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?
Custom Serialization Tricks for Ridiculous Speed
Imagine being able to shave substantial processing time and significantly boost performance simply by mastering serialization techniques. In an environment where analytics, big data, and intelligent data processing are foundational to competitive advantage, optimized...
Out-of-Order Events: Taming the Ordering Problem
In the rapidly evolving landscape of data-intensive businesses, event-driven systems reign supreme. Events flow from countless sources—from your mobile app interactions to IoT sensor data—constantly reshaping your digital landscape. But as volumes surge and complexity...
Checkpoints vs Snapshots: Managing State Without Tears
Imagine managing large-scale applications and data environments without ever fearing downtime or data loss—sounds like a dream, doesn't it? As complexity scales, the reliability of your systems hinges on the right strategy for state management. At the intersection of...
The Batch Size Dilemma: Finding Throughput’s Sweet Spot
In today's hyper-paced data environments, organizations face an intricate balancing act: finding the precise batch size that unlocks maximum throughput, optimal resource utilization, and minimal latency. Whether you're streaming real-time analytics, running machine...
Geolocation Workloads: Precision Loss in Coordinate Systems
In an age where precise geospatial data can unlock exponential value—sharpening analytics, streamlining logistics, and forming the backbone of innovative digital solutions—precision loss in coordinate systems may seem small but can lead to large-scale inaccuracies and...
Art of Bucketing: Hash Distribution Strategies That Actually Work
In today's data-driven world, handling massive volumes of information swiftly and accurately has become an indispensable skill for competitive businesses. Yet, not all data distribution methods are created equal. Among the arsenal of techniques used strongly within...
Compression in Motion: Streaming & Working with Zipped Data
In the modern world of rapid digital innovation, effectively handling data is more important than ever. Data flows ceaselessly, driving analytics, strategic decisions, marketing enhancements, and streamlined operations. However, the sheer size and quantity of data...
The Core Paradox: Why More CPUs Don’t Always Mean Faster Jobs
In today's fast-paced IT landscape, the prevailing wisdom is clear: if a process is running slowly, simply throwing more processing power at it—meaning more CPUs or cores—is the immediate go-to solution. After all, more cores should mean more simultaneous threads,...
Seasonality Effects: Adapting Algorithms to Cyclical Data
In the dynamic landscape of data analytics, seasonality is an undeniable force shaping your strategic decisions. Businesses confronting cyclical data variations—whether daily, monthly, or annual trends—must adapt algorithms intelligently to uncover impactful insights...