Sessions & Content

Tags
Content Type
Search
Conference
5+ Database Design Blunders and How to Avoid Them
Karen discusses five (plus a few more) database design blunders with tips on how to avoid them. Audience members will also be able to contribute their war stories of design fails, WTHs and D'ohs.
A Deep Dive in SQL Server 2012 Data Warehousing
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.
A heap of clusters
An in-depth dive into physical table structures
Building a BI Portal for Tabular Models
The Microsoft BI stack has a number of tools for data visualization - Excel, Power View, native Reporting Services, and Performance Point. Come see each visualization applied to the new tabular model in Analysis Services.
Load Testing Analysis Services
Ever deployed an Analysis Services cube that worked perfectly well with one user on the development server, only to find that it doesn’t meet the required volumes of user concurrency?
Loading Data Warehouse Dimensions in SSIS
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
Performance investigations with Analysis Services 2012
This session will do a brief overview of Analysis Services 2012 performance topics, and drill into some common methods for investigating performance issues. The talk will be adjusted based on the audience interests.
Revealing the Magic
In this deep(!) dive session. I will walk you through the internal storage format of MDF files. I'll cover how SQL Server stores its own internal metadata, how it knows where to find your data, and how to read it once found.
ROLAP with Column Store - Deep Dive
The Column Store Index is an exciting new technology in SQL Server 2012. Using column stores, you can unlock new levels of performance for data warehouses – often gaining an order of magnitude speedup on queries.
Spatial Data “Stretches Out” in SQL Server 2012
The addition of spatial data to SQL Server 2008 is one of the most important in terms of integration in line-of-business applications. This talk will discuss the new features and performance enhancements in SQL Server 2012.
SQL Server 2012: Column store indexes
This session will present you with a fascinating behind-the-scenes deep-dive view of the new column store index feature. How do column store indexes work? How are they built? And how can they yield such enormous performance boosts to some workloads?
SQL Server Indexes : The forgotten Fill-Factor
The fill-factor index option has a huge impact on the performance of your DB. By using a different approach for specific use cases this session will give you the tools to find the most optimal fill-factor for your tables.
System Center Advisor Deep Dive
System Center Advisor assesses your servers’ configuration and helps you proactively avoid downtime, performance degradation, and data loss. It only takes 5 minutes to setup and is accessible wherever you have a web browser.
Temporal Snapshot Fact Table
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.
The NUMA internals of SQL Server 2012
This session reviews the purpose of NUMA, how it changes the internal behaviours of Windows and SQL Server 2012 and NUMA related performance monitoring.
Troubleshooting TempDb
For the most DBAs and DEVs the TempDb is a crystal ball. But the TempDb is the most critical component in a SQL Server installation and is used by your applications and also internally by SQL Server.
TSQL Performance Tips
SQL Server optimizer doesn't use and index seek for execution of your query although the query is high selective? What is better, when and why: LIKE vs: SUBSTRING, IN vs. EXISTS, SUBQUERY vs. JOIN. Why you should not use the UPPER or LOWER functions?
<<1>>