There are at least two different approaches to design a holistic business and data model.

The bottom-up method, which is shown in the graphic below and the top-down method, which starts with the conceptual model first, although models can also be loaded from other modeling tools.

1. Connect AnalyticsCreator to any data source, especially databases, individual files, data lakes, cloud services, Excel files and other extracts. Build-in connectors to many common sources are available as well as support of Azure Data Factory, Azure Analytics.
2. Define Data - AnalyticsCreator extracts all metadata from the data sources, such as field descriptions, data types, key fields, and all relationships, which is stored in the AnalyticsCreator Metadata Repository. This will:
   1. Extract and capture DDL
   2. Detect structure changes and forward in all higher layers.
3. Cognitive Suggestion- Intelligent wizards help to create a draft version of the model across all layers of the data analytics platform. Choose different modelling approaches or create your own approach:
   1. Data Vault 2.0, dimensional, 3 NF, own
   2. Historical data handling (SCD, Snapshot, CDC, Gapless, ..)
   3. Use Azure DevOps
4. Model- The entire toolset of AnalyticsCreator is at your disposal to further develop the draft model. Behind the holistic graphical model, the generated code is already finished and can be also modified manually, including:
   1. Automated transformations and wizards
   2. Collaboration
   3. Development process supported by data lineage flow-chart
   4. Own scripting and macros are possible
5. Deploy - To deploy the Data model in different environments (Test, Prod, ..), AnalyticsCreator generates deployment packages that are also used for the change process of structures and loadings. Deployment packages can be used locally, in Fabric, Azure as well in hybrid environments. This includes:
   1. Stored procedures, SSIS
   2. Azure SQL DB, Azure Analysis Services, Synapse
   3. ARM Template for Azure Data Factory
   4. Tabular Models, OLAP Cubes
   5. Power BI
   6. Tableau
   7. Qlik