Experienced cloud data engineering Firm in Kitchener

Microsoft Fabric

Build custom business apps for mobile or desktop without heavy coding. Alphavima configures Microsoft Fabric for Kitchener teams managing operational workflows that need to work on phones, tablets, and desktops. All apps connect to Microsoft Dataverse for centralized, secure data storage.

Azure Synapse Analytics

For Kitchener organizations with large-scale analytical workloads, we design and implement Azure Synapse Analytics environments – including dedicated SQL pools for structured reporting, serverless SQL pools for ad hoc exploration, and Synapse Pipelines for orchestrated data movement. Our Synapse implementations cover the full data warehouse stack: dimensional modeling, fact and dimension tables, incremental load patterns using change data capture, and Power BI integration. Kitchener enterprises get a fully governed data warehouse on Synapse with role-based access control and column-level security.

Azure Data Factory (ADF)

We build, monitor, and maintain Azure Data Factory pipelines that move and convert data between your source systems – ERP, CRM, databases, flat files, APIs – and your Azure data platform. Each pipeline includes error handling, retry logic, failure alerting, and logging to Azure Monitor. Our ADF implementations for Kitchener businesses use parameterized Datasets, reusable Activities, and metadata-driven patterns to reduce hard-coding and make pipelines maintainable by your Kitchener team after handoff. ADF pipelines are built, tested, and deployed through Azure DevOps CI/CD – not manually uploaded to production.

OneLake and Data Lakehouse Architecture

We design and implement OneLake-based data lakehouse architectures using the medallion pattern – Bronze for raw ingested data, Silver for cleaned and conformed data, and Gold for business-ready aggregated datasets. Each layer is stored in Delta Lake format with full schema enforcement, time travel, and ACID transaction support. For Kitchener organizations moving away from legacy data warehouses, we migrate existing SQL Server or on-premises warehouse schemas to a lakehouse architecture on Azure – preserving historical data, refactoring transformation logic from SSIS or stored procedures into Delta Lake-compatible pipelines, and delivering a unified data model accessible from Fabric and Power BI. All medallion layers sit in OneLake and are queryable via SQL, Spark, or Power BI without copying data.

Data Governance with Microsoft Purview

We implement Microsoft Purview as the governance layer across your Azure data estate – cataloguing data assets, applying sensitivity labels, setting up data lineage tracking, and defining access policies that align with your Kitchener organization’s compliance requirements. Purview connects to Fabric, Synapse, ADF, and Azure Data Lake Storage automatically to capture metadata without manual documentation. Data quality is enforced at the pipeline level – validation rules, null checks, referential integrity checks, and duplicate detection – with failed records routed to a quarantine layer for review. Sensitivity labels applied via Purview propagate from source tables to Power BI reports automatically – one policy update, platform-wide effect.

Power BI and Analytics Layer

We build and publish Power BI semantic models directly from the Gold layer of your lakehouse – with pre-defined measures, hierarchies, relationships, and row-level security tested against your Kitchener reporting requirements. Every cloud data engineering engagement ends with a working Power BI dataset and at least one reference report your team can use and extend independently. Kitchener executives get real-time dashboards instead of overnight Excel files – with drill-through, filters, and scheduled refresh built in from day one.