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Microsoft Corporation

Microsoft Fabric

Composite Score

8.1 /10

CX Score

8.7 /10

17 Reviews Write a Review

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What is Microsoft Fabric?

Microsoft Fabric is a platform that allows users to get, create, share, and visualize data using an array of tools. Give your data teams all the tools they need in a unified experience that helps reduce the cost and effort of data integration, governance, and security.

Company Details

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Awards & Recognition

Microsoft Fabric won the following awards in the Machine Learning Platforms category

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6 Top Rated Capabilities

5 Top Rated Features

Latest Award, 2025

2024 Emotional Footprint Champion

2024

Strategy and Innovation
Service Experience
Product Impact
Contract Negotiation
Conflict Resolution

2024

Microsoft Fabric Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on Microsoft Fabric.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

90 Likeliness to Recommend

100 Plan to Renew

90 Satisfaction of Cost Relative to Value

2
Since last award

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Emotional Footprint Overview

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+99 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love Microsoft Fabric?

0% Negative

0% Neutral

100% Positive

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Feature Ratings

Average 81

Performance and Scalability

Data Ingestion

Openness and Flexibility

Ensembling

Model Monitoring and Management

Explainability

Data Exploration and Visualization

Pre-Packaged AI/ML Services

Algorithm Diversity

Data Pre-Processing

Data Labeling

Vendor Capability Ratings

Average 82

Quality of Features

Business Value Created

Breadth of Features

Ease of Data Integration

Product Strategy and Rate of Improvement

Usability and Intuitiveness

Ease of IT Administration

Ease of Implementation

Vendor Support

Ease of Customization

Availability and Quality of Training

Microsoft Fabric Reviews

SOMTO E.

Role: Information Technology
Industry: Technology
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Jul 2025

All-in-One Analytics Powerhouse

Likeliness to Recommend

9 /10

What differentiates Microsoft Fabric from other similar products?

Unified "OneLake" Architecture Single data lake for everything: Ingest, store, and analyze all data types (structured, semi-structured, unstructured) without silos. Native Integration with Power BI & Microsoft Stack

What is your favorite aspect of this product?

All-in-One Analytics Powerhouse

What do you dislike most about this product?

Teams/SharePoint integration is a double-edged sword: Great for Microsoft shops but alienates non-Office users.

What recommendations would you give to someone considering this product?

i will strongly recommend but i must warn that you must learn how to manage cost because it's not for learners

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Abiodun S.

Role: Industry Specific Role
Industry: Technology
Involvement: IT Leader or Manager

Validated Review

Verified Reviewer

Submitted May 2025

Streamlining Data Analytics"

Likeliness to Recommend

9 /10

What differentiates Microsoft Fabric from other similar products?

Unified Analytics Platform: Fabric integrates various data and analytics tools into a single platform, streamlining workflows and reducing complexity. - Lake-Centric Architecture: OneLake, a built-in SaaS data lake, provides a unified storage system for all organizational data, eliminating data silos and enabling easy discovery and sharing.

What is your favorite aspect of this product?

Unified Analytics Platform: Bringing together various data and analytics tools into a single platform. - AI-Powered Capabilities: Utilizing AI features like Copilot to generate insights and streamline workflows.

What do you dislike most about this product?

Complexity: Steep learning curve due to the platform's extensive features and capabilities. - Cost: High costs associated with using advanced features, large-scale deployments, or extensive data processing.

What recommendations would you give to someone considering this product?

Define Clear Business Objectives: Identify specific business problems or opportunities that Fabric can address. - Assess Data Readiness: Evaluate the quality, structure, and accessibility of your data. - Evaluate Skill Sets: Consider the technical expertise required to effectively utilize Fabric. - Plan for Integration: Think about how Fabric will integrate with existing infrastructure, applications, and workflows.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Antonio P.

Role: Consultant
Industry: Transportation
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Mar 2025

Best datalake, ecosystem of products, BI in once

Likeliness to Recommend

10 /10

What differentiates Microsoft Fabric from other similar products?

Amazing datalake, software ecosystem and copilot AI features for data modeling and BI

What is your favorite aspect of this product?

Whole ecosystem integrated, AI capabilities for reporting and data visualization

What do you dislike most about this product?

Cost and fees with tokens

What recommendations would you give to someone considering this product?

If you are in a large corporate and can afford recurring subscription fees, it is definitely a must-have if dealing with big data, ML and BI

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Microsoft Fabric

What is Microsoft Fabric?

Company Details

Need Assistance?

Awards & Recognition

2024 Emotional Footprint Champion

Microsoft Fabric Ratings

90 Likeliness to Recommend

100 Plan to Renew

90 Satisfaction of Cost Relative to Value

2 Since last award

Emotional Footprint Overview

+99 Net Emotional Footprint

How much do users love Microsoft Fabric?

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Performance and Scalability Systems performance (time) and scalability end-to-end: from data load and processing to model creation and deployment.

Data Ingestion Ability to access data from various sources on-prem and in the cloud and of various type: structured, unstructured, and semi-structured, real-time, etc.

Openness and Flexibility Integration with open-source and 3P resources (languages, frameworks, libraries, etc.)

Ensembling 'Ability to combine ML models for best results.

Model Monitoring and Management Ability to monitor model use and performance in production, incl. identifying models for refresh and/or replacement.

Explainability Ability to explain/ visualize the model.

Data Exploration and Visualization Ability to visually manipulate, interact with, and explore data, and perform basic descriptive statistics and pattern detection.

Pre-Packaged AI/ML Services Pre-trained models and associated resources, e.g., for forecasting, recommendations, image and video analysis, NLP, voice, etc.

Algorithm Diversity Provides multiple diverse ready-to-use machine learning algorithms out-of-the-box.

Data Pre-Processing Ability to wrangle or pre-process data to ready it for model training.

Data Labeling Ability to annotate/ label data to create a training data set.

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Microsoft Fabric Reviews

SOMTO E.

All-in-One Analytics Powerhouse

Likeliness to Recommend

Pros

Abiodun S.

Streamlining Data Analytics"

Likeliness to Recommend

Pros

Antonio P.

Best datalake, ecosystem of products, BI in once

Likeliness to Recommend

Pros

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2
Since last award

Feature Ratings

Performance and Scalability

Data Ingestion

Openness and Flexibility

Ensembling

Model Monitoring and Management

Explainability

Data Exploration and Visualization

Pre-Packaged AI/ML Services

Algorithm Diversity

Data Pre-Processing

Data Labeling

Vendor Capability Ratings

Quality of Features

Business Value Created

Breadth of Features

Ease of Data Integration

Product Strategy and Rate of Improvement

Usability and Intuitiveness

Ease of IT Administration

Ease of Implementation

Vendor Support

Ease of Customization

Availability and Quality of Training