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AI Infused Data Management Accelerator for Azure Databricks - MVP

WinWire Technologies

Accelerate Data Management by up to 70% with WinWire’s AI Agent–Infused Data Management Engine for Azure Databricks.

Modern enterprises on the Databricks Lakehouse face challenges with ingestion, schema evolution, and governance at scale. WinWire’s AI Infused Data Management (WinAIDM) unifies these processes with AI-infused automation and a visual management experience—enabling faster onboarding, consistent quality, and self-service governance.

WinWire’s Solution

WinAIDM Data Management Accelerator integrates four core engines that enable end-to-end automation:

  • 1. AI Data Onboarding – Automates discovery, metadata capture, and Databricks pipeline creation.
  • 2. Intelligent Integration – AI Agents orchestrate data movement across bronze, silver, and gold zones using Spark and Delta Lake.
  • 3. Quality Enforcement Engine – Applies AI-generated PySpark rules for schema, format, and business validations.
  • 4. Smart Data Modeling Engine – Uses AI to design dimensional models and generate transformations for analytics and reporting.
  • The WinAIDM Application UI provides a single pane of glass to configure, monitor, and validate all data processes—no manual code required.

    WinAIDM Solution Approach

  • Discovery: 1) Assess data sources, schema drift, and governance readiness. 2) Identify quality rules and transformation requirements.
  • Pilot: 1) Set up and Configuration of WinAIDM AI agents. 2) Deploy ingestion and DQ pipelines via AI Agents. 3) Deploy ingestion and DQ pipelines via AI Agents. 4) Use WinAIDM UI for configuration, rule authoring, and monitoring. 5) Validate and visualize results using Auto Insights.
  • Scale Out Plan: 1) Extend ingestion and transformation across enterprise sources.2) Integrate Unity Catalog and Microsoft Purview for governance.3) Enable self-service rule management and validation through the application.
  • Business Value

  • Up to 70% reduction in effort through AI automation.
  • Natural-language-driven PySpark generation via AI Agents.
  • Self-service application for rule, pipeline, and validation management.
  • Governance and lineage integration with Unity Catalog and Purview.
  • Accelerated insights from AI-powered reporting and Auto Insights.
  • Key Deliverables

  • AI-driven ingestion, DQ, and transformation pipelines for Azure Databricks.
  • Metadata templates and AI-generated validation functions.
  • WinAIDM Application for unified UI-based operation.
  • Pilot across 2–3 datasets sourced into Databricks Lakehouse (Delta Lake).
  • Integration with Unity Catalog and Purview.
  • Scale-out roadmap for enterprise adoption.
  • At a glance

    https://store-images.s-microsoft.com/image/apps.31259.62416636-ff88-4bdd-9f1e-65502e18758b.628e1176-e880-43ed-aa6f-6cf5e4b0141d.12c28dfd-f35e-4050-ae76-81ba4cf5d859
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