• Full BI-Stack Automation: From source to data warehouse through to frontend.
• Holistic Data Model: Complete view of the entire Data Model. This also allows for rapid prototyping of various models.
• Data Warehouses: MS SQL Server 2012-2022, Azure SQL Database, Azure Synapse Analytics dedicated, Azure SQL Managed Instance, SQL Server on Azure VMs, MS Fabric SQL.
• Analytical Databases: SSAS Tabular Databases, SSAS Multidimensional Databases, Azure Synapse Analytics dedicated, Power BI, Power BI Premium, Duck Db, Tableau, and Qlik Sense.
• Data Lakes: MS Azure Blob Storage, Onelake.
• Frontends: Power BI, Qlik Sense, Tableau, PowerPivot (Excel).
• Pipelines/ETL: SQL Server Integration Packages (SSIS), Azure Data Factory 2.0 pipelines, Azure Data Bricks, Fabric Data Factory.
• Azure: Azure SQL Server, Azure Data Factory Pipelines.
• Deployment: Visual Studio Solution (SSDT), Creation of DACPAC files, SSIS packages, Data Factory ARM templates, XMLA files.
• Modelling Approaches: Top-down modelling, Bottom-up modelling, import from external modelling tool, Dimensional/Kimball, Data Vault 2.0, Mixed approach of DV 2.0 and Kimball (A combination the best of both worlds by using elements of both Data Vault 2.0 and Kimball modelling), Inmon, 3NF, or any custom data model. The AnalyticsCreator wizard can help you create a data vault model automatically and also supports strict Dan Linstead techniques and data vaults.
• Historization Approaches: Slowly changing dimensions (SCD) type 0, type 1, type 2, mixed, SnapShot historization, Gapless historization, Change-based calculations.
• Surrogate Key: Auto-increment, long integer, Hash key, custom definition of hash algorithm.