Naveen JujaraySecure Case Study Sandbox
Case Studies/KANERIKA
2 min read

Accelerating Enterprise Data Modernization: Automated Informatica to Fabric Migration

Programmatically parsing legacy ETL XML files to auto-generate Power Query (M) scripts and T-SQL pipelines on Fabric.

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Client Identity

Kanerika Inc.

Assigned Role

Microsoft Fabric Analytics Engineer

Timeline Window

August 2025 – October 2025

Integration Agent

Kanerika Inc.

The Business & Technical Challenge

Migrating complex, legacy on-premises ETL architectures like Informatica PowerCenter to modern, cloud-native platforms like Microsoft Fabric is a notorious bottleneck. Legacy workflows, filter routing, aggregator states, and custom expression rules are deeply locked inside proprietary Informatica XML formats. Traditional migrations require expensive, manual re-coding and line-by-line rebuilding of pipeline transformations, introducing severe errors, prolonged testing timelines, and high development costs.

The Engineered Solution

Within the FLIP product engineering pod, we architected a programmatic compiler. We engineered an XML deconstruction parser that deciphers mapping nodes, routing matrices, and transform definitions, organizing them into a standardized metadata schema. I built the code generation engine that took this structural schema and automatically translated the business rules into equivalent Power Query (M) code blocks for Fabric Dataflow Gen2, and T-SQL script snippets for warehousing optimization. We then leveraged Microsoft Fabric REST APIs to automate the remote generation of pipelines in the destination Lakehouse.

FLIP Migration Architecture: Informatica PowerCenter to Microsoft Fabric

Step 01
Source XML

Proprietary Informatica pipeline mapping XML file loaded.

Step 02
Compiler Parser

Translates mapping logic blocks into standardized metadata.

Step 03
Code Generator

Compiles functional Power Query M equations and fast SQL files.

Step 04
Fabric API sink

Deploys code-gen schemas directly inside OneLake Warehouses.

Architectural Phases & Implementation Details

1

Proprietary XML Ingestion

Ingested legacy Informatica PowerCenter XML layouts, decoding nested structural mappings and rules.

2

Metadata Mapping Compiler

Created structured parsing tables classifying Expression, Filter, Joiner, and Aggregator properties.

3

M Query & T-SQL Compiler

Constructed programmatic logic generators that code-gen functional Power Query M rows and highly-optimal T-SQL views.

4

Automated Orchestration

Triggered cloud-native Fabric Dataflow Gen2 layers through dynamic Fabric REST pipelines, avoiding manual setup.

System & Integration Architecture

High-fidelity technical blueprint representing Naveen's Kanerika Inc. project systems and integrations.

Kanerika Inc. System Architecture Blueprint

*Click diagram above to inspect technical stages, pipeline sequences, and technology stacks at full magnification.

Measurable Outcomes & ROI

Manual Effort Saved

40% Decline

In developer workloads required to extract, recreate, and test legacy pipelines.

Delivery Acceleration

Months to Weeks

For large enterprise clients updating heavily tangled legacy on-premises ETL arrays.

Migration Parity

100% Parity

Verified via systematic validation framework, comparing historical outputs with new pipelines.

Core Outcomes Narrative & Direct Impact

Using metadata compilers and automatic programmatic generation algorithms:

Reclaimed 40% of the manual developer hours typical in baseline migration assignments.
Cut large transition calendars down from multiple months to just a handful of target automation weeks.
Maintained a verified 100% data and logic alignment matching the source on-premises transformations exactly.

Engineering Summary Memo

Enterprise modernization projects are historically derailed by manual lift-and-shift operations. By utilizing programmatic automation to parse XML layouts and programmatically compile optimized M and T-SQL environments, we proved that data engineers can automate migration processes. This module accelerates time-to-value for enterprise customers scaling up clinical, manufacturing, or financial analytics on Microsoft Fabric.