Enso hopes to automate data analytics processes, emerges from stealth with $16.5M

California-based Enso, a company that provides a self-service data analytics and visualization platform for enterprises, today came out of stealth with $16.5 million in funding.

It’s no new news that modern organizations have become heavily reliant on data analytics. They’re gathering data from various sources to get the best business results. However, even today, a large chunk of business users depend on spreadsheets for data preparation (cleansing, standardization, merging, joining and augmentation) and visualization. According to a study conducted by IDC, each business user spends on average up to nine hours per week on repetitive work like manually updating spreadsheet data with changes. This alone costs a company $10,000 in productivity dollars every year. They could rather be spending this time on better exploring the analytical problem at hand or looking at some other problem.

In addition, standalone spreadsheet tools such as Excel, which are not designed to prepare enterprise-level data, don’t easily allow users to test their analytic ideas and can even break or become prohibitively slow at times.

Enso’s open-source platform for data analytics

To address these challenges, Enso provides an open-source platform that’s designed to enable anyone to build and automate data-driven processes, starting from loading and blending data from any source to cleansing and performing advanced analytics, by simply connecting visual components. 

The self-service tool, which the company claims is as easy to use as Excel, analyzes the network of connected components, looks inside the data and suggests the best next steps, 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. It lets users observe the results of each step of the data pipeline in real-time.

“In one of the cases, we were working with a transaction maintenance team. One of their challenges was monitoring transaction errors, discovering which customers were charged twice, and providing automatic refunds to them. The whole process contains a lot of steps. First, the data needs to be downloaded from different sources, including an internal database, a government website (not providing an easy access API), and the underlying Mastercard system. Then, the data needs to be blended, which is a non-trivial process – the same record can be named and timestamped differently across these databases… Moreover, missing data or invalid time records have to be handled as well. By using Enso, we were able to automate 80-90% of their workflow, allowing their data analysts to do the same amount of work they did in the past in 8 hours in less than 1.5 hours now,” Wojciech Danilo, the CEO and CTO of the company, told Venturebeat.

Competition in analytics market

A number of companies are looking at the same space with the ultimate goal of unleashing the potential of analytics for all business users. The leading players in the segment are Tableau, Alteryx and Rapidminer.

However, Danilo claims that Enso’s product differentiates from these offerings on the basis of its interactivity and extensibility.

“Whenever you change any parameter, Enso recomputes the needed parts of the data workflow, and provides you results as soon as possible, often in real-time. Almost all other solutions need to re-run the workflow from scratch. In the case of heavyweight data workflows, this can be even an hour for others versus a few seconds with Enso. This makes a huge difference when building the workflow, as you’ll want to check the results after changing or adding a new data processing step. As a result, creating data workflows in Enso can take hours instead of days,” the CEO said.

Beyond this, he noted that Enso is not just a set of predefined components. Users can connect it to any exotic databases or use any in-house build libraries in Python, Java, JavaScript or R and it … just works. There’s no need for support or waiting for the next version of the product to include things that are needed.

Enso lays out its plans

With the fresh round of funding, led by SignalFire, Khosla Ventures and others, the company will work on improving the interface and stability of the product, making it accessible to a wider section of the audience. The UI of the current version requires the users to have some coding knowledge, but that will change with the next release.

“We plan to release Enso Cloud (SaaS) in Q1 2023 with a user-friendly interface that will not require you to understand coding or scripting. 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,” Danilo said.

According to Allied Market Research, the global business analytics software market is expected to witness 11.2% growth, surging from $61 billion in 2020 to $177 billion by 2030.