They help you assess, design, implement, migrate, optimize, and run data and analytics workloads on Microsoft Fabric. That can include OneLake architecture, lakehouses and warehouses, Fabric Data Factory pipelines, Power BI semantic models, Real-Time Intelligence, governance, security, capacity planning, and support.

A Microsoft Fabric consultant turns your business, reporting, security, and performance requirements into a working Fabric architecture. That means deciding how capacities, domains, workspaces, lakehouses, warehouses, pipelines, and semantic models should be structured.

Usually a readiness assessment, capacity and workspace design, OneLake architecture, security setup, data ingestion and transformation pipelines, lakehouse or warehouse build, semantic models, Power BI integration, monitoring, deployment processes, documentation, and knowledge transfer.

No. Fabric fits best when you already rely on Microsoft Azure, Power BI, Microsoft 365, or SQL technologies and want to reduce fragmentation. We will tell you honestly if it is not the right call.

A partner reduces the risk of early architecture, migration, governance, and capacity decisions that are expensive to fix later. You get specialists across Power BI, data engineering, integration, cloud architecture, and governance without hiring every role permanently.

We work in a few models depending on how much delivery ownership you want to keep in-house: as an advisory partner for assessment and architecture, as a delivery team that owns implementation and migration, or side by side with your internal team. We agree the model up front so responsibilities stay clear.

There is no reliable flat rate. A focused readiness assessment costs far less than an enterprise migration involving hundreds of pipelines, semantic models, reports, security rules, and downstream dependencies.

The main drivers are the number and complexity of data sources, data volumes, pipeline count, reporting dependencies, migration scope, governance obligations, real-time workloads, and how many teams or business domains use the platform.

A focused readiness and architecture phase usually takes two to four weeks. A limited pilot often lands in about six to ten weeks. An enterprise implementation or complex migration can run several months.

Yes. We plan and deliver migrations from Power BI Premium, Azure Synapse, Azure Data Factory, SQL Server, Azure SQL, SSIS, SSAS, Power BI dataflows, legacy data warehouses, and other data platforms.

Yes. A Power BI Premium to Microsoft Fabric migration includes capacity analysis, workspace and dependency assessment, licensing considerations, deployment planning, semantic model validation, and post-migration performance monitoring.

Yes. We assess Synapse SQL, Spark, notebooks, pipelines, libraries, and configuration dependencies, then map each workload to the appropriate Fabric destination. Azure Data Factory pipelines can move to Data Factory in Fabric, be redesigned, or run in temporary coexistence.

We start by finding which workloads consume capacity, when demand peaks, and where teams create contention. Then we use capacity metrics, workload scheduling, architecture changes, model optimization, and capacity separation or resizing where justified.

Governance is designed into tenant, capacity, domain, workspace, and data architecture from the beginning. We define access models, ownership, deployment standards, data classification, lineage, sensitivity labels, auditing, and Microsoft Purview integration according to your requirements.

A Fabric lakehouse combines open data storage in OneLake with Spark-based data engineering and analytical access. A Fabric warehouse gives you a more traditional relational, T-SQL experience for structured data warehousing.

Power BI is built into Microsoft Fabric and can run on governed semantic models built from Fabric data. Direct Lake lets Power BI read data straight from OneLake without maintaining a separate imported copy for suitable workloads, and Excel users keep their familiar access.

Yes. Fabric Real-Time Intelligence handles event-driven and streaming scenarios through Eventstreams and Eventhouse. Fabric also provides data engineering, data science, semantic models, and governed data foundations that support machine learning, Copilot, and data-agent use cases.

Yes. Knowledge transfer is included throughout architecture, implementation, and migration work. We document decisions, operating processes, deployment patterns, support responsibilities, and the reasoning behind the chosen design.