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?
Tensor Ops at Scale: Crunching Multidimensional Arrays
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Context Propagation: Maintaining State Across Boundaries
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Factory Pattern: Injecting Dynamic Processing Logic
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Complex Event Processing: Detecting Patterns in Streaming Flow
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Repository Pattern: Clean Data Access Layers
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Graphs at Scale: Adjacency Lists vs. Matrices Revisited
In the current era of big data and complex interconnected systems, graph analytics plays an increasingly critical role in understanding the nuanced relationships within data. As businesses grapple with more extensive, intricate systems and data sets, the method you...
Ports & Adapters: Going Hexagonal with Your Pipeline
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Bloom Filters & HyperLogLog: Fast Probabilistic Structures
In today's data-driven world, speed, efficiency, and accuracy aren't merely desirable—they're essential. As data volumes explode exponentially, traditional strategies to manage vast datasets encounter significant bottlenecks. Enter probabilistic data structures like...
Multimedia Pipelines: Extracting Metadata from Binary Blobs
In a digital-first world, multimedia is a core foundation of nearly every business-savvy decision—whether you're streaming high-definition videos, analyzing user-generated photos, or processing audio files for marketing insights, extracting and managing metadata from...