Often business reporting is done based on the input data available from the different source systems available. This approach is wrong. In this course, we’ll take an output focused approach to capturing business events and metrics before turning those requirements into a source system agnostic data model. A logical data model that clearly represents the business functions, defined using business glossary terms. Once created, a new reporting/semantic layer can be forged using industry established star schema definitions, that ultimately allows any business user to explore and self-serve on the data products created.

Using techniques such as Business Event Analysis Modelling (BEAM), Kimble and Inmon data warehousing we’ll unlock value for the business, reverse engineering required outputs to available source system inputs. Delivered using an Azure SQL Database and Azure Analysis Services for data modelling, then reporting in Power BI, we’ll create an OLAP data schema that can be used with upstream data mappings and defined as a rich entity diagram. Every business needs this foundational data modelling support to apply governance, unlock valuable insights and later, delivery AI use cases.