Mark Pryce-Maher

In this full day workshop, we’ll cover the skills and tasks required for a career as a Microsoft Fabric Analytics Engineer and prepare you for the DP-600 Certification Exam.

In this training session you will build a full fletched green field Lakehouse architecture based on best practices! You will be guided by experts in the field to learn about the key components & how to build it in the most dynamic & performant way!

Learn how to implement a data warehouse analytics solution with Azure Synapse. We will cover best practices on migrations, performance, security, and more!

Get ready to wrap up a serious day of learning with a dash of humor, spontaneity, and friendly competition! SQLBits presents "Slide Karaoke" where SQLBits speakers reveal their hidden talents while vying for bragging rights. This session promises to be a one-of-a-kind experience that will leave you in stitches and awe, and the speakers scrambling for their non-existent notes!

Come and join the Fabric Product Group for one of our fireside chats. Bring your questions because we have all the answers!!

SQLBits' has brought members of the Azure Synapse Program Group to Wales to ask YOUR questions. Bring your questions for: Dedicated SQL Pools, Serverless SQL Pools, Spark Pools, Pipelines, Kusto and everything else Synapse related.

5 minute lightning talks from your favourite speakers

Session covering table distributions, partitioning , RSC and materialised views.

Building a dashboard using Serverless SQL Pools in a performant way

In this session we explore Azure Synapse Analytics, we will dive into this limitless analytics service and explore how it brings together enterprise data warehousing and Big Data analytics.

This session will dive into how to successfully migrate to Azure Synapse, all the way from code conversion to enterprise grade developer tooling, with real customer examples for product and migration experts.

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.

We will travel back in time a bit to SQL 2005 to see how SSMS Add-ins worked, then jump forward to the present day were we will go through the process of writing a SSMS Add-in for R2.