Stop Stitching Together Data Tools. Microsoft Fabric Is the Unification.

Microsoft Fabric is a unified analytics platform launched in 2024 that combines what used to be separate Microsoft data products into one experience: Data Engineering (Lakehouse + Warehouse on OneLake), Data Factory (ETL/ELT), Data Science (notebooks + ML), Real-Time Intelligence (formerly Streaming), and Power BI. Synapse was the predecessor for warehousing + Spark; Fabric supersedes it with a unified storage foundation (OneLake) and a single licensing/admin model. New Daxonet engagements default to Fabric; existing Synapse clients migrate when their workload patterns and licensing make it economic.

Probably yes — but the timing depends on your specific Synapse usage. If you use mostly Synapse Dedicated Pools (DW SQL), Fabric Warehouse is the natural successor and migration is straightforward. If you use mostly Synapse Spark + Pipelines, Fabric Lakehouse + Data Factory is the path; migration is medium-effort. If you've heavily customised Synapse with private endpoints, custom Spark configurations, and integrated Azure ML, the migration is more involved and benefits from the Daxonet Migration Path 2 below. We start with a 2-week assessment that scores your specific environment and produces a recommendation.

OneLake is the single, organisation-wide data lake that underpins Fabric — Microsoft calls it 'the OneDrive of data'. Every workspace, workload, and product writes to OneLake by default. The practical impact: one copy of your data across all Fabric workloads (Lakehouse, Warehouse, Power BI, Data Science, Real-Time), no ETL between products, governance policies applied once. The 'data mesh + data lake' architectural debate gets resolved by the platform, not by your architecture team.

8-14 weeks elapsed for a single-domain implementation (e.g. finance reporting platform, customer 360, manufacturing data platform). Multi-domain (3+ business areas) runs in waves and totals 4-8 months. Critical sequencing: foundation first (workspaces, OneLake, governance, security), then ingestion, then workloads, then visualisation. Skipping foundation work to ship Power BI faster is the most common cause of expensive rework.

Fabric handles: enterprise BI / Power BI consolidation, data warehousing (small-to-large), data lakehouse (medium), batch ETL, light real-time streaming, data science / ML on enterprise data, AI / Copilot data foundation, regulatory reporting. Still better in other tools: very-large-scale streaming with sub-100ms latency (use Azure Event Hubs + Stream Analytics), specialised graph databases (Cosmos DB Gremlin), high-frequency operational stores (Cosmos / Azure SQL). We're honest about the boundary — Fabric is not a universal solvent.

Yes. Fabric supports 'shortcuts' that create live virtual references to data in ADLS Gen2, S3, Synapse Dedicated SQL Pools, and SQL Server — meaning Fabric can query your existing data without copying it. This is the recommended pattern for hybrid migrations: stand up Fabric, point shortcuts at existing storage, build new workloads in Fabric, migrate legacy workloads gradually. We've delivered this pattern at multiple Malaysian enterprises with mixed Microsoft data estates.

It depends on workload mix. Fabric uses a single capacity-based licensing model (Fabric Capacity Units) that covers all workloads. For organisations consolidating from multiple separate licences (Synapse + ADF + Power BI Premium + Streaming + ML), Fabric is typically 20-40% cheaper at equivalent capacity. For organisations with very-large-scale, single-workload usage, the saving is smaller. Daxonet's assessment includes a cost model comparison: current state vs. Fabric target state, with sensitivity analysis on capacity choice.

Yes for qualifying enterprise scope. Fabric is a strategic Microsoft platform with active FastTrack engagement. Daxonet co-delivers with Microsoft FastTrack for eligible engagements — specifically benefits the foundation phase (governance, security, capacity sizing) and the migration assessment phase. For Business Central / mid-market scope without FastTrack eligibility, Daxonet uses the same methodology with our own quality gates.