It is pleasure to let you know that we will be in Australia: Sydney, and Melbourne February 2016 to deliver SSIS and Machine Learning Courses. Courses are adjusted to a one-day program with heaps of demos and handouts for audience. Our courses designed in a pragmatic approach in the way that enables you to start getting benefits from the course from the moment you step into room. You will be able to build Azure Machine Learning solutions and build your ETL design patterns with SSIS easily after these programs.

Here are schedule of courses:

SQL Saturday Melbourne: 19th of Feb 2016

Being Smarter: A Tour of Machine Learning by Leila Etaati

ETL Design Patterns with SSIS by Reza Rad


 SQL Saturday Sydney: 26th of Feb 2016

Being Smarter: A Tour of Machine Learning by Leila Etaati

ETL Design Patterns with SSIS by Reza Rad


Details of courses:

ETL Design Patterns with SSIS


There are some challenges in implementing ETL for real world data warehouse. In this one day conference we will deep in dive for challenges such as; Inferred Dimension Member, Slowly Changing Dimension, Late and Early Arriving fact tables, Durable natural Keys, Accumulating fact tables. SSIS best practice and practical solution will be discussed and you will see live demos of solving above challenges with SSIS (combined with MDS sometimes). Challenges above are avoidable in most of the data warehouses, so a pragmatic solution with considering best practices would be necessary learning for every ETL and BI developer, consultant, and architect.


Each challenge will be discussed in this way; defining the problem, exploring what is data warehousing solution for the problem, exploring issues of ETL implementation for that solution, elaborating different methods to implement the solution, proposing the best practice and practical real world ETL solution for the problem with many live demos.


Being Smarter: A Tour of Machine Learning

In this pre conference session the audience will become familiar with machine learning concepts, how to prepare data for predictive and descriptive analysis and choosing the best model, how to formulate business problems into a machine learning experiment. We will also cover how to interpret the machine learning results, data mining and some statistics and will follow up with a discussion on how to choose the best algorithm and which algorithm can be suitable for which type of problems.

The audience will learn how to work with on premises based technologies like SQL Server Analysis Services Data Mining engine, the DMX language and the Excel Data Mining add-on. And they will also learn how to work with Azure ML as a cloud base machine learning and how to use R with Azure ML. We will use Azure ML, Azure ML with R, RStudio, SSDT, .Net, SSMS, Excel and the Azure Portal.

Time breakdown:
50% Lecture,
30% Demos
20% Student Labs


SQL Saturday Sessions

We also deliver regular SQL Saturday sessions as below:

Melbourne: Power BI Rises; Wonderful Things You Can Do by Reza

Melbourne: Being Smarter with Azure Machine Learning and R

Sydney: Azure Data Factory vs SSIS by Reza

Sydney: A Journey into Azure Machine Learning by Leila