This session covers the more advanced aspects of development for Azure SQL Data Warehouse. Areas such as data movement, workload concurrency and resource management will all be covered during this intense 60 minute session.
Virtualization has had a major impact on computing. While data professionals have adjusted to this for database servers, many BI workloads have moved there as well. Learn about the impact of virtualization on BI.
Data Warehouses are changing. This session will run through the architecture of the modern warehouse, from structured/unstructured Azure Data Lakes to platform as a service Azure Data Warehouse and bringing the two together.
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
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.
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.
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
This session looks at some of the different methods available to load slowly changing dimension data into a data warehouse, and compares the relative performance given different data scenarios and traditional storage compared with FusionIO
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.