GithubHelp home page GithubHelp logo

mrdaggubati / data-management-zone Goto Github PK

View Code? Open in Web Editor NEW

This project forked from azure/data-management-zone

0.0 0.0 0.0 5.45 MB

Template to deploy the Data Management Zone of the Enterprise Scale Analytics architecture. The Data Management Zone provides data governance and management capabilities for the data platform of an organization.

License: MIT License

PowerShell 10.17% Shell 23.76% Dockerfile 0.62% Bicep 65.45%

data-management-zone's Introduction

Enterprise-Scale Analytics - Data Management Zone

Objective

The Enterprise-Scale Analytics 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 Enterprise-Scale 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.
  2. 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.

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.

Enterprise-Scale Analytics


The Enterprise-Scale Analytics architecture represents the strategic design path and target technical state for your Azure data platform.


This respository describes the Data Management Zone, which is classified as data management hub. It is the heart of the Enterprise-Scale Analytics architecture pattern and enables central governance of data assets across all Data Landing Zones. Enterprise-Scale Anayltics targets the deployment of a single Data Management Zone instance inside a tenant of an organization.

Note: Before getting started with the deployment, please make sure you are familiar with the complementary documentation in the Cloud Adoption Framework. After deploying your Data Management Zone, please move on to the Data Landing Zone deployment to create an environment in which you can start working on generating insights and value with data. The minimal recommended setup consists of a single Data Management Zone and a single Data Landing Zone.

Deploy Enterprise-Scale 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.

Reference implementation Description Deploy to Azure Link
Enterprise-Scale Analytics Deploys a Data Management Zone and one or multiple Data Landing Zone 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
Data Management Zone Deploys a single Data Management Zone to a subscription. Deploy To Azure Repository
Data Landing Zone Deploys a single Data Landing Zone to a subscription. Please deploy a Data Management Zone first. Deploy To Azure Repository
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 and Data Landing Zone first. Deploy To Azure Repository
Data Product Streaming Deploys a Data Workload template for Data Streaming Analysis to a resource group inside a Data Landing Zone. Please deploy a Data Management Zone and Data Landing Zone first. Deploy To Azure Repository
Data Product Analytics Deploys a Data Workload template for Data Analytics and Data Science to a resource group inside a Data Landing Zone. Please deploy a Data Management Zone and Data Landing Zone first. Deploy To Azure Repository

Deploy Data Management Zone

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

  1. Prerequisites
  2. Create repository
  3. Setting up Service Principal
  4. Template Deployment
    1. GitHub Action Deployment
    2. Azure DevOps Deployment
  5. Known Issues

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repositories using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

data-management-zone's People

Contributors

abdale avatar analyticjeremy avatar hallihan avatar marvinbuss avatar microsoft-github-operations[bot] avatar microsoftopensource avatar xigyenge avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.