Uncomplicate Data
ET1, for humans who hate complex
No ET phone home.
Data Inputs
CSV, JSON, and Github CSVs. Extract the data.
Filters
Filter by measure, use regex, wild cards, across your data.
Merge
Inner join, left join, stack with union, and concat columns.
Aggregate
Minimum, maximum, mean, sum, and yes, group by.
Streaming
Flow data downstream. Never click run.
Consulting
Expert help.
Keep it Simple.
About ET1
ET1 is a visual data workbench that lets you explore, clean, and explain data in-memory. Built for non-technical humans, (but developer friendly) who want to wrangle data, without complexity.
Create
Hands-on ETL
Training Documentation
Use the training material to help you understand more about ET1 and how it helps solve data wrangling problems.
ET1 Basic Training
If you need help getting started, begin here.
ET1 Video Training
Learn the basics, the features, and more.
Future Insight
We see the future being focused on adoption, training, and creating Easy Tools for anyone. We are building an emerging technology while also maintaining a creative user experience that is inviting and friendly for all ages.
Inspiration
We are inspired by software, video games, and Sci-Fi movies like The Matrix, Minority Report and Ironman. ET1 is created to be “some-what” similar to other legendary software like Alteryx Desktop, and KNIME Analytics Platform.
Join beta.
Why do you want to access beta?
Role-Based Access Control for Data Platform Services
In today’s data-driven landscape, decision-makers depend on powerful analytics insights, seamless data integrations, and efficient security frameworks to keep their organizations competitive. Yet, despite investing heavily in sophisticated data platforms, many leaders...
Reference Data Management System Architecture
Reference data stands as the backbone of any robust data-driven organization—offering consistently structured data credentials crucial for analysis, decision-making, compliance, and operational excellence. Architecting an effective Reference Data Management (RDM)...
Data Element Collision Detection in Enterprise Integration
In a bustling digital ecosystem, data flows freely across numerous applications, systems, and platforms. Business leaders understand well the critical need to preserve data integrity and harmonious integration as their organization scales. Imagine data streams as...
Semantic Versioning for Data Schemas and APIs
In today’s rapidly evolving digital landscape, data-driven companies must continuously innovate to stay ahead. As the volume and complexity of data increases, managing data schemas and APIs becomes a critical factor influencing business agility, reliability, and...
Homonym and Synonym Resolution in Enterprise Glossaries
Imagine a scenario you've likely encountered: you're in a key strategic meeting, and stakeholders from different departments are converging. They start discussing "repairs"—marketing understands it as customer relationship repair, finance thinks warranty expenses, and...
Data Quality Rule Expression Language Design
In the realm of data-driven decision-making, good data quality isn't just advantageous—it's essential. Leaders who rely on analytics to refine strategies, streamline operations, and enhance competitiveness know that even small inaccuracies or anomalies in their data...
Golden Record Management in Multi-Source Environments
In today's hyper-connected digital landscape, enterprises face the inherent complexity of operating with diverse data sources. Whether it's customer records, transactional histories, or operational metrics, data redundancy and discrepancies are typical pitfalls that...
Distributed Metadata Management Architecture
Facing the exponential growth of data today, organizations are challenged to maintain efficient, scalable, and trustworthy metadata systems. Metadata is the orchestrator behind the curtain, empowering critical operations such as data exploration, governance, lineage...
Data Ownership vs. Data Stewardship: Technical Implementation
In today’s data-driven environment, organizations perceive data not just as a byproduct of operations, but increasingly as a strategic asset that fuels innovation and competitive advantage. However, alongside the technical evolution comes an important debate: data...