4th - 7th May 2016

Liverpool

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This talk takes a look at Cloud Computing – what it is, the types of Cloud available and their advantages and disadvantages along with what Microsoft Azure has to offer.
This session covers the more advanced aspects of development for Azure SQL Data Warehouse. Areas such as data movement, workload concurrency and resource management will all be covered during this intense 60 minute session.
This session will compare Microsoft’s options for deploying highly available SQL Server data platforms in mid-2016.
Azure Data Factory and SSIS are both data movement tools, but built for different purposes. In this session you will learn pros and cons of using each technology, and best practices of using each in real world scenarios.
Azure SQL Database is on a roll with a blockbuster set of new features. Attend this session to understand the big changes and investments with Azure SQL Database
Azure offers many great tools and services, but how to they fit together and what are your options when trying to architect an end to end Azure BI platform?
Virtualization has had a major impact on computing. While data professionals have adjusted to this for database servers, many BI workloads have moved there as well. Learn about the impact of virtualization on BI.
Azure SQL DB can automatically make customer apps run faster and more cost-effectively, based on analyzed workload telemetry from millions of customer databases. Come and see live demos about what the service can do for customers today
In this session, we are going to look at a typical machine learning process and how to apply it to real world data. We are going to use Azure Machine Learning to transform data and ideas into models that are production ready in minutes.
Running databases in SQL Servers in your office or data centre? Considering moving them to Azure? Want to know what options and benefits of Infrastructure as a Service and Platform as a Service?
In this talk, you will get an overview on what to think about when storing data in a document database.
Discover the ins and outs of some of the newest capabilities of our favorite data language. From JSON to COMPRESS/DECOMPRESS, from SESSION_CONTEXT() to DATEDIFF_BIG(), and new query hints.
The quickest way to migrate your on-premises OLTP database to Azure is to "Lift & Shift". In this session we will investigate how we could use more of the cloud features like SQL Database, Redis Cache, Search, etc.
The Internet of Things starts with your things. It's a great time to take a look at game changing technologies you can use today to make your IoT ideas stand out from the rest using Microsoft Azure. Welcome to the Internet of Your Intelligent Things!
This session is going to examine how to successfully a modern data architecture on the Microsoft Azure cloud platform. Using a canonical IoT application example, we will focus on design tenants for efficient, scalable and resilient data processing.
SQL Server 2016 introduces the Query Store. The Query Store will change how you tune queries. Come to this session to learn everything you'll need.
This session looks at building time series analysis with AzureML in R
Data Warehouses are changing. This session will run through the architecture of the modern warehouse, from structured/unstructured Azure Data Lakes to platform as a service Azure Data Warehouse and bringing the two together.
PolyBase is one of the most exciting, innovative features in PDW; enabling transparent data integration with Hadoop's distributed file system (HDFS) and Windows Azure Storage Blobs (WASB). See it in action.
Azure stream analytics is a new Azure service for analyzing streaming data.
Azure Machine Learning is a fully managed cloud service for predictive analytics. In this 1hour session, we will run through; ML Studio,using data, Creating and running Experiments, visualising results, R , publishing and using experiments.
Sometimes don't want our data in the cloud, but that doesn't mean we can't use the cloud at all.
This presentation will focus on techniques and practices for using memory optimized tables in SQL Server to build “warm” data stores from a variety of application data sources (logs,traces, performance statistics)
The Azure CAT team has successfully architected, designed and built hundreds of cloud projects. In this session we will share the learnings on how to design a cloud application to scale to handle large, complex workloads.
Come to this session to see how to build a scalable analytical solution on Microsoft Azure with Elastic Search and Kibana.
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