Designing Data Architectures that InfoSec will actually approve
2022TL; DR
Building your data platform in the cloud is easy, but what about integrating it with your existing networking, how do you manage user security, what on earth is a private endpoint? In this session I'll guide you from through a secure reference architecture with Data Factory, Databricks, Data Lake, and Azure Synapse, working together as a secure, fully productionised platform. Each has their own idiosyncrasies, but this session will teach you the options available and the pitfalls to avoid.
Session Details
Building your data platform in the cloud is easy, but as soon as that dreaded word "security" becomes involved it suddenly becomes incredibly painful. How do you go about integrating it with your existing networking, how do you manage user security, what on earth is a private endpoint? Over the past year, a lot of these tools have evolved and we now have a set of mature patterns we can apply to actually make a modern data platform secure.
In this session I'll guide you from through a secure reference architecture with Data Factory, Databricks, Data Lake, and Azure Synapse, working together as a secure, fully productionised platform. Each has their own idiosyncrasies, but this session will teach you the options available and the pitfalls to avoid.
3 things you'll get out of this session
Speakers
Craig Porteous's other proposed sessions for 2026
Centralise or Federate - How to Scale your Lakehouse - 2026
Do You Really Need a Data Lakehouse? Separating Hype from Business Need - 2026
Craig Porteous's previous sessions
Zero to Lakehouse in Microsoft Fabric
Fabric is Microsoft's unified software as a service data platform, built around a Data Lakehouse architecture. In this session I'll share an array of data Lakehouse architecture patterns, and demonstrate how you can build a full Data Lakehouse platform without ever touching an Azure resource.
Building a Lakehouse on the Microsoft Intelligent Data Platform
This session session aims to give you that context. We'll look at how spark-based engines work and how we can use them within Synapse Analytics. We'll dig into Delta, the underlying file format that enables the Lakehouse, and take a tour of how the Synapse compute engines interact with it. Finally, we'll draw out our whole Lakehouse architecture
Designing Data Architectures that InfoSec will actually approve
In this session I'll guide you from through a secure reference architecture with Data Factory, Databricks, Data Lake, and Azure Synapse, working together as a secure, fully productionised platform. Each has their own idiosyncrasies, but this session will teach you the options available and the pitfalls to avoid.
Why the Lakehouse?
In this session I'll cover what the Data Lakehouse architecture is, where it fits against existing architectures like a data warehouse, and why you should build one. We'll also cover the underlying technology options to arm you with all of the information you need to plan your next data platform.
Keynote by The Community
Ben and Rob have found some wonderful folk to actually do the important parts of the community keynote. on the theme of
How to be a nonpassive member of the data community