How does Microsoft Fabric integrate with existing Azure landscapes?

Fabric connects natively with Azure services and on-premise systems through OneLake and Data Factory shortcuts, allowing for a gradual modernization without disrupting existing operations.

Microsoft Fabric Consulting Services

Q: What is the difference between Microsoft Fabric and Databricks?

Microsoft Fabric provides a unified, SaaS-based experience integrating data engineering and Power BI, while Databricks is a specialized PaaS focused on advanced engineering and data science. The choice depends on your existing ecosystem and technical maturity.

Q: In which cases does Microsoft Fabric fit best for enterprise organisations?

It is ideal for organizations seeking a centralized, scalable platform with built-in governance, self-service analytics, and AI-readiness, especially when dealing with fragmented data silos.

When Do You Need Microsoft Fabric?

Microsoft Fabric consulting services are for organisations that want to build a scalable, secure, AI-ready data platform on Microsoft Fabric with Power BI for real-time insights and self-service analytics. We help consolidate analytics platforms, replace legacy data warehouses, and improve reporting with real-time, self-service insights.

Contact sales Learn more

Aleksandras Voitechovskis

Head of Data Solutions

[email protected]

Robertas Skardžius

Cloud & Data Business Manager

[email protected]

Why Choose Microsoft Fabric?

Modern & scalable data analytics platform

A scalable data infrastructure built around a centralised data platform and lakehouse architecture. This supports long-term growth, performance, and flexible analytics needs.

Unified data foundation

With a centralised data platform, all teams work with consistent and trusted data. This reduces data silos, improves data quality, and ensures everyone is using the same reliable information for reporting and decision-making.

Faster business insights

Built-in real-time analytics and interactive dashboards help teams move from raw data to insights faster. This means quicker answers to business questions and better support for day-to-day decisions.

AI-driven self-service analytics

Power BI, semantic data models, and Copilot enable business user-driven analytics without heavy reliance on IT teams. Users can explore data confidently while governance and data consistency are maintained.

Our Microsoft Fabric Expertise Areas

Architecture & platform setup

We design and implement Microsoft Fabric Lakehouse environments using Medallion architecture with clear Bronze, Silver, and Gold layers. This ensures your data is structured, reliable, and ready for analytics, reporting, and AI use cases.

Data integration & engineering

We build robust data pipelines in Microsoft Fabric, including CI/CD data pipelines for reliable deployments. Our team also develops Power BI semantic models to ensure your data is consistent, well-structured, and easy to use across the organisation.

Business intelligence & reporting

We modernise business intelligence with Power BI reporting, dashboards, and report development. This helps organisations replace legacy BI tools, improve data accessibility, and deliver clear, interactive insights to business users.

Advanced analytics & data science

We prepare your data for analytics and machine learning, enabling predictive and descriptive analytics, automated insights, and deeper data exploration. This helps organisations move beyond reporting and start using data to drive smarter decisions.

Our Microsoft Fabric Consulting Process

Analysis & design

We start with data analytics consulting to understand your business goals, data challenges, and technical landscape. This includes defining a clear data strategy, designing the right data analytics solution, and creating a scalable data architecture that supports both current and future needs.

Engineering & development

Our team delivers reliable data warehouse development, data pipeline development, and data integration using proven ETL development practices. This ensures your data flows smoothly from source systems into Microsoft Fabric, ready for reporting, analytics, and AI use cases.

Operational support

After launch, we provide ongoing data platform support, data quality management, and BI support services. We also focus on analytics optimisation to keep your platform performant, accurate, and aligned with evolving business needs.

Industries for Microsoft Fabric Consulting

Banking & finance

Banking data analytics

Regulatory compliance analytics

Financial analytics

Risk analytics

Manufacturing

Manufacturing data analytics

Data storage & processing

Production analytics

Workforce analytics

Wholesale / Retail

Retail data analytics

Supply chain analytics

Procurement analytics

Pricing analytics

Logistics

Logistics data analytics

Fleet analytics

Warehouse management analytics

Route analytics

Insurance

Insurance data analytics solutions

Underwriting, claims & risk analytics

Fraud detection & operational analytics

Regulatory-compliant BI & reporting

Case Studies

Microsoft Fabric implementation

Data analytics solution

Data services

Microsoft Fabric

FAQ

What is the difference between Microsoft Fabric and Databricks?

Microsoft Fabric focuses on an integrated experience across data engineering, analytics, and Power BI. Databricks is often used for advanced data engineering and data science workloads. The right choice depends on your data maturity, user needs, and existing technology stack.

In which cases does Microsoft Fabric fit best for enterprise organisations?

Microsoft Fabric is a strong fit for organisations that need a centralised, scalable data platform with reliable governance, self-service analytics, and AI-ready capabilities. It works especially well when data is spread across multiple systems, reporting is slow, or legacy platforms are becoming hard to maintain.

How does Microsoft Fabric integrate with our existing Azure and on-premise data landscape?

Microsoft Fabric connects easily with Azure services and supports secure data ingestion from on-premise systems. This means you can keep your existing setup, while gradually modernising your data platform without disrupting daily operations.