Paul Andrew

Paul is a Microsoft Data Platform MVP with 10+ years’ experience working with the complete on premises SQL Server stack in a variety of roles and industries. Now as the Business Intelligence Consultant has turned his keyboard to big data solutions in the Microsoft cloud. Specialising in Azure Data Lake Analytics, Azure Data Factory, Azure Stream Analytics, Event Hubs and IoT. Paul is also a STEM Ambassador for the networking education in schools’ programme, PASS chapter leader for the Microsoft Data Platform Group – Birmingham, SQL Bits, SQL Relay, SQL Saturday, PASS Summit speaker and helper. Currently the Stack Overflow top user for Azure Data Factory. As well as very active member of the technical community.


PRECON: The Modern Azure Data Warehouse


The number of data & analytics components available in Azure has exploded over the past couple of years - understanding which components should be in your toolbelt and what part each plays can be a daunting task, especially given the speed technology is advancing at. However, if you want to meet the challenges of the growing data landscape, you have to adopt distributed cloud architectures!

We have helped many of Microsoft's clients move their BI architectures to the cloud and we can guide you on that journey too, taking you through our recommended architecture and explaining the common pitfalls and mistakes to avoid. There are many learnings of traditional "Big Data" that we can apply when designing our platform, we'll take you through them so you're ready for any data problem - whether it's volume, variety or velocity!

Morning - The Core Modern Analytics Platform

In this first workshop, we want you to leave fully equipped to build a scalable, robust data platform that can support any analytical requirement. We’ll be providing an overview and practical demonstrations of:
• Cloud Architectures & Approaches
• Building and maintaining Azure Data Lakes
• Facilitating & Orchestrating data flow using Azure Data Factory V2
• Designing for performance with Azure SQLDW
These three key technologies will allow you to establish a platform on which many more analytical components can be added, and you will leave this session confident in taking this first step.

Afternoon - The Complete Modern Analytics Platform

The afternoon session will look at additional processing and integration components, enriching and augmenting the data you're collecting and curating:
• Applying the Lambda Architecture with Streaming Analytics
• Serverless Orchestration with Logic Apps & Azure Functions
• Tackling Big Data using Data Lake Analytics & U-SQL
• Reporting & Visualisation in the Modern Analytics Platform
With these sessions combined, you'll have a firm understanding of all the technologies needed to build an end-to-end analytics platform in a modern, scalable manner. This knowledge, and the patterns we will cover, will equip you to design a solid foundation which will support a vast variety of data analytics solutions.

Simon Whiteley  Precon 

U-SQL Production Analytics with Azure Data Lake



After a very quick overview of Azure Data Lake Analytics let’s get stuck into the technology. This highly scalable cloud service has been generally available for a few years now and its adoption for production workloads is rapidly growing. But is U-SQL just another transformation tool or can we unlock its potential as a powerful, scale out framework to manipulate our data in new ways? In this session we’ll explore that question and see how U-SQL can be applied to production data analytics solutions. Plus, our options for code generation and deployment in Azure with meta data driven workloads.