Fabric

Microsoft Fabric is an integrated data and analytics platform that includes integration, lakehouse, data warehouse, real-time analytics, and Power BI. We help streamline your data architecture and shorten the path from source to decision.

Schedule an appointment

Fabric 's implementations demonstrate faster onboarding and less manual work.

90%

less data processing

25%

higher productivity

end-to-end data platform

✦

The Challenge

Data is growing faster than the company's ability to use it

Tools create silos

Separate tools for integration, data storage, and reporting result in duplicate data, inconsistent KPI definitions, and rising maintenance costs.

The report shows the past

Long loading times and manual data preparation delay the analysis, so decisions are made based on an outdated picture of the situation.

There are several versions of KPIs

Departments build their own models and spreadsheets, so the same metrics yield different results, and meetings are used to reconcile numbers rather than make decisions.

AI lacks a stable foundation

Undescribed, inconsistent, and hard-to-access data limit the quality of models and agents, which is why AI projects remain at the experimental stage.

✦

How It Works

From Dispersed Sources to Shared Data, Analytics, and Actions

Fabric It integrates data into OneLake, allows you to prepare and share it with multiple teams, and then use it for Power BI, real-time analytics, and AI.

Combine the sources

Select the data you want to copy, replicate, stream, or share via shortcuts.

Agree on a model

Define the data, quality standards, owners, and common metrics for the selected area.

Share the result

Power reports, real-time analytics, data models, and AI solutions.

Measure and Scale

Monitor the quality, capacity utilization, costs, and value of each use case.

THE LOOP CLOSES WITH DATA

✦

Pillars

The Two Pillars of Microsoft Fabric: A Shared Data Foundation and Faster Adoption

A single data architecture instead of more silos

OneLake and a shared working model minimize duplication, point integrations, and multiple versions of the same data.

The OneLake Common Layer

Many engines use the data without creating separate copies.

Consistent data and metrics

The teams work based on agreed-upon models and KPI definitions.

Visible origin

The catalog and lineage help determine the source and owner of the data.

Controlled access

Roles and policies filter data based on the user and their needs.

From batch and stream data to action

The same ecosystem supports reporting, real-time events, advanced analytics, and data for AI.

Shorter time to report

Automated workflows reduce the need for manual data merging and preparation.

Decisions Made Closer to the Event

Real-Time Intelligence detects conditions that require a response.

Power BI without unnecessary copies

Direct Lake shortens the path from data to business analytics.

Data Ready for AI

Agreed-upon sources enhance the usefulness of models and agents.

✦

Photos

See how it works

What Is Microsoft Fabric ? A Data and Analytics Platform

Microsoft Fabric is a SaaS platform that combines integration, data engineering, data warehousing, real-time analytics, data science, and Power BI on the OneLake foundation.

OneLake and OneLake Catalog

They reduce silos and help you find, share, and manage data.

Data Factory and Data Engineering

They automate data preparation and reduce the time it takes to feed data into analyses.

Warehouse and Real-Time Intelligence

They combine historical reporting with the analysis of incidents that require a rapid response.

Power BI and Copilot

They expedite the transition from agreed-upon data to analysis and the communication of findings.

Take a look inside

Where does Microsoft Fabric deliver the greatest business value?

The platform is ideal for situations where multiple systems feed into shared KPIs, reports need to be generated more quickly, and data is intended to support operations and AI.

Finance, Sales, and Marketing

Shared models integrate financial results, the pipeline, customers, and campaigns, reducing the need for manual reconciliation of reports across departments.

Manufacturing, Logistics, and Operations

ERP, inventory, IoT, and event data enable the early detection of deviations, downtime, delays, and inventory risks.

Customer Service, Product, and AI

The history of interactions and behaviors feeds into the company’s analyses, predictive models, and context-aware agents.