Accelerate Enterprise Migration to dbt — with AI-Led Deterministic Automation

At DataSwitch, we enable enterprises to intelligently transform legacy ETL estates, SQL pipelines, and warehouse-native transformations into production-grade dbt implementations through deterministic AI-led automation.

85–90%

Average Automation Rate

70–80%

Avg Cost Reduction Achieved

4–6 Wks

Fastest Dbt Modernization (2,500+ Objects)

14+

Successful Implementations On Dbt

Available on
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AWS
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Azure
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Google Cloud

Engineer Intelligent Transformation Pipelines into dbt

Go beyond legacy migration tools. With GenAI-led automation and graph-based engineering, DataSwitch delivers high-quality code faster—reducing manual effort by up to 95%.

Data Platforms
Source DB Reader
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netezza logo
oracle logo
mysql logo
sqlserver logo
db2 logo
greenplum logo
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synapse logo
hive logo
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dbt
ETL tools
Source ETL Reader, Scheduler
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talend logo
ssis logo
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autosys logo
palantir logo
fabric logo
abinitio logo
sapbw logo
uc4 logo
odi logo
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Automate Your End-to-End Migration to dbt

DataSwitch handles every phase of your dbt modernization — from legacy code discovery and assessment to automated conversion, validation, optimization, and production deployment — powered by DataSwitch's Agentic AI automation for high efficiency, speed, and accuracy.

Discover

Analyze and inventory legacy ETL workflows, SQL transformations, schemas, warehouse dependencies, and data pipelines to generate a comprehensive modernization assessment — including automation feasibility, transformation complexity, dependency mapping, optimization opportunities, and migration readiness insights.

Modernize

Powered by its deterministic Agentic AI engine, DS Migrate intelligently transforms legacy ETL and SQL-based workloads into reusable, modular, and production-ready dbt models, macros, snapshots, sources, and tests — aligned with enterprise engineering standards and modern analytics architecture principles.

Auto Validate & Optimize

With built-in validation, dependency checks, and auto-remediation capabilities, DS Migrate validates generated dbt assets, identifies transformation inconsistencies, optimizes model structures, and ensures deployment-ready outputs with syntactical accuracy and governance alignment.

Key dbt Enablement Areas

We cover all facets of the dbt ecosystem to deliver highly optimized, modular, and deployable code packages.

dbt Model & Macro Generation
Incremental & Snapshot Models
Automated dbt Testing
Source, Seed & Exposure Generation
End-to-End Lineage Enablement
Modular SQL-to-dbt Transformation
Analytics Engineering Modernization
Production-Ready dbt Frameworks

Frequently Asked Questions

DataSwitch enables enterprises to intelligently transform legacy ETL estates, complex SQL pipelines, and warehouse-native transformations into production-grade dbt implementations. Driven by deterministic, Agentic AI-led automation, the platform maps legacy logic directly into clean, modular analytics engineering frameworks.
DataSwitch delivers an 85% to 90% average automation rate for code translation alongside a 70% to 80% average operational cost reduction. Backed by more than 14 successful implementations on dbt, the platform features a documented fastest delivery window of just 4 to 6 weeks for a high-density workload exceeding 2,500+ data objects.
Traditional rule-based conversion tools require extensive manual rewriting. DataSwitch goes beyond legacy migration tools by leveraging GenAI-led automation and graph-based engineering to deliver high-quality, production-ready code faster, reducing manual remediation effort and custom engineering cycles by up to 95%.
The lifecycle is systematically executed through three automated phases: 1. Discover (analyzing legacy ETL workflows, SQL transformations, schemas, and warehouse ecosystems to assess automation feasibility and dependency mapping); 2. Modernize (using DS Migrate to intelligently transform legacy workloads into reusable, modular dbt models, macros, snapshots, sources, and tests); and 3. Auto Validate & Optimize (leveraging built-in dependency checks and auto-remediation to ensure syntactical accuracy and complete governance alignment).
The framework ingests metadata from source data platforms including Teradata, Netezza, Oracle, MySQL, SQL Server, IBM DB2, Greenplum, SAP HANA, Azure Synapse, Hive, and Sybase IQ. Simultaneously, its source ETL readers parse and translate pipeline logic from Informatica PowerCenter (9.6+), Talend, Microsoft SSIS, IBM DataStage, SAP BODS, Informatica IDMC, Autosys, Palantir, Microsoft Fabric, Ab Initio, SAP BW, UC4, Oracle ODI, and Oracle Middleware.
DataSwitch covers all facets of the dbt ecosystem across eight standardized vectors: dbt Model & Macro Generation, Incremental & Snapshot Models, Automated dbt Testing, Source, Seed & Exposure Generation, End-to-End Lineage Enablement, Modular SQL-to-dbt Transformation, Analytics Engineering Modernization, and Production-Ready dbt Frameworks.

Ready to Modernize into dbt?

Tell us about your modernization journey — we’ll assess your legacy ETL and SQL ecosystem, estimate automation potential, and define a realistic transformation roadmap into dbt. No obligation.