Avanade Centre of Excellence (CoE) Technical Architect specialising in data platform solutions built on Microsoft Azure.
Data engineering competencies include Azure Synapse Analytics, Data Factory, Data Lake, Databricks, Stream Analytics, Event Hub, IoT Hub, Functions, Automation, Logic Apps and of course the complete SQL Server business intelligence stack.
15+ years’ experience working within healthcare, retail, manufacturing, and gaming verticals delivering analytics through the definition of industry leading design patterns and technical architectures.
STEM ambassador and very active member of the data platform community delivering training and technical sessions at conferences both nationally and internationally.
Father, husband, swimmer, cyclist, runner, blood donor, geek, Lego and Star Wars fan!
Sessions
Previous Sessions
Demonstrating an end to end IoT solution providing real-time sensor data from a Raspberry Pi into an Azure IoT Hub, through Stream Analytics, then with outputs to Power BI and SQL DB. Learn how to build this simplified IoT solution from scratch.
Let’s understand the role of this hyper-scale two tier big data technology and how to harness its power with U-SQL, the offspring of T-SQL and C#. We’ll cover everything you need to know to get started developing solutions with Azure Data Lake.
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.
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.
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.
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.
How has advancements in highly scalable cloud technology influenced the design principals we apply when building data platform solutions?