AutoMapper Studio

AutoMapper is an intelligent, no-code/low-code source to target data mapping engine designed to simplify complex data transformations. It automates schema mapping, validation, and transformation - enabling data teams to accelerate pipeline creation and reduce manual effort. With support for both UI-based workflows and custom rule scripting, AutoMapper seamlessly integrates into enterprise data ecosystems hosted on AWS.

Key Features:

Automated Data Mapping – Intelligently detects and aligns source columns to target schemas, reducing mapping time by up to 70%.

Smart Transformation Rules – Define transformations with SQL expressions, constants, joins, or regex-based extraction.

Custom Logic Support – Add user-defined rules for complex, business-specific transformations.

Entity Generation & Tagging – Organize and tag columns to improve mapping accuracy and reusability.

Multiple Input Format Options – Connect to AWS S3, upload Parquet or Delta files, and include reference datasets.

PySpark Code Export – Generate ready-to-use PySpark scripts for seamless integration into EMR workflows.

Potential Benefits:

Accelerated Time-to-Value – Reduce project delivery timelines from weeks to days with automation.

Reduced Human Error – Built-in validation ensures data consistency and accuracy before deployment.

Scalable for Enterprises – Handles large-scale data workloads natively integrated with AWS services.

Flexible and Extensible – Adaptable to any business domain with customizable rules and logic.

Improved Collaboration – Enables seamless collaboration among data engineers, analysts, and subject matter experts through a shared visual interface.

Lower Operational Costs – Minimizes manual coding, reduces rework, and optimizes resource utilization.