Data Warehousing with MS SQL Server

A high-performance data warehouse forms the backbone of data-driven organizations. It collects, structures, and historizes data from heterogeneous sources so that it is reliably available for analytics, reporting, and decision-making.

Microsoft SQL Server provides a mature and proven enterprise platform for data warehousing. Combined with Microsoft Fabric, it enables a modern, flexible, and scalable hybrid architecture — uniting stable on-premises data storage with cloud-based analytics and integration capabilities.

Our SQL Server and Microsoft Fabric–based solutions deliver a future-proof data platform that integrates existing systems seamlessly while paving the way toward cloud transformation.

Comeli with a Microsoft flag – symbolizing data warehousing with MS SQL Server and Microsoft Fabric.

Architecture

A structured data warehouse built on MS SQL Server requires a clearly defined target architecture. During the design phase, data sources, integration pathways, and data models are specified.

Standardized modeling approaches and documented transformation logic ensure that the platform remains transparent, maintainable, and scalable over time.

In hybrid scenarios involving Microsoft Fabric, the clear separation of operational data storage, analytical processing, and reporting layers is essential.

Governance

Beyond technical architecture, consistent data governance is critical. This includes defined data quality rules, versioning concepts, and clearly assigned responsibilities.

Structured ETL processes and transparent transformation logic ensure full traceability of data lineage and changes.

This is particularly important in regulated industries or audit-relevant environments.

Operations

Stable operation of a SQL Server data warehouse depends on performance optimization, structured access control, and well-defined deployment processes.

Scalability, maintainability, and monitoring are incorporated at the architectural level to ensure controlled growth as data volumes increase.

This ensures technical robustness and operational manageability — even in hybrid scenarios with Microsoft Fabric.

Use Cases

Data warehousing with MS SQL Server is commonly applied in the following contexts:

  • Hybrid data warehouses using SQL Server as the source system and Fabric as the analytics platform
  • Regulatory reporting in financial services and insurance
  • Departmental data marts with Power BI as the front-end
  • Integration platforms for operational systems and cloud applications
  • Migration of legacy DWH systems into a Microsoft Fabric environment

Capabilities

Schematic representation of a relational data warehouse model with tables and relationships.
  • Relational data warehousing with high performance and transactional integrity
  • Flexible deployment: on-premises, hybrid, or fully within Microsoft Fabric
  • Integration with OneLake and Data Factory for centralized data management
  • Linking SQL Server data with Fabric lakehouses and warehouses
  • Use of T-SQL, views, and stored procedures for standardized business logic
  • System versioning and historization for audit-compliant data storage
  • Automated ETL workflows using SSIS, Data Factory, or Spark notebooks
  • Direct integration with Power BI for dashboards, reporting, and self-service analytics
  • Security and access management via Azure Active Directory

Services

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We support you from architectural design through productive deployment — whether on-premises, in the cloud, or in hybrid environments:

  • Architecture design and data modeling (Data Vault, star schema, snowflake schema)
  • Modernization of existing SQL data warehouses and integration into Microsoft Fabric
  • Development and optimization of ETL processes using SSIS, Data Factory, and Spark
  • Configuration of OneLake connections and Fabric warehouse interfaces
  • Performance tuning, maintenance, and automation
  • Development of data marts and semantic layers for Power BI
  • Training and coaching for data engineers and BI teams

Frequently Asked Questions on Data Warehousing with MS SQL Server

This FAQ addresses topics that frequently arise in consulting engagements and training sessions. Each answer is concise and refers to additional material where appropriate. If your question is not listed, please feel free to contact us.

Comeli dragon leans against a “FAQ” sign and answers questions about Data Warehousing with MS SQL Server.

When is a hybrid architecture with SQL Server and Microsoft Fabric appropriate?

A hybrid architecture is particularly suitable when existing on-premises systems should continue to operate while cloud-based analytics and integration capabilities are required.

How is historization implemented in a SQL Server data warehouse?

Historization is achieved through structured data models, system versioning, and defined ETL processes that store changes in a traceable and audit-compliant manner.

Can an existing DWH be integrated into Microsoft Fabric?

Existing SQL Server data warehouses can be gradually integrated into a Fabric environment, for example by connecting to lakehouses or warehouses within OneLake.

What role does Power BI play in data warehousing with MS SQL Server?

Power BI serves as the analytics and reporting front-end. Through semantic layers and data marts, structured data is made accessible to business users and management.