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?
Hot, Warm, Cold: Choosing the Right Temperature Tier for Your Bits
In the digital age, data is the lifeblood flowing through the veins of every forward-thinking organization. But just like the power plant supplying your city’s electricity, not every asset needs to be available instantly at peak performance. Using temperature tiers to...
Trees, Graphs, and Other Recursive Nightmares in Hierarchical Workloads
If you’ve ever ventured into the realm of hierarchical data, you've surely encountered the bittersweet reality of recursive relationships—those intricate, repeating patterns embedded within trees, graphs, and nested structures that both fascinate and frustrate data...
The Metadata Maze: Extracting Schemas from Unstructured Blobs
In today's data-driven landscape, the volume and variety of unstructured information flowing daily into organizations can quickly become overwhelming. With business leaders and technologists recognizing the immense potential hidden in unstructured data—such as images,...
Data on a Shoestring: Open Source vs Enterprise Pipeline Costs
Every organization aims to become data-driven, but not every organization enjoys unlimited resources to achieve that vision. Leaders tasked with managing data-rich environments find themselves confronting a perennial question: Should we embrace cost-effective...
Sampling Isn’t Dead: Modern Stats Techniques for Big-Data Workloads
When the term “big data” emerged, many tech leaders believed that traditional statistical strategies such as sampling would quickly become extinct. However, rather than fading away, sampling has evolved, keeping pace with rapid innovation and the massive data influxes...
Graceful Degradation: Surviving When Everything Goes Wrong in Batch Jobs
Picture this: your data-driven enterprise relies heavily on nightly batch processing to power critical business decisions, but one evening, disaster strikes—pipelines break, dependencies fail, and your morning analytics dashboard starts resembling an empty canvas....
Parquet vs ORC vs Avro: The File-Format Performance Showdown
In today's data-driven landscape, selecting the right file format isn't merely a technical detail; it's a strategic business decision. It affects query performance, storage efficiency, ease of data transformation, and, ultimately, your organization's competitive edge....
Unicode Nightmares Solved: Processing Multi-Language Text
In the digital era, data doesn't speak a single language—it's a multilingual symphony playing across global applications, databases, and interfaces. This multilingual reality brings with it complexities, intricacies, and sometimes outright nightmares in the form of...
Lineage Tracking at Scale Without Sacrificing Throughput
As digital environments grow increasingly complex, tracking data lineage becomes vital for organizations aiming for transparency, trust, and operational efficiency. Implementing scalable lineage tracking without compromising throughput is a unique challenge businesses...