Azure Data Platform
Derby, England, United Kingdom
The resources on offer in Azure are constantly changing, which means as data professionals we need to constantly change too. Updating knowledge and learning new skills. No longer can we rely on products matured over a decade to deliver all our solution requirements. Today, data platform architectures designed in Azure with best intentions and known good practices can go out of date within months. That said, is there now a set of core components we can utilise in the Microsoft cloud to ingest and deliver insights from our data? When does ETL become ELT? When is IaaS better than PaaS? Do we need to consider scaling up or scaling out? And should we start making cost the primary factor for choosing certain technologies? In this session we'll explore the answers to all these questions and more from an architects viewpoint. Based on real world experience lets 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 Platform solution.
Principal consultant and architect specialising in big data solutions on the Microsoft Azure cloud platform.
Data engineering competencies include Azure 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.
Many years’ experience working within healthcare, retail and gaming verticals delivering analytics using industry leading methods and technical design patterns.
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!