Nexadata Pipelines are end-to-end workflows for transforming data through a series of organized steps. With the addition of Nexadata AI Copilot, you can now create pipelines simply by describing your transformation objectives.

You provide:

Input files (tabular format)
A structured prompt describing your desired logic
An optional output goal file to guide the final format

From there, Copilot builds the pipeline step-by-step, using a deterministic, agentic AI approach. Each transformation is logically derived, reproducible, and fully visible.

Nexadata AI Copilot in Action:

👍 Advanced users can continue to use Advanced Mode to manually define or refine transformations with full control.

Step-by-step Instructions

Step 1: Prepare Your Data

Before starting:

Set up a dataset and add it to your Workflow.
If multiple datasets need to be joined, they must have a common join key. This key could be a unique ID or an email address.
(Optional) Upload a sample output file to define the structure of your desired result

These three inputs — input data, structured prompt, and output goal — provide Nexadata AI Copilot with the context, intent, and target needed to build a pipeline.

Step 2: Build Your Pipeline with Nexadata AI Copilot

Nexadata AI Copilot uses agentic AI intelligence to construct pipelines based on your transformation goals. Every pipeline is generated deterministically, meaning:

Each transformation is derived step-by-step
The same inputs will always produce the same outputs
Every action is explainable, auditable, and transparent

What You Provide

Sample data files — the datasets to be transformed
Structured prompt — a plain-language description of your logic
(Optional) Output goal file — a CSV showing the target format

Copilot evaluates your inputs, applies each transformation in a logical sequence, and presents you with a full, deterministic pipeline ready for review.

✏️ Example Prompts

Example 1

Convert all values in the "status" column to uppercase to ensure consistency. Convert the "last_name" column to lowercase for standardization purposes. Keep only the rows where status equals "ACTIVE" (after the uppercase transformation). Remove the "overtime_hours," "hours_worked," and "projects_completed" columns. Rename "performance_score" to "rating". Group the data by "region" and calculate average salary. Sort the grouped results by average salary in descending order.

Example 2

Build a segment hierarchy based on total order volume per customer. Customers with more than 20,000 in total sales should be classified as 'Strategic', those from the USA as 'Domestic', and all others as 'International'.

Each of these prompts leads to a deterministic sequence of transformations, ensuring full traceability from input to output.

Step 3: Review and Refine Your Pipeline (Human-in-the-loop)

Once Copilot has built your pipeline:

Review each transformation step in order.
Each step is deterministically generated based on your prompt and the output from the previous step.

👍 For more control, users can select and configure transformations through an intuitive UI.

Advanced Mode lets you precisely define each step by manually configuring the transformation logic.

Regardless of the mode chosen, Advanced Mode is always accessible to refine and modify all transformation steps—providing maximum flexibility to adjust your pipeline as needed. Below is an example of configuring a filter transformation in Advanced Mode.

Natural Language Mode (Step-Level Prompting)

You can still add individual transformations using natural language prompts.

Steps created this way are marked with a ⚡ lightning bolt icon.
Hover over the icon to view the original prompt used for that transformation.

This mode works alongside Copilot and Advanced Mode—offering flexible ways to build or edit pipelines, one step at a time.

👉 If you'd like to learn more about natural language mode or advanced mode, please check out this article.

Supported Transformations

Whether you build your pipeline using Copilot or Advanced Mode, Nexadata supports a wide range of transformations:

Copy: Duplicate a column and specify its position in the dataset.
Filter: Include or exclude rows based on custom conditions.
Flip sign: Automatically adjust the sign of values based on custom conditions.
Group by: Group and summarize data with functions like sum, count, and average.
Insert column: Add new columns with formulas or default values.
Insert row numbers: Add sequential row numbers to your dataset using the Insert Row Numbers transformation.
Join: Combine datasets in Nexadata with a common key, using graphical joins (inner, outer, left, right) for a custom, unified output dataset.
Keep: Selectively retain essential columns while removing all others, streamlining your dataset.
Lowercase: Standardize text by converting selected columns to lowercase.
Math Operations: Use the Math transformation for statistical operations like sum, mean, median, and standard deviation on selected columns.
Merge: Combine selected columns into a single column with a custom delimiter.
Remove: Remove unnecessary columns to simplify your dataset for improved focus and clarity.
Rename: Update column names, enhancing clarity and consistency across your dataset.
Replace: Find and replace values in a column, with options for exact matches or regex patterns.
Shift: Reposition columns to the start, end, or relative to another column.
Sort: Arrange dataset columns in ascending or descending order, with options for empty value placement.
Split: Divide a column’s contents into multiple columns based on a specified delimiter.
Stack Rows: Combine rows from two or more datasets where the columns and column types match.
Uppercase: Standardize text by converting selected columns to uppercase.