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Simon Whiteley

Coming from a world of traditional BI structures, Simon is now obsessed with utilising cloud technologies to revolutionise these traditions.

He will dive into any interesting BI problem, whether its ETL patterns, analysis models or building custom D3 visualisations.

As a Microsoft Data Platform MVP, his main focus is harnessing Azure Data Services to build the next generation of Cloud Analytics Architectures!





Presenting

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.

Paul Andrew  Precon 

Cloud Orchestration: Azure Data Factory V2 & PaaS SSIS

Many existing Data Factory solutions include a large number of workarounds due to limitations with the service. Now that Data Factory V2 is available, we can restructure our Data Factories to be lean, efficient data pipelines, and this session will show you how.

The initial Data Factory release was targeted at managing hadoop clusters, with a couple of additional integrations thrown in - it was mistakenly believed to be "the new SSIS" and subsequently there were a lot of very disappointed people. The new release remedies many of these complaints, adding in workflow management, expressions, ad-hoc triggers and many more features that open up a world of possibilities.

This session will run through the new features in ADFV2 and discuss how they can be used to streamline your factories, putting them in the context of real-world solutions. We will also look at the additional compute options provided by the new SSIS integration, how it works within the context of Data Factory and the flexibility it provides.

A working knowledge of ADF V1 is assumed.

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