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
You have tuned your SQL server to it's limits, you have maxed the RAM on your server, and still your data warehouse is too slow. Is a Parallel Data Warehouse the next step?
Big Data has triggered the need for organisations to build real-time Operational Data Store (ODS) layers to feed the ‘Data Lake’ on Hadoop. Attend this lunchtime session to learn why a real-time ODS should be at the heart of your data architecture
T4 templating will be a first class citizen in SSDT for SQL Server 2014. This session will show why you should use this technology for SQL code generation and how you can automate the process. The session will be demo rich.
A deep dive in the internals of the database architecture, discovering how Vertipaq stores information, in order to gain better insights into the engine and understand the best way to model your data warehouse to leverage the features of VertiPaq.
“Just use partitioning” is the answer you hear, when you need to manage very large data sets in your Data Warehouse. But how do you design and implement it? We will walk through different ways to design partitioning, including layered partitioning.
This session will discuss what a modern strategy for data warehousing can be in this era, considering how the use of technologies like PowerPivot or Analysis Services Tabular affect the way you should model your data.
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.
: We are looking at the dawn of a new workload: BigData. In this session I will talk about what BigData is, and which BigData technologies Microsoft are working on.
Users love flexible analytics but hate to wait for the data to be loaded into a traditional data warehouse. John will describe how to build an infrastructure to support real-time loading of your OLAP cubes so your user's get exactly what they want