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https://store-images.s-microsoft.com/image/apps.57653.5d9d3857-6943-4e19-a07d-b1a456e7f727.fe3423ee-6568-4ac1-9342-2ff3afd7ab63.31524b74-4a6c-40d9-82ce-4d594ce67c63
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LTIMindtree Limited
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Assessment
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AnalyticsData PlatformMigration
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Servicios financierosIndustriales y fabricaciónVenta al por menor y bienes de consumoAutomoción, movilidad, transporteServicios profesionales
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Australia
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LTIMindtree Data And AI SSIS Modernization to Databricks

LTIMindtree Limited

Modernize SSIS Packages to Azure Databricks workloads with AI-driven automation, reducing effort, risk, and time to insight in just 6 weeks

Modernizing SSIS Workloads with Confidence

As organizations embrace Azure Databricks, many struggle with the complexities of migrating legacy SSIS workloads to modern PySpark-based solutions. Achieving a smooth, low-risk, and strategically aligned transition is critical—but not always straightforward.

Our Solution: Accelerated SSIS-to-Databricks Migration

This focused 6-week engagement is tailored for data leaders, ETL architects, and modernization teams looking to accelerate their shift from on-premises SSIS to the Azure ecosystem, including Microsoft Fabric and Azure Databricks.

We bring a proven, Gen AI–driven automation framework that can reduce migration effort by up to 70%, helping you:

  • Eliminate repetitive manual tasks and reduce technical debt
  • Minimize migration risks with automation and guided planning
  • Accelerate value realization across the Microsoft data platform

    • By converting traditional ETL pipelines into scalable PySpark workflows, you'll unlock the full potential of Azure Databrick's & Microsoft's ecosystem —ensuring scalability, performance, and long-term adaptability.

    Why This Engagement Matters

  • Boost Azure Databricks Adoption: Transform SSIS packages into native, cloud-optimized pipelines
  • Streamline Azure Integration: Ensure compatibility with services like Azure Data Factory
  • Maximize your Microsoft Investment: Modernize workloads to make full use of your existing licensing and platform capabilities

    • Engagement Overview

    Week 1: Discovery & Assessment

  • Scan and inventory existing SSIS packages using proprietary tooling
  • Identify control/data flow patterns, dependencies, and integration points
  • Classify workloads by complexity and readiness for modernization

    • Week 2: Planning & Estimation

  • Generate effort estimates
  • Identify blockers such as unsupported components or custom logic
  • Define a target architecture that aligns with Azure-native services

    • Weeks 3–6: AI-Powered Modernization & Prototyping

  • Auto-generate PySpark-based pipelines compatible with Azure Databricks
  • Validate logic accuracy and ensure performance alignment
  • Deliver a working prototype along with a detailed migration roadmap

    • Deliverables & Outcomes

    By the end of the engagement, you will receive:

  • A clear modernization roadmap aligned to Microsoft best practices
  • A validated prototype to demonstrate modernization feasibility
  • Accelerated momentum to scale SSIS workload transformation across your environment

    • This offering reduces uncertainty and accelerates your path toward a future-ready, cloud-native data architecture—built on Microsoft’s trusted platform.

    Más información
    SSIS to PySpark Azure Databricks
    https://store-images.s-microsoft.com/image/apps.574.5d9d3857-6943-4e19-a07d-b1a456e7f727.fe3423ee-6568-4ac1-9342-2ff3afd7ab63.75c28e2a-eec2-46d0-8b1a-84d5d239065d
    https://store-images.s-microsoft.com/image/apps.574.5d9d3857-6943-4e19-a07d-b1a456e7f727.fe3423ee-6568-4ac1-9342-2ff3afd7ab63.75c28e2a-eec2-46d0-8b1a-84d5d239065d