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What is Microsoft Fabric? Why is it another failure of services of Microsoft as they promised?

Ryan Arjun
6 min readApr 1, 2025

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Microsoft Fabric is an all-in-one analytics platform launched by Microsoft, designed to unify and simplify data management, analytics, and AI integration for organizations. It brings together several existing Microsoft services — such as Power BI, Azure Synapse Analytics, and Azure Data Factory — into a single Software as a Service (SaaS) solution.

The platform is built to handle a wide range of data-related tasks, including:

  • Data Movement: Tools like Azure Data Factory enable seamless data ingestion and transformation.
  • Data Science: Features for building and deploying machine learning models.
  • Real-Time Analytics: Capabilities for processing and analyzing streaming data.
  • Business Intelligence: Integration with Power BI for reporting and visualization.

At its core, Fabric uses a centralized data storage system called OneLake, which aims to provide a single, unified repository for an organization’s data. It caters to various roles — data engineers, data scientists, and business analysts — offering tailored tools to streamline workflows and improve productivity. Launched into general availability in late 2023, Fabric is positioned as a comprehensive solution to meet the growing demands of data-driven organizations.

Why Is It Considered Another Failure of Microsoft Services?

Despite Microsoft’s promises of a revolutionary, unified analytics platform, Microsoft Fabric has faced significant criticism, leading some to label it as another failure in the company’s history of service offerings. Below are the key reasons behind this perception:

1. Early-Stage Challenges

Since Fabric is still a relatively new platform, it has encountered typical early-stage issues. Users have reported:

  • Bugs and Performance Issues: The platform has been plagued by reliability problems and slow performance in some cases.
  • Steep Learning Curve: Mastering its various components requires significant time and effort, which has frustrated early adopters.

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Ryan Arjun
Ryan Arjun

Written by Ryan Arjun

BI Specialist || Azure || AWS || GCP — SQL|Python|PySpark — Talend, Alteryx, SSIS — PowerBI, Tableau, SSRS

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