Alex Whittles

Power BI and Microsoft Fabric have become the data hub for your organization. Whilst incredibly powerful, this also brings significant risk. This session looks at how you can protect your organization, your data, and yourself, through effective governance, auditing and disaster recovery. This will cover license reduction, FinOps, risk reduction, auditing, and using off-the-shelf AI to automate governance tasks to improve adoption and trust.

Power BI and Microsoft Fabric have become the data hub for your organisation. Whilst incredibly powerful, this also brings significant risk. This session looks at how you can protect your organisation, your data, and yourself, through effective governance, auditing and disaster recovery. This will cover license reduction, FinOps, risk reduction, auditing, and using off-the-shelf AI to automate governance tasks to improve adoption and trust.

As organizations scale their use of Power BI and Microsoft Fabric, many find that early success quickly leads to complexity: uncontrolled workspace sprawl, unclear ownership, inconsistent security, and growing governance risk.

Power BI and Microsoft Fabric have become the data hub for your organization. Whilst incredibly powerful, this also brings significant risk. This session looks at how you can protect your organization, your data, and yourself, through effective governance, auditing and disaster recovery. This will cover license reduction, FinOps, risk reduction, auditing, and using off-the-shelf AI to automate governance tasks to improve adoption and trust.

Take Power BI to the next level to support BIG data, as well as layering logic over the top of an existing cube or dataset for unlimited flexibility. This session will look at composite models as well as Direct Query over Datasets and DirectLake in Fabric, to see how they can enhance our Power BI world.

Microsoft Fabric is here, but what is it and why is it needed? This session will give you a solid understanding of what Fabric is, the architecture, how data warehousing and data lakes fit into Power BI, and why it's the future for our data engineering and data analytics projects.

With the introduction of Microsoft Fabric, taking control of your rapidly growing Power BI estate provides an ever-increasing challenge. In this session we’ll look at how we can monitor activity, structure Power BI and Fabric for better management, and increase transparency. This will cover...

As your Power BI usage grows you need to think carefully about how to plan and manage your tenant so you don't lose control of it and end up in Power BI Hell. In this session we'll cover how to think about workspaces, Apps, security, dataset re-use, endorsements, data lineage, DevOps, monitoring and auditing, in order…

Take Power BI to the next level to support BIG data, as well as layering logic over the top of an existing cube or dataset for unlimited flexibility. This session will look at Composite Models as well as Direct Query over Datasets, and Hybrid tables to see how they can enhance our Power BI world.

Learn how to take Power BI to the next level to support BIG data, layering logic over the top of an existing dataset for unlimited flexibility, and find out how hybrid models can help bridge the gap between Direct Query and Import. This session will look at 'Composite models' as well as 'Direct Query over Datasets' and 'Hybrid models' to see how they can enhance our Power BI world, as well as understanding the pros, cons and use cases of each. Using a combination of live demos and theory, this session will explain and show the concepts, leaving you ready to experiment with your own data.

Looking at the code & approach to a number of hands-on Machine Learning projects, including: - Creating a basic predictive model and deploying as a web service - Using pre-built Azure Cognitive Services - Using Python to build a deep learning neural net that can play games

Machine Learning is a popular buzzword, but what does it actually look like, and how can we use it? This session will show a number of high level examples of using ML to do some useful and fun stuff, including training a model to play a game