.
Coddee and Flowbox are two of the startups that Danilo has launched. Brodacka was responsible for designing and developing image processing libraries at Flowbox.
Enso's platform allows data analysis.
The eponymous open source project Enso was created by Danilo and Brodacka. Enso is a visual programming toolkit that helps build data workflows, dashboards and apps by analyzing historical and live data, suggesting possible next steps, and even controlling other applications.
While the concept might sound similar to existing visualization tools like Alteryx, Knime or Databricks, Danilo insists that Enso is different.
Enso is changing much broader categories of data processing. There is more to it than a nice interface with a hardcoded, limited and hardly-extensible set of components. There are people who extended Enso with the possibility to analyze and process 3D models of buildings, sound and even internet of things device networks.
The handling of data is one of the highlights of Enso. A standard computer science toolset can be used to review, version and deploy the pipelines. Enso can help visualize errors when they occur and prevent certain errors from happening, for example by preventing users from overwriting values in a database.
One company that used Enso for a pilot project gave refunds to customers that were affected by duplicate transactions. The data was taken from multiple sources, including government websites, and reconciled even in the absence of timestamps.
The image is called Enso.
Business users bring domain expertise to the table, but due to lack of technical skills, they need to constantly ask developers for help and, thus, are waiting for results even several days after every such request. If you want to process more advanced data, like logs, medical images, internet of things devices, or your website traffic data, you need more than just excel. We want Enso to be the go-to solution.
As data analysts and scientists become increasingly bogged down in repetitive work like updating spreadsheets every time a dataset changes, it's hope that Enso ultimately reduces the barrier to more versatile forms of data processing. Enso Cloud will be establishing a recurring revenue stream over the next year and he has a business motivation. He hopes to make the field less intimidating for the layperson because he has worked with large datasets and data pipelines for most of his career.
It is impossible to provide tools for this domain that do not have a powerful and flexible engine. Enso did not create just a nice interface with a hardcoded set of data-processing components.
Enso, which has a 20-person workforce, has raised $17.5 million in capital. The company is hiring.
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