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Renaming from ESA to DMA (#217)
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* ESA to DMA name change in Readme.md

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* updated portal strings

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Co-authored-by: Marvin Buss <[email protected]>
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34 changes: 17 additions & 17 deletions README.md
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# Enterprise-Scale Analytics and AI - Data Landing Zone
# Data Management & Analytics Scenario - Data Landing Zone

## Objective

The [Enterprise-Scale Analytics](https://aka.ms/adopt/datamanagement) architecture provides a prescriptive data platform design coupled with Azure best practices and design principles. These principles serve as a compass for subsequent design decisions across critical technical domains. The architecture will continue to evolve alongside the Azure platform and is ultimately driven by the various design decisions that organizations must make to define their Azure data journey.
The [Data Management & Analytics scenario](https://aka.ms/adopt/datamanagement) provides a prescriptive data platform design coupled with Azure best practices and design principles. These principles serve as a compass for subsequent design decisions across critical technical domains. The architecture will continue to evolve alongside the Azure platform and is ultimately driven by the various design decisions that organizations must make to define their Azure data journey.

The Enterprise-Scale Analytics architecture consists of two core building blocks:
The Data Management & Analytics architecture consists of two core building blocks:

1. *Data Management Zone* which provides all data management and data governance capabilities for the data platform of an organization.
1. *Data Landing Zone* which is a logical construct and a unit of scale in the Enterprise-Scale Analytics architecture that enables data retention and execution of data workloads for generating insights and value with data.
1. *Data Landing Zone* which is a logical construct and a unit of scale in the Data Management & Analytics architecture that enables data retention and execution of data workloads for generating insights and value with data.

The architecture is modular by design and allows organizations to start small with a single Data Management Zone and Data Landing Zone, but also allows to scale to a multi-subscription data platform environment by adding more Data Landing Zones to the architecture. Thereby, the reference design allows to implement different modern data platform patterns like data-mesh, data-fabric as well as traditional datalake architectures. Enterprise-Scale Analytics has been very well aligned with the data-mesh approach, and is ideally suited to help organizations build data products and share these across business units of an organization. If core recommendations are followed, the resulting target architecture will put the customer on a path to sustainable scale.
The architecture is modular by design and allows organizations to start small with a single Data Management Zone and Data Landing Zone, but also allows to scale to a multi-subscription data platform environment by adding more Data Landing Zones to the architecture. Thereby, the reference design allows to implement different modern data platform patterns like data-mesh, data-fabric as well as traditional datalake architectures. Data Management & Analytics has been very well aligned with the data-mesh approach, and is ideally suited to help organizations build data products and share these across business units of an organization. If core recommendations are followed, the resulting target architecture will put the customer on a path to sustainable scale.

![Enterprise-Scale Analytics](/docs/images/EnterpriseScaleAnalytics.gif)
![Data Management & Analytics](/docs/images/DataManagementAnalytics.gif)

---

_The Enterprise-Scale Analytics architecture represents the strategic design path and target technical state for your Azure data platform._
_The Data Management & Analytics architecture represents the strategic design path and target technical state for your Azure data platform._

---

This respository describes the Data Landing Zone, which is where data is persisted and data workloads are executed. A Data Landing Zone is a unit of scale of the Enterprise-Scale Analytics architecture pattern and it enables regional deployments, clear seperation of ownership, chargeback of cost, in-place data sharing within and across Data Landing Zones and many other much asked benefits. In addition, it is possible to scale within Data Landing Zones with cross-functional Data Integration and Data Product teams. The reference design targets a self-service approach for these teams to overcome bottlenecks and the need for a central team for cloud service deployments. The Data Landing Zone reference implementation will create a consistent setup inside a subscription and will deploy storage accounts as well as data processing services like Azure Synapse, Azure Data Factory as well as Azure Databricks.
This respository describes the Data Landing Zone, which is where data is persisted and data workloads are executed. A Data Landing Zone is a unit of scale of the Data Management & Analytics architecture pattern and it enables regional deployments, clear seperation of ownership, chargeback of cost, in-place data sharing within and across Data Landing Zones and many other much asked benefits. In addition, it is possible to scale within Data Landing Zones with cross-functional Data Integration and Data Product teams. The reference design targets a self-service approach for these teams to overcome bottlenecks and the need for a central team for cloud service deployments. The Data Landing Zone reference implementation will create a consistent setup inside a subscription and will deploy storage accounts as well as data processing services like Azure Synapse, Azure Data Factory as well as Azure Databricks.

> **Note:** Before getting started with the deployment, please make sure you are familiar with the [complementary documentation in the Cloud Adoption Framework](https://aka.ms/adopt/datamanagement). Also, before deploying your first Data Landing Zone, please make sure that you have deployed a [Data Management Zone](https://github.com/Azure/data-management-zone). The minimal recommended setup consists of a single [Data Management Zone](https://github.com/Azure/data-management-zone) and a single Data Landing Zone.
## Deploy Enterprise-Scale Analytics
## Deploy Data Management & Analytics

The Enterprise-Scale Analytics architecture is modular by design and allows customers to start with a small footprint and grow over time. In order to not end up in a migration project, customers should decide upfront how they want to organize data domains across Data Landing Zones. All Enterprise-Scale Analytics architecture building blocks can be deployed through the Azure Portal as well as through GitHub Actions workflows and Azure DevOps Pipelines. The template repositories contain sample YAML pipelines to more quickly get started with the setup of the environments.
The Data Management & Analytics architecture is modular by design and allows customers to start with a small footprint and grow over time. In order to not end up in a migration project, customers should decide upfront how they want to organize data domains across Data Landing Zones. All Data Management & Analytics architecture building blocks can be deployed through the Azure Portal as well as through GitHub Actions workflows and Azure DevOps Pipelines. The template repositories contain sample YAML pipelines to more quickly get started with the setup of the environments.

| Reference implementation | Description | Deploy to Azure | Link |
|:---------------------------|:------------|:----------------|------|
| Enterprise-Scale Analytics | Deploys a [Data Management Zone](https://github.com/Azure/data-management-zone) and one or multiple Data Landing Zones all at once. Provides less options than the the individual Data Management Zone and Data Landing Zone deployment options. Helps you to quickly get started and make yourself familiar with the reference design. For more advanced scenarios, please deploy the artifacts individually. |[![Deploy To Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#blade/Microsoft_Azure_CreateUIDef/CustomDeploymentBlade/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fdata-management-zone%2Fmain%2Fdocs%2Freference%2FenterpriseScaleAnalytics.json/uiFormDefinitionUri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fdata-management-zone%2Fmain%2Fdocs%2Freference%2Fportal.enterpriseScaleAnalytics.json) | |
| Data Management & Analytics Scenario | Deploys a [Data Management Zone](https://github.com/Azure/data-management-zone) and one or multiple Data Landing Zones all at once. Provides less options than the the individual Data Management Zone and Data Landing Zone deployment options. Helps you to quickly get started and make yourself familiar with the reference design. For more advanced scenarios, please deploy the artifacts individually. |[![Deploy To Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#blade/Microsoft_Azure_CreateUIDef/CustomDeploymentBlade/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fdata-management-zone%2Fmain%2Fdocs%2Freference%2FdataManagementAnalytics.json/uiFormDefinitionUri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fdata-management-zone%2Fmain%2Fdocs%2Freference%2Fportal.dataManagementAnalytics.json) | |
| Data Management Zone | Deploys a single Data Management Zone to a subscription. |[![Deploy To Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#blade/Microsoft_Azure_CreateUIDef/CustomDeploymentBlade/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fdata-management-zone%2Fmain%2Finfra%2Fmain.json/uiFormDefinitionUri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fdata-management-zone%2Fmain%2Fdocs%2Freference%2Fportal.dataManagementZone.json) | [Repository](https://github.com/Azure/data-management-zone) |
| Data Landing Zone | Deploys a single Data Landing Zone to a subscription. Please deploy a [Data Management Zone](https://github.com/Azure/data-management-zone) first. |[![Deploy To Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#blade/Microsoft_Azure_CreateUIDef/CustomDeploymentBlade/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fdata-landing-zone%2Fmain%2Finfra%2Fmain.json/uiFormDefinitionUri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fdata-landing-zone%2Fmain%2Fdocs%2Freference%2Fportal.dataLandingZone.json) | [Repository](https://github.com/Azure/data-landing-zone) |
| Data Product Batch | Deploys a Data Workload template for Data Batch Analysis to a resource group inside a Data Landing Zone. Please deploy a [Data Management Zone](https://github.com/Azure/data-management-zone) and Data Landing Zone first. |[![Deploy To Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#blade/Microsoft_Azure_CreateUIDef/CustomDeploymentBlade/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fdata-product-batch%2Fmain%2Finfra%2Fmain.json/uiFormDefinitionUri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fdata-product-batch%2Fmain%2Fdocs%2Freference%2Fportal.dataProduct.json) | [Repository](https://github.com/Azure/data-product-batch) |
Expand All @@ -40,13 +40,13 @@ The Enterprise-Scale Analytics architecture is modular by design and allows cust

To deploy the Data Landing Zone into your Azure Subscription, please follow the step-by-step instructions:

1. [Prerequisites](/docs/EnterpriseScaleAnalytics-Prerequisites.md)
2. [Create repository](/docs/EnterpriseScaleAnalytics-CreateRepository.md)
3. [Setting up Service Principal](/docs/EnterpriseScaleAnalytics-ServicePrincipal.md)
1. [Prerequisites](/docs/DataManagementAnalytics-Prerequisites.md)
2. [Create repository](/docs/DataManagementAnalytics-CreateRepository.md)
3. [Setting up Service Principal](/docs/DataManagementAnalytics-ServicePrincipal.md)
4. Template Deployment
1. [GitHub Action Deployment](/docs/EnterpriseScaleAnalytics-GitHubActionsDeployment.md)
2. [Azure DevOps Deployment](/docs/EnterpriseScaleAnalytics-AzureDevOpsDeployment.md)
5. [Known Issues](/docs/EnterpriseScaleAnalytics-KnownIssues.md)
1. [GitHub Action Deployment](/docs/DataManagementAnalytics-GitHubActionsDeployment.md)
2. [Azure DevOps Deployment](/docs/DataManagementAnalytics-AzureDevOpsDeployment.md)
5. [Known Issues](/docs/DataManagementAnalytics-KnownIssues.md)

## Contributing

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8 changes: 4 additions & 4 deletions ...seScaleAnalytics-AzureDevOpsDeployment.md → ...agementAnalytics-AzureDevOpsDeployment.md
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Expand Up @@ -60,7 +60,7 @@ The following table explains each of the parameters:
| Parameter | Description | Sample value |
|:--------------------------------------------|:-------------|:-------------|
| **AZURE_SUBSCRIPTION_ID** | Specifies the subscription ID of the Data Landing Zone where all the resources will be deployed | <div style="width: 36ch">`xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx`</div> |
| **AZURE_LOCATION** | Specifies the region where you want the resources to be deployed. Please check [Supported Regions](/docs/EnterpriseScaleAnalytics-Prerequisites.md). | `northeurope` |
| **AZURE_LOCATION** | Specifies the region where you want the resources to be deployed. Please check [Supported Regions](/docs/DataManagementAnalytics-Prerequisites.md#supported-regions). | `northeurope` |
| **AZURE_RESOURCE_MANAGER _CONNECTION_NAME** | Specifies the resource manager connection name in Azure DevOps. More details on how to create the resource manager service connection in Azure DevOps was described in the previous paragraph or [here](https://docs.microsoft.com/azure/devops/pipelines/library/connect-to-azure?view=azure-devops#create-an-azure-resource-manager-service-connection-with-an-existing-service-principal). | `my-connection-name` |

### Configure `params.dev.json`
Expand Down Expand Up @@ -149,7 +149,7 @@ After following the instructions and updating the parameters and variables in yo

**Congratulations!** You have successfully executed all steps to deploy the template into your environment through Azure DevOps.

Now, you can navigate to the pipeline that you have created as part of step 5 and monitor it as each service is deployed. If you run into any issues, please check the [Known Issues](/docs/EnterpriseScaleAnalytics-KnownIssues.md) first and open an [issue](https://github.com/Azure/data-landing-zone/issues) if you come accross a potential bug in the repository.
Now, you can navigate to the pipeline that you have created as part of step 5 and monitor it as each service is deployed. If you run into any issues, please check the [Known Issues](/docs/DataManagementAnalytics-KnownIssues.md) first and open an [issue](https://github.com/Azure/data-landing-zone/issues) if you come accross a potential bug in the repository.

>[Previous](/docs/EnterpriseScaleAnalytics-ServicePrincipal.md)
>[Next](/docs/EnterpriseScaleAnalytics-KnownIssues.md)
>[Previous](/docs/DataManagementAnalytics-ServicePrincipal.md)
>[Next](/docs/DataManagementAnalytics-KnownIssues.md)
4 changes: 2 additions & 2 deletions ...erpriseScaleAnalytics-CreateRepository.md → ...taManagementAnalytics-CreateRepository.md
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Expand Up @@ -16,5 +16,5 @@ First, you must generate your own respository based off this template respositor
1. Optionally, to include the directory structure and files from all branches in the template and not just the default branch, select **Include all branches**.
1. Click **Create repository from template**.

>[Previous](/docs/EnterpriseScaleAnalytics-Prerequisites.md)
>[Next](/docs/EnterpriseScaleAnalytics-ServicePrincipal.md)
>[Previous](/docs/DataManagementAnalytics-Prerequisites.md)
>[Next](/docs/DataManagementAnalytics-ServicePrincipal.md)
8 changes: 4 additions & 4 deletions ...ScaleAnalytics-GitHubActionsDeployment.md → ...ementAnalytics-GitHubActionsDeployment.md
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Expand Up @@ -52,7 +52,7 @@ The following table explains each of the parameters:
| Parameter | Description | Sample value |
|:--------------------------------------------|:-------------|:-------------|
| **AZURE_SUBSCRIPTION_ID** | Specifies the subscription ID of the Data Landing Zone where all the resources will be deployed | <div style="width: 36ch">`xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx`</div> |
| **AZURE_LOCATION** | Specifies the region where you want the resources to be deployed. Please check [Supported Regions](/docs/EnterpriseScaleAnalytics-Prerequisites.md) | `northeurope` |
| **AZURE_LOCATION** | Specifies the region where you want the resources to be deployed. Please check [Supported Regions](/docs/DataManagementAnalytics-Prerequisites.md#supported-regions) | `northeurope` |

### Configure `params.dev.json`

Expand Down Expand Up @@ -103,7 +103,7 @@ After following the instructions and updating the parameters and variables in yo

**Congratulations!** You have successfully executed all steps to deploy the template into your environment through GitHub Actions.

Now, you can navigate to the **Actions** tab of the main page of the repository, where you will see a workflow with the name `Data Landing Zone Deployment` running. Click on it to see how it deploys the environment. If you run into any issues, please check the [Known Issues](/docs/EnterpriseScaleAnalytics-KnownIssues.md) first and open an [issue](https://github.com/Azure/data-landing-zone/issues) if you come accross a potential bug in the repository.
Now, you can navigate to the **Actions** tab of the main page of the repository, where you will see a workflow with the name `Data Landing Zone Deployment` running. Click on it to see how it deploys the environment. If you run into any issues, please check the [Known Issues](/docs/DataManagementAnalytics-KnownIssues.md) first and open an [issue](https://github.com/Azure/data-landing-zone/issues) if you come accross a potential bug in the repository.

>[Previous](/docs/EnterpriseScaleAnalytics-ServicePrincipal.md)
>[Next](/docs/EnterpriseScaleAnalytics-KnownIssues.md)
>[Previous](/docs/DataManagementAnalytics-ServicePrincipal.md)
>[Next](/docs/DataManagementAnalytics-KnownIssues.md)
7 changes: 2 additions & 5 deletions docs/EnterpriseScaleAnalytics-KnownIssues.md → docs/DataManagementAnalytics-KnownIssues.md
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Expand Up @@ -20,8 +20,6 @@ ERROR: Deployment failed. Correlation ID: ***
This error message appears, in case during the deployment it tries to create a type of resource which has never been deployed before inside the subscription. We recommend to check prior the deployment whether the required resource providers are registered for your subscription and if needed, register them through the `Azure Portal`, `Azure Powershell` or `Azure CLI` as mentioned [here](https://docs.microsoft.com/azure/azure-resource-manager/management/resource-providers-and-types).
## Error: ProvisioningDisabled
**Error Message:**
Expand All @@ -41,6 +39,5 @@ ERROR: Deployment failed. Correlation ID: ***
This error message appears when during the deployment it tries to create a MySql/SQL Database/Other Services but the subscription is restricted from provisioning that specific resource at that specific region. We recommend to request subscription quota increase through a support request, or to deploy to a different region.
>[Previous (Option (a) GitHub Actions)](/docs/EnterpriseScaleAnalytics-GitHubActionsDeployment.md)
>[Previous (Option (b) Azure DevOps)](/docs/EnterpriseScaleAnalytics-AzureDevOpsDeployment.md)
>[Previous (Option (a) GitHub Actions)](/docs/DataManagementAnalytics-GitHubActionsDeployment.md)
>[Previous (Option (b) Azure DevOps)](/docs/DataManagementAnalytics-AzureDevOpsDeployment.md)
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