Archives: Schedule

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Posted on by brisbanebootcamp

An Introduction to Cosmos DB

Knowing data is crucial when it comes to design – and data Professionals have this skill refined.
But knowing implementation detail is also important.
While there are similarities between SQL and Cosmos DB, there are also some large differences – some of which may surprise the SQL Professional.
Sometimes an implementation oversight can bite you hard at the wrong time – and at a time when correcting that oversight might be costly and problematic.
Come along to this session and find out why a Primary Key is not what you think, tables are not equal to containers and a few other details that might surprise you.
This session will help anybody with SQL Server knowledge to compare the relational database to the NoSQL models available in Cosmos DB.
A version was presented at the 2022 PASS summit.

 

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Posted on by brisbanebootcamp

(Workshop) The eleven rules of DAX management

We will conduct a workshop on the 11 rules that need to be followed to manage DAX in a Power BI model before they are published to production. DAX management ensures your
code is

Auditable
Performant
Readable
Consistent
Discoverable

We will start off with a Power BI model, define some measures and apply these 11 rules. Apart from Power BI Desktop, participants also need to install DAX Studio and Tabular Editor 2

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Posted on by brisbanebootcamp

Maximise Your APIs with a Digital Integration Hub

Data is at the heart of every organisation, and the ability to share that data reliably and efficiently in a controlled manner with internal and external consumers is critical to business operations. But how to expose multiple sources of truth across a host of different interfaces whilst maintaining performance and security? Let Dan show you how a Digital Integration Hub can be the answer!

 

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Posted on by brisbanebootcamp

(Workshop) Getting Started with Machine Learning using ML.NET

Want to get started with machine learning but don’t know where to start? Have you got an Excel spreadsheet, SQL Database or CSV lying around and wondering if you can use it to experiment with Machine Learning?

In this workshop, we’ll start from a CSV exported by a service, and go all the way to an application that uses Machine Learning to make clever decisions.

We will cover:
1. What does a developer need to know about Machine Learning?
2. How does ML.NET help getting started with ML?
3. Quickly prototype a solution with ML.NET Model Builder
4. Improve solution with simple data science rules
5. Integrate a machine learning solution into your application
6. Continuously improving machine learning model and updating applications

 

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