AutoMapper: Automated Data Mapping

Transform Complex Genomic Data into Breakthrough Insights Faster, Smarter, Scalable Explore Now

Automapper's Core Framework

Why AutoMapper?

Cut Mapping Time by 70%

Slash mapping projects from weeks to days with intelligent column detection. Stop spending months on manual mapping—start delivering results instantly.

Eliminate Errors

Catch errors before they reach your pipelines with built-in validation. Easily check for type mismatches and transformation errors in a single click.

Code Your Way When Needed

Tackle the toughest transformations by creating your own logic with custom rules to handle unique business requirements that are off-the-shelf.

Maps to Your Patterns

Your industry-specific preferences become baked into the system with every decision you make, creating a mapping engine that thinks like your business.

Simple Steps to Smarter Mapping

Everything you need - automated, scalable, and built for enterprise velocity.

Upload Your Source

Drag and drop Parquet files or connect directly to S3 buckets. Add lookup tables and reference data too all in one place.

Define Your Destination

Upload your target schema JSON or use a reference dataset. AutoMapper learns exactly where your data needs to go.

Generate Entities

Create semantic categories for columns with similar purposes. AutoMapper uses these to improve mapping accuracy.

Apply Intelligent Tags

Tag your entities to guide the mapping engine. Tags propagate automatically to all related columns.

Set Transformation Rules

Define how data should change during mapping with SQL expressions, constants, or join operations through an intuitive interface.

Review Your Mappings

Check AutoMapper’s suggestions and fine-tune where needed. Validate that everything will land exactly where it should.

Run With Confidence

Execute your transformation with a single click. Export to your destination or as PySpark code for your pipeline.

Raw Inputs to Ready-to-Use Data On Autopilot

Column Alias

Easily match variations like fname to First Name. AutoMapper auto-detects and aligns source fields to your destination schema.

Merge Fields

When multiple fields need to be merged into a single property, AutoMapper handles it with precision no manual formatting required.

Extractions

Need domains from email addresses or area codes from phone numbers? AutoMapper extracts it all using regex or simple patterns.

Nested Data

Convert columns into nested records or arrays. Perfect for mapping child object transformations on the fly.

Interpolations

Build clean, formatted text merging values like turning address components into a single location string.

Default Values

Auto-populate empty fields with default values to ensure consistency across datasets.

Smart Formatting

Standardize names, clean up special characters, or encode values with predefined transformations all configurable.

Arithmetic Calculations

Compute fields like taxes or risk scores using formulas across columns. AutoMapper supports advanced calculations seamlessly.

Built for Enterprises Driving Data Innovation

Ready to kickstart smart mapping?

Data Innovation in Action

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What our customers are saying

Modak delivered exceptional work by completing all planned objectives while proactively identifying design gaps. Their collaborative approach fostered strong knowledge sharing and continuous learning across the engagement. Even under pressure, Modak maintained a supportive and professional environment, ensuring outcomes were achieved with precision and grace.

Anna KingLead Product Owner

Modak provided excellent support, demonstrating consistency and commitment in resolving critical user issues within CML. Their proactive engagement and technical depth ensured challenges were addressed effectively, reinforcing trust and reliability throughout the process.

Ryan CicakPrincipal Solutions Engineer, Cloudera

Modak provided excellent support in streamlining Cloud 3.0 integration and setting up key StreamSets components. Their expertise helped simplify the adoption of the new platform within CDF EPP and enabled meaningful product improvements, allowing tenants to focus on pipeline development with minimal infrastructure concerns.

Christina SelwayAssociate Director, Cloud Architecture

We greatly value Modak’s continued support and collaboration. Through dedicated design, development, and rigorous testing, they have enabled the platform that streamlines data operations and delivers measurable business value.

Gian PrakashDirector, R&D Information Research Business Techno…

Modak’s perseverance, collaboration, and unwavering commitment stand out in every engagement. Their ability to overcome challenges with a positive approach and deliver with excellence has earned deep appreciation across the organization. These achievements reflect Modak’s dedication to going above and beyond to create lasting impact.

Yesenia M. EchevarriaARCH Data Operations Lead

Modak’s proactive handling of a critical StreamSets issue removed a major roadblock for Medicaid reporting. By keeping all stakeholders informed and working closely with the CDFCC team, they showcased both technical depth and strong communication. Their ability to resolve challenges under pressure reinforces Modak’s reliability as a trusted partner.

Sitara SuravarapuLead Technology Leadership Professional

Modak has played a critical role in the success of the CAGE project, contributing from day one with deep technical expertise and commitment. Their ability to take initiative, innovate, and prototype solutions ahead of challenges has been invaluable. The team’s contributions to the ARCH program continue to drive impact, and we look forward to building on this strong collaboration in the next phase.

Henry SuAssociate Data Engineer II

Modak’s commitment to delivering the DataOps project on time has been outstanding. Their dedication, precision, and excellence ensured smooth execution and timely outcomes. The organization deeply values this consistency and focus—truly fantastic work.

Sudeep SangamreddiLead Cloud Architect

Modak’s dedication and perseverance were instrumental in bringing the UDAP Disaster Recovery to a production-ready state. This unanimous approval reflects both the passion and teamwork behind the effort. The achievement sets a strong foundation for the next phase, raising the bar for future success and enabling the path to go fully live.

Raj MarriapanTechnology Leadership Principal

Modak’s team demonstrated exceptional commitment and professionalism in completing the Pharmacy Business Migration. Over 16 months, they successfully transitioned all use cases to the EEH Kafka cluster, enabling the decommissioning of PBM clusters. This milestone not only ensures operational efficiency but also delivers $1.5M in annual savings.

Kapil ShahLead Technology Lead Professional

Modak played a pivotal role in delivering a major release that introduced an entirely new functional module. Their excellence, collaboration, and commitment ensured a smooth launch and demonstrated how a supportive team culture can drive successful project outcomes.

Dr. Xing, YunzhaoAssociate Director, Statistical Innovation

Modak’s delivery on FileWatcher enhancements and the MBE to CoreAPI migration has been central to advancing interoperability goals. This helped us with faster data availability, improved reliability, and reduced operational friction—creating a strong foundation for future innovation and business agility.

Jessie GoodloeAssociate Director, Interoperability

Modak’s flawless implementation showcased both technical skill and dedication, directly impacting Humana’s operating expenses by driving greater cloud efficiency. This milestone stands out as one of several high-value use cases delivered in 2024, underscoring Modak’s ability to combine quality execution with measurable business impact.

Manish JhaAssociate Director

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