English
Approach
Create a data analytics platform in five easy steps
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.
*Everything is done on the design level
(Use mouse over on the graphic for more info)
Model
Optimize draft
MODEL
Optimize draft / create your own model
The entire toolset of AC 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.
- Automated transformations and wizards
- Collaboration
- Development process supported by data lineage flow-chart
- Own scripting and macros possible
Deploy
Generate code & structure
DEPLOY
Generate code & structure
To deploy the DW 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 Azure as well in hybrid environments
- Stored procedures, SSIS
- Azure SQL DB, Azure Analysis Services, Synapse
- ARM Template for Azure Data Factory
- Tabular Models, OLAP Cubes
- Power BI
- Tabeau
- Qlik
Connect
Access to data
Connect
Access to data
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
- 3rd party connector 250+ data sources
- Support of Azure Data Factory, Azure Analytics
DEFINE
Describe data
DEFINE
Describe data
AC extract all metadata from the data sources, such as field descriptions, data types, key fields, and all relationships to create an AC metadata connector.
- Extract and capture DDL
- Detecting structure changes and forward in all higher layers
- Using existing metadata connectors from AnalyticsCreator cloud
- Ready to go metadata connectors for known source systems are available for download in the AC cloud and in the community.
COGNITIVE SUGGESTION
Intelligent wizard
Cognitive suggestion
Use the no code approach with wizards or develop by your own
Intelligent wizards help you to create a draft version of your model across all layers of your data analytics platform. Choose different modelling approaches or create your own approach.
- Data Vault 2.0, dimensional, 3 NF, own
- Historical data handling (SCD, Snapshot, CDC, Gapless, ..)
- Use Azure DevOps
Connect
Access to data
Connect
Access to data
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
- 3rd party connector 250+ data sources
- Support of Azure Data Factory, Azure Analytics
DEFINE
Describe data
DEFINE
Describe data
AC extract all metadata from the data sources, such as field descriptions, data types, key fields, and all relationships to create an AC metadata connector.
- Extract and capture DDL
- Detecting structure changes and forward in all higher layers
- Using existing metadata connectors from AnalyticsCreator cloud
- Ready to go metadata connectors for known source systems are available for download in the AC cloud and in the community.
COGNITIVE SUGGESTION
Intelligent wizard
Cognitive suggestion
Use the no code approach with wizards or develop by your own
Intelligent wizards help you to create a draft version of your model across all layers of your data analytics platform. Choose different modelling approaches or create your own approach.
- Data Vault 2.0, dimensional, 3 NF, own
- Historical data handling (SCD, Snapshot, CDC, Gapless, ..)
- Use Azure DevOps
Model
Optimize draft
MODEL
Optimize draft / create your own model
The entire toolset of AC 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.
- Automated transformations and wizards
- Collaboration
- Development process supported by data lineage flow-chart
- Own scripting and macros possible
Deploy
Generate code & structure
DEPLOY
Generate code & structure
To deploy the DW 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 Azure as well in hybrid environments
- Stored procedures, SSIS
- Azure SQL DB, Azure Analysis Services, Synapse
- ARM Template for Azure Data Factory
- Tabular Models, OLAP Cubes
- Power BI
- Tabeau
- Qlik
AnalyticsCreator architecture of an
automated Data Analytics Platform
1. Raw data, ERP, CRM, any
2. Azure Data Lakehouse, Data Warehouse, Data Vault 2.0,
Kimball, virtual & real time, on premises
3. Tabular column based model, OLAP, Power BI Premium
4. Holistic data model
5. AnalyticsCreator source code generator
6. Developer, Business use