Lakehouses, pipelines and Power BI on one Microsoft Fabric platform.
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§ Signs
As a Microsoft partner, we design and implement Microsoft Fabric platforms that bring data engineering, warehousing, real-time data and Power BI together on OneLake. Our Fabric data engineering work covers Data Factory pipelines and Dataflow Gen2, lakehouse and warehouse development, medallion layers, notebooks in Python, PySpark and SQL, and Eventstream for real-time intelligence. We plan capacity and CU utilization, optimize Direct Lake models, secure workspaces, and migrate SQL Server and Azure sources into Fabric so your reports run on governed, current data.
Fabric is most valuable when it replaces moving parts, not when it is added as one more tool.
Microsoft is moving Premium capacity customers to Fabric capacities, and you need to know what to buy and what changes.
Data Factory, Synapse, a data lake and Power BI each have their own security, monitoring and bill.
Reports slow down at month end because background refreshes and interactive queries compete for the same capacity.
Hundreds of workspaces, no naming rules and no clear separation of development, test and production.
Each semantic model imports its own copy of the same tables, and Direct Lake has never been evaluated.
§ What we deliver
Choose an area to see the services in it.
Microsoft FabricOneLakeFabric Data FactoryDataflow Gen2Eventstream
Power BIMicrosoft Fabric§ Proof
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§ Approach
We review your sources, existing Azure and SQL Server estate, Power BI usage and capacity needs.
You receive Fabric readiness assessment and roadmap
Workspaces, lakehouses and warehouses, medallion layers, security and capacity are designed together.
You receive Fabric architecture and capacity plan
Pipelines, Dataflow Gen2, notebooks and semantic models are built with error handling and monitoring.
You receive Working pipelines and semantic models with monitoring
SQL Server and Azure sources are moved into Fabric in phases and reconciled before reports switch over.
You receive Migration waves with reconciliation reports
We tune CU usage, Direct Lake models and refresh patterns as usage grows.
You receive Capacity and performance review
We set workspace standards, admin settings and a request process, and coach your team so Fabric grows in a controlled way.
You receive Governance guide, capacity alerts and team walkthroughs
§ Tech stack
Microsoft FabricOneLakeFabric Data FactoryDataflow Gen2EventstreamPower BI
Azure DevOps§ Engagement models
A defined scope, timeline and deliverables, from design through go-live.
An agreed price for a clearly scoped implementation, such as a migration or a new warehouse.
Our engineers work under your contract, or as a subcontractor to consulting firms and system integrators.
Data engineers who join your team and work in your tools and processes.
Consultants and developers working remotely, with overlap in your working hours.
Architecture reviews, platform choices and design guidance for your own team.
Monitoring, incident handling and ongoing fixes for pipelines and databases in production.
A short, fixed-scope engagement to test an approach on your data or plan a migration.
§ FAQs
Fabric brings data integration, lakehouse and warehouse storage, real-time data and Power BI onto one platform over OneLake. Depending on your estate it can consolidate separate Data Factory, Synapse and Power BI workloads.
Yes. Migrating SQL Server and Azure sources to Microsoft Fabric is one of our specialized consulting services, delivered in phases with reconciliation so reports keep working.
Through capacity planning and CU utilization optimization: sizing capacity to workloads, scheduling heavy jobs, tuning notebooks and pipelines, and using incremental loads instead of full refreshes.
Direct Lake lets Power BI semantic models read Delta tables in OneLake directly, without scheduled import refreshes. We help decide where Direct Lake, DirectQuery or Import fits, and optimize the models.
Yes. We integrate Real-Time Intelligence and Eventstream for streaming data alongside batch pipelines.
By measurement, not by guess. We list your workloads, run representative loads on a trial or small F SKU, read the Capacity Metrics app and only then recommend a size. Buying a large SKU before sizing is the most common avoidable cost.
A lakehouse suits Spark and Python work, semi-structured data and data science. A warehouse suits T-SQL teams and multi-table transactions. Both store Delta tables in OneLake, so many platforms use both, each for what it does best.
Yes. Dedicated SQL pools move to a Fabric warehouse, Spark notebooks to Fabric notebooks and pipelines to Fabric Data Factory, with each step validated against the source before users switch.
Yes. OneLake shortcuts read data where it already lives, including ADLS and Amazon S3, and mirroring keeps a replica of supported sources such as Azure SQL Database and Snowflake in OneLake.
With Git integration to Azure DevOps or GitHub, deployment pipelines between workspaces, and parameterized connections, so changes are reviewed and promoted rather than edited in production.
§ In detail
An inventory of your Azure and Power BI estate, with a capacity and licensing recommendation based on measured usage.
Domains, workspaces per environment, a lakehouse or warehouse decision per workload, and shortcuts to existing storage.
Data Factory pipelines, Dataflow Gen2 and PySpark notebooks under Git integration and deployment pipelines.
Models built on OneLake tables where Direct Lake suits the size and usage, with the fallback behavior tested, not assumed.
Workspace roles, OneLake security, sensitivity labels and Microsoft Purview integration for discovery and lineage.
The Capacity Metrics app set up with alerts, plus guidance on scaling, pausing and scheduling heavy jobs.
Fabric is often owned by BI teams. We add data engineering practice, such as Git, testing and CI/CD, without taking reports away from them.
We help define workspace standards, tenant settings and a request process so self-service stays safe.
We prove capacity sizing and governance on a single business domain before rolling Fabric out wider.
As a Microsoft partner we keep track of Fabric's fast release cycle and tell you which new features are ready for production.
Practice management, time and finance data combined in OneLake for matter and client profitability reporting.
Line telemetry through Eventstream and KQL databases, next to ERP data in the lakehouse.
Workspace isolation and sensitivity labels for patient data, designed around HIPAA and state privacy rules.
Store, online and supply chain data in one lakehouse, with Power BI reading it through Direct Lake.
§ Contact
Moving to Fabric or getting more from it? Tell us about your sources and reports.
