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(BALLOT TICKET) Data Science with Microsoft SQL Server

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THIS IS NOT AN EVENT TICKET.

Due to the popularity of Data Science Festival events we are now allocating event tickets via a random ballot. Registering for this event enters you into the ticket ballot, tickets for the live event and joining details will be released via e-mail on Friday 17th February.

The live event will be held at 6pm on Tuesday 21st February.

Join Data Science Festival - London in partnership with SHACK15 this month for 2 great presentations.

SCHEDULE

6.00pm doors open
6.30 - 7:15pm - Talk - Gavin Payne
7:15 - 7:45pm - Beer & Pizza
7:45 - 8.30pm - Talk - Oliver Frost
8:30 - 9:00pm - Beer & Close

Gavin Payne: How SQL Server works and how to make your queries faster.

Summary: TBC

Bio: TBC


Oliver Frost: Data Science with SQL Server 2016 and R.

Summary: One of the most notable additions to the Microsoft BI stack is the addition of Microsoft R Server inside SQL Server 2016. The in-built ScaleR packages deliver scalability and multi-threading capabilities that open-source R can’t easily provide, opening up a world of possibilities for data scientists interested in machine learning and predictive analytics. But what does this look like on a Microsoft platform?

Oliver Frost, a Data Engineer at Consolidata, demonstrates what tools are available to you as a data scientist inside SQL Server 2016 and on Azure. Discover how R adds value where traditional relational databases struggle, how to use ScaleR functions to build predictive models and see how Azure ML can be used to build efficient machine learning pipelines.

Bio: Oliver Frost is a Data Engineer at Consolidata and an active member of the SQL community. His time is divided between working on technical client projects, operating from the company data platform using SQL Server, R and Azure. Ollie likes to incorporate knowledge from his previous life as a neuroscience graduate and as a former blindfolded Rubik's Cube world record holder - his belief that psychology, neuroscience and big data will, one day, collide in a big way.


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