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?
Data Taxonomy Development for Unstructured Content
In today's rapidly evolving digital landscape, organizations are often inundated with overwhelming volumes of unstructured content. Emails, documents, audio files, videos, and social media data can create clutter rather than clarity. To turn this tremendous data...
Inter-Company Data Sharing Governance Framework
Navigating today's incredibly fast-paced digital ecosystems requires businesses not only to leverage their data effectively but also to strategically share and exchange it with external partners. Whether it's supply chain insights, customer behavioral patterns, market...
Column-Level Encryption for Sensitive Data Fields
In today's fast-paced digital environment, businesses are the stewards of increasingly vast amounts of sensitive information, from financial figures and employee personal records, to confidential client data. With great data comes not only great opportunity, but also...
User-Driven Data Classification Implementation
Imagine meticulously collecting terabytes of data only to discover significant organizational confusion surrounding what it all truly means. In today's competitive landscape, where accurate decisions hinge on speedy data retrieval, understanding the information in...
Data Field Deprecation Signals and Consumer Notification
In today's rapidly evolving technology landscape, outdated data strategies can spell doom for data-driven enterprises. Yet, even more insidious than outdated systems are obsolete data fields that silently threaten analytics accuracy and operational workflows....
Granular Access Log Implementation for Data Usage Auditing
Imagine being able to trace the exact path any user takes through your organization's data platforms—understanding in real-time who accessed specific data, how frequently, and for what purpose. With businesses increasingly relying on data-driven decisions, granular...
Data Element Cross-Reference Registry Implementation
In our increasingly interconnected digital world, the complexity of data integration across various systems is evolving rapidly. Business leaders are navigating intricate data landscapes, facing constant challenges of data fragmentation and inconsistency. Implementing...
Propagating Data Classification Tags Through Transformations
In a modern analytics environment, data doesn't stay stationary—it constantly transforms, integrates, and morphs to deliver strategic insights. However, as data moves and evolves, its classification tags—privacy, sensitivity, compliance, and ownership—must remain...
Enterprise-Wide Data Type Standardization Framework
Data is the lifeblood of the modern enterprise, fueling innovation, strategic decision-making, and competitive advantage. Yet, despite recognizing its value, many organizations grapple with inconsistent, fragmented data types that hamper their analytical capabilities...