Enso is a visual programming language designed for data science that enables users to create repeatable workflows for data preparation, analysis, and deployment. By automating data processes, it helps data teams save an average of seven hours per week, enhancing efficiency in managing structured and unstructured data.
Funding
$30.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
+14Founders
Product
Problem
Data teams often struggle with inefficient data workflows due to manual processes, difficulty in blending structured and unstructured data, and lack of version control, leading to wasted time and potential errors. Existing tools may also lack transparency, hiding configurations behind icons and making it difficult to understand and audit workflows.
Solution
Enso is a visual programming language designed to streamline data workflows for data science teams. It enables users to create repeatable processes for data preparation, analysis, and deployment through a no-code or full-code interface. The platform supports ingestion of both structured and unstructured data from various sources, including Snowflake, PostgreSQL, SQL Server, Excel, Tableau, files, and APIs. Enso allows users to clean, reshape, blend, and process data in-database and in-memory, with live, interactive data processing for immediate feedback. Workflows are automatically versioned and saved, and data links provide shortcuts to data sources that can be updated without modifying the workflows themselves.
Target Audience
Enso is designed for data teams, including data scientists, data engineers, and business analysts, who need to create and manage efficient, repeatable data workflows for data preparation, analysis, and deployment.
Features
- Visual programming interface with full-code editing capabilities
- Data Links for managing connections to files, databases, queries, and APIs
- Version control for workflows, data files, and data links
- Ingestion of structured data from sources like Snowflake, PostgreSQL, and SQL Server
- Ingestion of unstructured data from files and APIs in formats like text, JSON, and XML
- Data cleaning and reshaping tools for addressing missing values and correcting errors
- Data blending and processing in-database and in-memory
- Live, interactive data processing for immediate feedback
- Integrated workflow documentation
- Cloud and desktop deployment options
- Data Links sharing with granular control based on classification and risk level
- Ability to store encrypted credentials for Data Links
- Comprehensive access and usage logging for governance
- Workflow scheduling and monitoring in the Enso Cloud
- Ability to expose workflows as REST APIs