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Title & Speakers Event

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MeetUp Agenda

18:00 - Arrive. Networking 18:30 - Guest Speaker Talk 19:30 - Buffet. Networking 20:30 - Event Close

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An Engineers Guide To Realtime Data Handling And Analytics

The velocity of data is getting faster across many industries, fuelled by the business demand to gain insights and value from sources in near real-time. This necessity is then allowing decision makers to pivot and ultimately stay ahead of the competition. Furthermore, the growth of the internet of things and ‘smart’ devices now means the volume of that high velocity data has exploded. Meeting this demand requires new concepts and new designs for data/solution architects, with high throughput ingestion endpoints and query stream tools that can perform aggregations ‘on the fly’. In this course, we will address the above head on. Discussing and designing architectures that can scale and burst for high throughput events. Querying using both SQL and KQL to blend stream and batch data feeds for downstream reporting.

As a platform, we’ll use Azure Event Hub and Azure Stream Analytics to ingest and handle that initial data stream. Before applying the same patterns to other resources in Microsoft Fabric and Azure Data Explorer. Understanding the patterns to apply as an architect vs the tooling available for delivery.

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Venue Website

http://www.waterfall-derby.com/

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Sponsors

Cloud Formations https://www.cloudformations.org

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Microsoft Community Code of Conduct

https://answers.microsoft.com/en-us/page/codeofconduct

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11th Dec 24 | East Midlands Data | Derby | Speaker - Paul Andrew

Please join us on June 5th to listen to the topic: An Engineers Guide To Realtime Data Handling And Analytics

What \~ Toronto Data Professionals Community (Virtual) When \~ Wednesday, 5th June, 2024

Agenda:

  • 12:00 PM Networking and Introduction
  • 12:15 PM Topic: An Engineers Guide To Realtime Data Handling And Analytics with Paul Andrew
  • 1:30 PM End

Where: Online via Microsoft team

Session Details: The velocity of data is getting faster across many industries, fueled by the business demand to gain insights and value from sources in near real-time. This necessity is then allowing decision makers to pivot and ultimately stay ahead of the competition. Furthermore, the growth of the internet of things and ‘smart’ devices now means the volume of that high velocity data has exploded. Meeting this demand requires new concepts and new designs for data/solution architects, with high throughput ingestion endpoints and query stream tools that can perform aggregations ‘on the fly’.

In this session, we will address the above head on. Discussing and designing architectures that can scale and burst for high throughput events. Querying using both SQL and KQL to blend stream and batch data feeds for downstream reporting.

As a platform, we’ll use Azure Event Hub and Azure Stream Analytics to ingest and handle that initial data stream. Before applying the same patterns to other resources in Microsoft Fabric and Azure Data Explorer. Understanding the patterns to apply as an architect vs the tooling available for delivery.

Speaker’s Bio: Paul (AKA @mrpaulandrew) is the Co-Founder & CTO of Cloud Formations, a specialist data consultancy based in the UK. With nearly 20 years’ experience designing and delivering Microsoft data architectures, Paul leads a passionate team of engineers, supporting businesses small and large with scalable cloud platforms. Business value delivered through data insights. Over the years, Paul has covered the breadth and depth of design patterns and industry leading concepts, including Lambda, Kappa, Delta Lake, Data Mesh and Data Fabric.

Paul is also a Microsoft Data Platform MVP, director for the Data Relay community conference, East Midlands user group leader, book author and mentor. In addition to the day job(s), Paul is a father of three, husband, foodie, runner, blood donor, geek, Lego, and Star Wars fan! Lastly, Paul confesses to enjoying a Ramstein playlist when given half a chance to do some coding for a customer project.

An Engineers Guide To Realtime Data Handling And Analytics
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