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 works quite similarly, wherein the business model can also be loaded from other modelling tools.

*All what you do is on the design level

Model

Optimize draft

Group 689
4.

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

Group 688
5.

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
Group 199
Group 692

Connect

Access to data

1.

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
  • 3 rd party connector 200+ data sources
  • Support of Azure Data Factory, Azure Analytics
Group 691

DEFINE

Describe data

2.

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.
Group 690

COGNITIVE SUGGESTION

Intelligent wizard

3.

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
1

Connect

Access to data

1.

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
  • 3 rd party connector 200+ data sources
  • Support of Azure Data Factory, Azure Analytics
2

DEFINE

Describe data

2.

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.
3

COGNITIVE SUGGESTION

Intelligent wizard

3.

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
4

Model

Optimize draft

4.

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
5

Deploy

Generate code & structure

5.

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

Packages

Choose your package for work

starter Package

arrow-circle-up

Named user or concurrent user Limited on legal entity Limited on legal entities 6 month subscription

Book a call
POPULAR

Core Package

Vector

Named user or concurrent user Unlimited legal entities Unlimited to data, environments Different subscription periods

Book a call

FLat rate package

star

Consultancy/Freelancer only Managed service approach 1 month subscription

Book a call

Synapse Package

Synapse-Package

Named user or concurrent user Unlimited legal entities Unlimited to data, environments Different subscription periods

Book a call