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Migrate Spotfire to Microsoft Fabric

Quadrant Technologies

Spotfire customers can seamlessly migrate to Microsoft Fabric with Quadrant's support, optimizing workflows and establishing a robust landing zone for a smooth transition

Migrating from Spotfire to Microsoft Fabric

Quadrant Managed Services

Migrating from Spotfire to Microsoft Fabric involves transferring datasets, visualizations, and workspaces to a comprehensive platform that centralizes data management, real-time analytics, and BI. Fabric enhances scalability, flexibility, and provides advanced tools for better insights and unified data handling.

Fabric Adoption Methodology:

Quadrant Managed services follows structured methodology to onboard customers onto Microsoft Fabric. It involves the following steps:

  • Assessment
  • Adoption – Follows 4 C’s Framework
    1. Competence
    2. Consultation
    3. Certainty
    4. Customer Satisfaction
  • Acceleration
  • Adherence to Enterprise Scale
  • Aligning to industry-standard solutions with Microsoft Fabric's integrated capabilities.

Spotfire to Microsoft Fabric Inventory Tool

This tool allows customers to accelerate the Inventory assessment by using Rest APIs for following:

  • Data Ingestion: Migrates data from various sources into Fabric’s unified data ecosystem.
  • Enhanced Data Governance: Fabric’s Medallion Architecture includes data cleansing, standardization, and a Data Quality and Governance Platform (DQGP), ensuring reliable data for analytics.
  • AI-Powered Context Models: Leverages Fabric’s large language models (LLMs) for automated business context modeling, enabling AI-driven insights.
  • Co-Pilot/GenAI Templatized Reports: Provides quick, adaptable reporting with AI assistance, automating report creation and customization.
  • Real-Time Analytics: Supports continuous real-time analytics with end-to-end alerts for time-sensitive insights.

Key Components of the Inventory Tool:

  1. Data Source Inventory:

    • Data Source Type: Database, file, API, etc.
    • Data Volume: Size of the data source.
    • Data Freque

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