The Evolution of Data Platform Architectures in Azure - Lambda, Kappa, Delta, Data Mesh

2022

TL; DR

How has advancements in highly scalable cloud technology influenced the design principals we apply when building data platform solutions?

Session Details

How has advancements in highly scalable cloud technology influenced the design principals we apply when building data platform solutions? Are we designing for just speed and batch layers or do we what more from our platforms, and who says these patterns must be delivered exclusively? Let’s disrupt the theory and consider the practical application of all things. Can we now utilise Azure technology to build architectures that cater for lambda, kappa and delta concepts in a complete stack of services? And should we be considering a solution that offers all these principals in a nirvana of data insight perfection? In this session we’ll explore the answer to all these questions and more in a thought provoking, argument generating look at the challenges every data platform architect faces.

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3 things you'll get out of this session

Paul Andrew's other proposed sessions for 2026

An Evolution of Cloud Data Architectures - Lambda, Kappa, Delta, Mesh & Fabric - 2026

An Introduction to Delta Lake and The Lakehouse - 2026

Build a Lakehouse in a Day with Metadata & Open-Source Tools - 2026

Building Near Real-time Data Solutions in Microsoft Azure & Fabric - 2026

Data & Community: An Amazing Network Of Peers Supporting Innovation & Growth - 2026

Data Modelling: The Lost Art of Turning Inputs into Insights - 2026

Deciphering Data Architectures full-day workshop - 2026

Designing & Delivering Data Products: From Mesh Principles to Data Fabric Automation - 2026

Fabric Data Activator: Real-Time Data Feeds, Automated Alerts & Stock Intelligence - 2026

Fast-Track Your Lakehouse Build with a Metadata Framework - 2026

Microsoft Fabric Platform Governance - Where To Start - 2026

Paul Andrew's previous sessions

An Evolution of Data Architectures - Lambda, Kappa, Delta, Mesh & Fabric

How has advancements in highly scalable cloud technology influenced the design principals we apply when building data platform solutions?

Building an Azure Data Analytics Platform End-to-End

Based on real world experience let’s think about just how far the breadth of our knowledge now needs to reach when starting from nothing and building a complete Microsoft Azure Data Analytics solution.

Creating a Metadata Driven Orchestration Framework Using Azure Data Integration Pipelines

We'll explore delivering this framework within an enterprise and consider an architect’s perspective on a wider platform of ingestion/transformation workloads with multiple batches and execution stages.

ETL in Azure Made Easy with Data Factory Data Flows

What happens when you combine a cloud orchestration service with a Spark cluster?! The answer is a feature rich, graphical, scalable data flow environment to rival any ETL tech we’ve previously had available in Azure.

Using Azure DevOps for Azure Data Factory

DevOps as a concept does not always translate to the technology when implemented. In this session we'll explore that problem when working with Azure Data Factory and what the different cloud only CI/CD options are.

Complex Azure Orchestration w Dynamic Data Factory Pipelines

If you have already mastered the basics of Azure Data Factory (ADF) and are now looking to advance your knowledge of the tool this is the session for you.

Building an End to End IoT Solution Using Pi Sensors & Azure

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