In this session, Henry will address the disruption that is being experienced in the data management sphere and how a DBA can look at the options they have to apply their skills to this new world.
This session will help you get familiar with SQL Server Machine Learning Services. We will go over its components and features, and understand how it brings data scientists and developers closer. As an example, we will build a Predictive Model using R and SQL Server Machine Learning Services.
As data professionals, we need to aim towards the most efficient way of provisioning production data to non-production environments while remaining compliant with data protection regulations.
Trying to get some tips to start using Azure Data Warehouse? Do you know how Azure Data Warehouse is different from Azure SQL Database? Trying to process Terabytes of data in only a few minutes?
This session will answer and expand upon each one of these questions. Azure Data Warehouse was released 4 years ago and has been maturing across its lifetime.
Join the February QSSUG meetup! In this session, Darren Dawson will take you through the how, when and why for implementing partitioning in your databases, and the common pitfalls to avoid.
We’ve made some changes to the organiser team, venue and date for the Queensland SQL Server User Group. Firstly, Microsoft has finished their renovations which means we can move back to our original venue, Microsoft Brisbane, Level 28, 400 George Street, Brisbane. Secondly, we’ve had to change the date to the first Wednesday of each month. […]
SQL Server Managed Instance, the PaaS Instance Offering With the pending release of SQL Server Managed Instance, the capabilities of the product as a near 100% compatible with an on premises instance will be discussed. What will be addressed are the capabilities of the product, features that are supported, how to migrate with the azure […]
In this presentation you will learn that data storytelling is a structured approach for communicating data insights and unlocking value in data which involves a combination of three key elements: data, visuals, and narrative.