In this session, we are going to explain and test different DW features in SQL Server 2012, including star join optimization through bitmap filters, table partitioning, window functions, columnstore indices and more.
This session will cover advanced security topics in the Analysis Services Multidimensional model.
Most of us use Excel in our Daily work, but are you familiar with the Business Intelligence features in Excel? In this session we'll look at some of the most common and useful BI features in Excel 2010 and discuss limitations and best practices.
Snapshots without snapshots...is that possible? Take a "Classic" snapshot fact table, add some temporal data theory and you'll get a new fact table than can store snapshot data without doing snapshots. A life saver when you have a lot of data.
Deep dive into the handling of many to many relationships in DAX. How to make them work and how to optimize their speed thorugh many patterns and live examples of M2M usage.
Learn how to leverage the data model to create flexible behaviour in a cube without the overhead of calculated members
This session will introduce the concept of scoped assignments in MDX and show how they can be used to solve various calculation problems.
Cube tuning is a key part of any BI project and it gets more so as cubes get bigger. Here are a series of tuning procedures to follow for cubes large and small.
Learn about the most frequently made Analysis Services design mistakes, the problems they cause, and how to fix them or not make them in the first place
Learn to tune Analysis Services 2008 query performance
A step-by-step demo on BIDS of how to build an SSAS cube (DB) from an operational system (normalized database) such as Operational Data Store (ODS) or directly from the transactional business system, without building a star/snowflake schema Data Warehouse/Mart first.
Learn how the Analysis Services cache works, and how you can pre-load it with data to ensure optimal query performance.
Among many of its functions, MDX language has one special set function - Axis() function. That function allows creation of calculated measures that are context aware and, if wanted, don't need to refer to any dimension or hierarchy in the cube. In other words, such measures are universal or independant, which means they can be used in any MDX query.
In this session we will present such measures and explain how they work. We'll also show the way how to design them for various scenarios and discuss their potentials and weaknesses.
Previous experience in writing MDX queries is recommended.