4th - 7th May 2016


Content Type

Sessions & Content

Think you know MDX? This session will show you some advanced, little-known but nonetheless practical tips and tricks for writing complex calculations and making your queries run faster.
Tabular offers only one-to-many relationships on a single column: it seems poor when compared with Multidimensional. However, with DAX, you can handle any relationship. We analyze and solve scenarios with calculated, virtual and complex many-to-many.
A SSAS MDX Deep Dive session covering the implementation of a business requirement to identify rogue behaviour over time and within SCD organisation groups.
Data warehouse designers often ignore the specific needs of an OLAP database. In this session, John will outline the best ways to optimise your relational database to support your multidimensional OLAP cubes
Power BI offers new features for creating dashboards on the cloud. In this session, you will learn how to create data models, display visualizations and synchronize cloud data with on premise data sources.
In this session, we will share some of the hard lessons learned from the first large deployments in Analysis Services Tabular.
Do you need an OLAP database? Do you know how the data changed over time? Do you need an OLTP database? Do you need to write, never block and never lose a change? Then Temporal Databases tick those boxes and are a simple solution to these problems.
Each of the default SSAS client tools (Pivot Tables, SSRS, Power BI etc.) have strengths, but numerous limitations. See how XLCubed extends business users abilities in reporting, dashboards & data discovery, in any version of of SSAS & Office.
This session goes beyond the classical star schema modeling, exploring new techniques to model data with Power Pivot and SSAS Tabular. You will see how brute-force power in DAX allows different data models than those used in SSAS Multidimensional
In this session Pyramid analytics will show how to use BI Office to easily build an adhoc Analysis Services Tabular Edition analytic data set and perform associative analysis using the unique features of BI Office.
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