Data Regulated platform — How to build Enterprise ready Data Platform with Data mesh and Centralized

Balamurugan Balakreshnan
2 min readJan 29, 2022

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Build next generation data platform for New Data regulated enterprise

Use Cases

  • Build Enterprise ready data platform for data regulated enterprises
  • Data mesh for business domain or country specific regulation
  • Centralized data estate/swamp/lake C-Level reporting
  • Data Governance, privacy and security enabled
  • Lineage for right to be forgotten and other user centric privacy
  • Data Driven insights
  • Artificial intelligence, machine/deep learning driven insights
  • Reinforcement learning drive decision making
  • Enable business users to become knowledge/Intelligent driven insights assisted users
  • Enterprises should be able to automate and apply application life cycle management
  • Security enabled for business domains or country / Region specific
  • Every business domain or country or data regulation based will have its own security model
  • There will be global security model
  • No need to move data
  • Centralized data lake can connect to individual Mesh storage as linked service to read data
  • Every data mesh will have its own storage and execution to accommodate mesh or country specific regulation

Architecture

  • Let’s build a solution for the above modern data regulated data platform
  • Choice is to show how it can be achieved by using Azure synapse analytics — unified platform

Solution

  • Architecture above is split into 2 sections
  • Top part which is the high-level architecture for data regulated platform
  • Bottom part is the common services that each mesh/centralized platform will follow
  • Bottom part is also the data governance that cuts across the entire platform
  • Common data model can be part of both Mesh and Centralized data platform
  • Data security and infra security both are applied
  • Data security is how the rows are filtered based on user context. So only authorized users can access necessary part of the system
  • Optional block chain can be used for lineage
  • Ability to converge any type of data is also covered
  • Above architecture can accommodate GDPR, CCPA and other data regulations
  • By using Purview we can manage the data governance and lineage
  • By using Azure Machine learning, data can extend to build own insights using machine/deep learning
  • Mesh can be split based on country for global companies
  • Synapse Spark, serverless SQL provides way to connect to country specific storage and read when needed, instead moving data
  • This also applies to different business domains as well.
  • Multi cloud data store is not added for now will be future based
  • Multi engine or data processing is durable

Original Article — Samples2022/dp.md at main · balakreshnan/Samples2022 (github.com)

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