Create a Data Warehouse in 5 Easy Steps

Create a DWH in 5 easy Steps

Looking to start a DWH from scratch, migrate your DWH or automate your data warehousing process?
Let us help you take the first step towards a more efficient and streamlined data warehousing process

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The Process

Model

Optimize Draft

Model
4.

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, and in an 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

Deploy

Create Code & Structure

Deploy
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, and in an 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
Connect

Connect

Access to data

1.

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, and in an 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
DEFINE

Define

Describe data

2.

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, and in an 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
COGNITIVE_SUGGESTION

COGNITIVE SUGGESTION

Intelligent Wizard

3.

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, and in an 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
1

Connect

Access to data

1.

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, and in an 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
2

Define

Describe data

2.

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, and in an 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
3

COGNITIVE SUGGESTION

Intelligent Wizard

3.

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, and in an 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
4

Model

Optimize Draft

4.

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, and in an 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
5

Deploy

Create 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, and in an 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
Shape Image

1. Connect to any Data Source

Connect AnalyticsCreator to any of 250+ data sources, like databases, individual files, data lakes, cloud services, Excel files and other extracts.

Enjoy full support of Azure Data Factory, Azure Analytics

Connect to Any Data Source
Define Your Data

2. Define Your Data

AnalyticsCreator extracts 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. Let AnalyticsCreator Help You

The Intelligent wizards help you to create a draft version of your model across all layers of your data analytics platform. You can choose different modelling approaches (including DataVault 2.0 or Kimball) or you can create your own approach.

Let AnalyticsCreator Help You
Refine Your Data Model

4. Refine Your Data Model

The entire AnalyticsCreator 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.

5. Deploy Your Data Model

Deploy your new DWH 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
  • Tableau
  • Qlik
Rapid Deployment_

Take Control of Your Data

Our metadata-based solution streamlines your data warehouse platform's life-cycle processes for faster results.  Find out how our customers have reported up to 10x faster life-cycle process times.

Contact us today to learn more.

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Ranked #1

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Feature Rich

Our customers enjoy the feature-rich functionality of AnalyticsCreator

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Satisfaction

We constantly strive to improve our functions and features.