CSV, JSON, and Github CSVs. Also manual tables.
These help you kick start your data pipeline. ET1 helps you do that and a bit more.
Once your data comes into the data input, it begins to flow downstream using a custom DAG streaming engine.
You know the drill, data tools are very similar, it all starts with extracting your data.
But are you familiar with where your data lives? Start asking, documenting, and building your understanding of your data environment. This software will help you warehouse that information into a single canvas, without having to ask engineering for help.
Input Node Overview
The Input nodes are essential for moving the needle in ET1, without data, we are using our feelings!
- The CSV Input node is great for getting your Comma delimited files into ET1.
- The JSON Input node is great for getting JSON in the app, your engineering team will be happy.
- The Github CSV is where you can get CSVs off the public internet. That’s fun. Enrich your data pipelines.
- Manual table is great, synthesize a few rows, add table, make life easier.
The future of data inputs for ET1
We are eager to add more connections but today we are looking to keep it simple by offering CSV, JSON, Github CSV, and manual tables.
Next? Excel input perhaps.
ETL Input Nodes – Simple as Pie
📊 CSV Input
- What it does: Loads data from CSV files or text
- Why it’s cool:
- Drag & drop any CSV file
- Handles messy data with smart parsing
- Preview before committing
- No more: Fighting with Excel imports or command-line tools
🧾 JSON Input
- What it does: Imports JSON data from files or direct input
- Why it’s cool:
- Works with nested JSON structures
- Automatically flattens complex objects
- Great for API responses and config files
- No more: Writing custom parsers for every JSON format
📝 Manual Table
- What it does: Create data tables by hand
- Why it’s cool:
- Add/remove rows and columns on the fly
- Perfect for quick mockups or small datasets
- Edit cells like a spreadsheet
- No more: Creating throwaway CSV files for tiny datasets
🐙 GitHub CSV
- What it does: Pull CSV files directly from GitHub
- Why it’s cool:
- Point to any public GitHub CSV file
- Auto-refreshes on URL change
- A fetch button to ‘get’ it again
- Great for github collaboration
- No more: Downloading data, this gets it for you.
The Best Part?
No coding required.
No complex setup.
Just point, click, and start transforming your data like some data engineer, the pro.
What used to take hours (and a computer science degree) now takes seconds, and not scary…
Return to ET1 Overview to learn more.
