Microsoft Fabric consulting, implementation & migration services

MMC Global supports Fabric readiness and strategy, architecture, implementation, workspace and workload configuration, pipeline and data engineering, lakehouse and warehouse delivery, Power BI and semantic model development, integration, migration, governance, performance optimization, and managed support. We can own a defined workstream or deliver the program with your internal data and business teams.

That depends on your use cases, current Microsoft investments, data volumes and latency, team skills, security requirements, integration landscape, and capacity economics. A readiness assessment compares the target Fabric architecture with retaining, consolidating, or integrating existing services so the recommendation is based on fit rather than a platform-first assumption.

We can plan and execute migrations of relevant pipelines, data lakes, warehouses, notebooks, semantic models, and reports from environments such as Azure Synapse, Azure Data Factory, SQL-based platforms, and legacy Power BI estates. Other source platforms are assessed individually. Every migration includes dependency mapping, data-quality rules, reconciliation, performance testing, cutover planning, and rollback considerations.

Yes, subject to the capabilities and access methods of each source. Fabric can be connected through supported connectors, gateways, APIs, event interfaces, files, pipelines, and OneLake shortcuts. We define ownership, refresh or latency needs, security, failure handling, monitoring, and reconciliation before choosing the integration pattern.

Customization is primarily architectural and operational: workload selection, workspace and domain structure, lakehouse or warehouse design, pipelines, notebooks, data models, security, semantic models, reports, deployment automation, monitoring, and support processes. We favor maintainable platform-native patterns and document the decisions your team will need to operate and extend.

We design access around user and workload responsibilities, establish workspace and data-product standards, define ownership and lineage, apply sensitivity and sharing controls, and integrate Microsoft Purview where it fits the governance model. Performance work includes pipeline, Spark, SQL, semantic-model, Direct Lake, storage, and capacity analysis based on the workloads actually in use.

Timing varies with the number of sources, data quality, use cases, security approvals, integration complexity, report and model inventory, migration volume, and rollout approach. We use discovery to produce a phased estimate with milestones, dependencies, acceptance criteria, and an initial production scope instead of promising an arbitrary fixed duration.

Engagements can be structured as a readiness assessment, focused pilot, defined implementation or migration, a specialist workstream alongside your team, or ongoing managed support. Support can cover production stabilization, incident and problem resolution, monitoring, release assistance, capacity and performance optimization, knowledge transfer, and planned enhancements.

Our approach connects platform decisions to business use cases, data ownership, integration dependencies, operational responsibilities, and measurable acceptance criteria. You receive a transparent delivery plan, documented architecture and controls, structured validation, and a clear transition from implementation into internal ownership or ongoing support—without unsupported partnership claims or one-size-fits-all promises.