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Microsoft Fabric services
Microsoft Fabric services we provide
Consulting
Our experts provide comprehensive Microsoft Fabric consulting services, designing tailored implementation strategies and evaluating implementation readiness, project ROI, and possible bottlenecks. This way, we help organizations reduce project risks, accelerate deployment, and maximize the data platform’s business value.
- Define high-value Microsoft Fabric use cases, recommend the most suitable capabilities, create comprehensive data and analytics strategies, and develop implementation roadmaps for the project’s step-by-step rollout
- Design a scalable Microsoft Fabric architecture, offering recommendations for effective data storage and migration, solution integration and customization, and artificial intelligence capabilities
- Help establish governance, security, and compliance frameworks using dedicated Microsoft Fabric capabilities and Microsoft Purview to ensure secure, reliable, and long-term platform usage
Implementation
We implement Microsoft Fabric solutions tailored to your business needs, establishing a unified data platform that enables reliable data management, the delivery of accurate insights, and long-term scalability.
- Configure workspaces, capacities, access controls, data governance settings, and platform integrations to align the solution with your company’s business workflows
- Implement and optimize data lakehouses, warehouses, and data pipelines, migrate existing data and analytics assets if needed, and integrate the Microsoft Fabric solution with enterprise data sources and systems
- Validate the solution’s operation through testing, optimizing it if necessary, and deliver data engineering, advanced analytics, and business intelligence capabilities to the production environment
License & cost optimization
Relying on our deep Microsoft expertise and product knowledge, we help you select a suitable Microsoft Fabric licensing model or optimize existing expenses, balancing the platform’s functionality, performance, and overall costs.
- Analyze data platform, user roles, and analytics and reporting requirements to recommend the right Fabric SKU and capacity sizing
- Review current license and capacity utilization to identify underused resources and remove unnecessary costs
- Provide cost-saving recommendations for licensing, capacity, and workload optimization as business needs evolve
Migration
We transfer data, analytics workloads and processes, and supporting assets, including metadata, security configurations, and deployment pipelines, from legacy platforms to the Microsoft Fabric system, ensuring successful analytics workflows and data movement with minimized risks of business operations disruption.
- Map data assets, datasets, and workloads from legacy systems, define their structure in Microsoft Fabric and OneLake environments, supporting structured migration and preserving data relationships
- Transition legacy data architectures to the Fabric-based platform
- Validate migrated workloads, assets, and data quality, as well as post-migration platform performance
Integration
We integrate Microsoft Fabric with your existing business systems, applications, and data sources, enabling seamless data exchange, improved data accessibility, and broader data analytics capabilities.
- Implement automated data ingestion, synchronization, and transformation workflows using Fabric Data Factory
- Extend Fabric’s AI capabilities by integrating it with Azure Machine Learning to build, train, deploy, and monitor AI models at scale
- Connect Fabric with other Microsoft solutions, including Power BI, Microsoft Teams, Dynamics 365, Power Apps, and Azure services, enabling enhanced collaboration and reporting
- Integrate third-party business applications (ERP and CRM solutions), marketing platforms, data warehouses and cloud platforms (Amazon S3, Snowflake), and data processing frameworks (like Apache Spark) with Microsoft Fabric
User training & system maintenance
Our team offers comprehensive post-implementation support, maximizing the solution’s value through facilitating end-user adoption, as well as ensuring high long-term performance and alignment with evolving business needs and regular software updates.
- Deliver role-based training programs and documentation for business users, data engineers, administrators, and other specialists to accelerate Microsoft Fabric tools adoption and time-to-value
- Monitor solution performance, scalability, and usability to timely identify and eliminate performance issues and capacity constraints
- Support ongoing enhancements and updates as business needs evolve
Microsoft Fabric capabilities we implement
We help businesses maximize the value of Microsoft Fabric solutions leveraging platform capabilities that best support their business needs, data strategy, and analytics requirements. The core Microsoft Fabric capabilities include but are not limited to:
Unified data platform
Utilize Microsoft Fabric’s data engineering, management, and storage capabilities to consolidate enterprise data into a unified environment built on OneLake, centralize access to data from various sources, reduce silos, and enable consistent analytics across the organization.
Business intelligence
Transform raw historical business data into actionable insights with the help of Microsoft Power BI through semantic models and immersive visualizations, such as dashboards and reports, to enable self-service analytics, improved performance monitoring, and trend identification.
Real-time analytics
Monitor and analyze data real-time to make quick business decisions by instantly tracking KPIs, timely detecting anomalies, getting proactive alerts on critical metrics changes, and responding quickly to operational events before they affect performance and revenue.
AI & machine learning
Leverage Microsoft AI, machine learning, and data science functionality to automate analytics workflows, accelerate AI model development, and generate insights faster. Utilize Copilot across Fabric workloads to assist with data preparation, analytics, and natural language data exploration.
Governance & security
Protect sensitive enterprise data with Microsoft Purview’s governance, compliance, and sensitivity labeling. Leverage comprehensive OneLake catalogs and data discovery capabilities to maintain visibility and control over data assets.
Hire an experienced Microsoft Fabric implementation partner
How we approach Microsoft Fabric projects
To ensure successful Microsoft Fabric solution implementation, our experts follow an established end-to-end roadmap, adapting it to your business objectives and existing data landscapes as well as incorporating Microsoft best practices. The common steps Microsoft Fabric platform delivery include:
1
Discovery & data assessment
Data management needs and requirements analysis
Current data landscape assessment
Data analysis process gaps and needs identification
2
Solution design
OneLake data model design
Data ingestion and transformation approaches selection
Security, governance, and access control frameworks establishment
Microsoft Fabric licensing and capacity planning
3
Implementation
Fabric components setup and structure configuration
Workspace, capacity, and environment configuration
Lakehouse, data warehouses, semantic models, and other Fabric components implementation
Security roles, permissions, and governance controls configuration
ETL/ELT implementation and data integration
Data, reports, datasets, and analytics workloads migration
4
Testing & optimization
Data validation
Performance, security, and user acceptance (UAT) testing
Capacity and workload optimization
5
User adoption & ongoing support
Change management and user training
Performance monitoring and troubleshooting
On-demand capacity management and feature enhancements
Industry use cases
Microsoft Fabric provides robust capabilities for delivering tailored solutions across multiple industries, allowing businesses to streamline their specific data management workflows, enhance decision-making, drive value from their data, and accelerate their digital transformation initiatives.
Manufacturing
Integrate data from machinery sensors, ERP systems, and supply chain tools into a single environment to gain faster insights, improve operational visibility, optimize production performance, and maximize efficiency across plants.
Construction
Harness robust data management capabilities to combine field, project, finance, and resources data into a centralized platform and get insights for project progress monitoring, cost control, and informed decision-making based on live data.
Healthcare
Unify clinical, operational, and financial data from diverse sources and empower healthcare professionals with a fuller picture of the patients’ health and healthcare operations, leading to more accurate decision-making and improved overall patient outcomes.
Insurance
Leverage unified policy, claims, and customer data, as well as advanced analytical models and AI capabilities to better assess risks, improve underwriting accuracy, accelerate claims processing, adjust policy pricing, and deliver more personalized customer experiences.
Non-profit organizations
Consolidate data from donors, volunteers, programs, and finances to improve fundraising performance, efficiently track program impact, increase financial and operational transparency, and ensure informed decisions to maximize mission outcomes.
Financial services
Efficiently process transaction, risk, and financial data to enhance financial reporting, optimize transaction monitoring, strengthen governance and regulatory compliance, streamline risk management, and identify new revenue opportunities.
Logistics
Utilize consolidated supply chain, fleet, and warehouse data to optimize delivery routes, improve delivery predictability, reduce operational costs, and enhance supply chain resilience.
Retail
Analyze customer and operational data from various touchpoints and gain insights on customer behavior and product performance to optimize merchandising, personalize shopping experiences, and optimize inventory management.
Software & hi-tech
Integrate product telemetry, engineering, and customer data to analyze product performance and adoption, optimize software development and DevOps metrics, and drive innovation.
Our Microsoft Fabric projects best practices
When implementing Microsoft Fabric solutions, we adhere to proven best practices to ensure efficient and fast implementations and establish a reliable foundation for data analytics, AI tools, and business intelligence.
Clear workspace organization
We create separate workspaces for different business domains, teams, or analytical workloads, logically grouping the components of your Microsoft Fabric data platform. This approach helps ensure clear workspace and data assets ownership, easier management, as well as effective cross-team dataflows and collaboration.
DevOps & CI/CD
Our experts use robust version control, environment management practices, and CI/CD pipelines to ensure controlled implementation and testing of Microsoft Fabric assets. This way, we reduce implementation risks and enable seamless updates across data environments.
Medallion architecture pattern
We prioritize the use of the medallion architecture pattern, organizing data into three progressive layers - Bronze (raw), Silver (cleansed), and Gold (business-ready). This approach, especially suitable for Fabric Lakehouse implementations, enables data transformation and validation processes to be streamlined, as well as enhances overall data structure and simplifies governance.
Governance & security by design
Our team implements data governance, strict access controls, and lineage tracking in your data management architecture from day one to ensure reliable analytics results, reduce data silos, prevent unmanageable data sprawl, and minimize costly security vulnerabilities.
Unify and streamline data management with Microsoft Fabric
About Itransition
15+ years of experience in data analytics and business intelligence
Providing IT consulting and software engineering services since 1998
Certified Microsoft Solutions Partner since 2008
Certified BI solution specialists, data engineers, and security experts on board
Internal Microsoft Center of Excellence
Adherence to ISO 27001 and ISO 9001 quality and security management practices
FAQs
Microsoft Fabric is a cloud computing platform delivered as Software as a Service (SaaS) and designed to support the entire data lifecycle, including data ingestion, transformation, real-time processing, analysis, and visualization. This powerful platform encompasses various Microsoft data management tools, including Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Power BI and enables efficient data collection, storage, and analysis.
The main benefits of implementing Microsoft Fabric include, but are not limited to:
- Centralized data handling
Microsoft Fabric provides end-to-end data management functionality, combining data engineering, warehousing, BI, and governance into a single native interface. - Simple integration
As part of Microsoft 365, Fabric seamlessly connects with other Microsoft services, including Power BI, Azure, Dynamics 365, and Purview. - Scalability & flexibility
Fabric offers capabilities for a wide range of analytical workloads, from small tasks to large-scale data processing, allowing businesses to adjust capacity in accordance with their needs. - Fast time to value
With Microsoft Fabric’s consolidated data engineering, warehousing, and analytics capabilities, low infrastructure complexity, and prebuilt integrations, the data management solutions can be configured, set up, and deployed quickly. - Data-driven decisions enablement
Fabric’s built-in AI and machine learning capabilities and analytical tools allow for repetitive tasks automation and real-time insights generation, which drives faster, more informed decision-making.
For evaluation purposes, Microsoft Fabric offers a limited free trial. For long-term adopters, the platform offers a dual licensing system, combining capacity-based licensing and user licensing.
Fabric Capacity licenses (F-SKUs) are purchased in the form of Capacity Units (CU) via monthly commitment or on a pay-as-you-go basis, providing compute resources required for data warehousing, integration, engineering, and management. The users actively engaged in creating and managing Fabric content, including reports, semantic models, pipelines, notebooks, etc. typically require additional individual Power BI Pro or Premium Per User (PPU) licenses. This licensing approach enables companies to scale platform resources and user access in accordance with their unique business needs.
Microsoft Fabric provides multiple data management capabilities within a single SaaS platform. However, the solution also works alongside other technologies from Microsoft's broader data ecosystem. Here’s how it relates to some of the key Microsoft data services:
- Azure Synapse Analytics
Microsoft Fabric complements Azure Synapse Analytics by providing many similar analytics capabilities, such as data engineering, data warehousing, and analytics, within a unified SaaS platform that also integrates Power BI, Data Factory, AI capabilities, and OneLake. Azure Synapse Analytics remains a separate Azure service and continues to support organizations that require Azure-based analytics with greater infrastructure flexibility. - Microsoft Azure SQL Database
Azure SQL Database provides a relational database management system, specializing in data storage and retrieval and queries primarily structured data. Integrated with Microsoft Fabric, the system can process more complex datasets, including structured and unstructured data like images, videos, and sensor insights. - Microsoft Azure
Azure provides a comprehensive portfolio of cloud services that IT professionals can use to host enterprise applications, data workloads, and analytical solutions. Deployed on Azure, Fabric seamlessly leverages its infrastructure and services to deliver secure and scalable data storage, processing, and analytics solutions.
Microsoft Fabric unifies data from various sources by funneling it into OneLake that uses the Delta Lake storage format and bridging legacy and cloud environments through built-in Data Factory pipelines, database mirroring, gateways, and OneLake shortcuts. This structure enables access to the data without extensive duplication and allows for seamless cross-domain analytics.
The initial workload migration can be completed in 4 to 6 weeks. A full enterprise implementation, including data engineering, governance, and AI functionality setup can take up to 3 to 6 months. To get a more accurate scope and timeline estimate for your specific project, you can turn to our Microsoft consulting team.
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