Event Date: 17-09-2016 - Session time: 09:00:00 - Track: Room 3
Also ideas/samples of potential use cases.
Event Date: 17-09-2016 - Session time: 09:00:00 - Track: Room 1
However, in order for R to do its magic it needs data so historically we have imported data from various sources, SQL Server being one of those sources. In SQL Server 2016, Microsoft has embedded R in the SQL engine. Yes, we do now have access to R natively in SQL Server.
Event Date: 17-09-2016 - Session time: 09:00:00 - Track: Room 2
In this session we will discuss a key approaches that you can use to design simple, easy to use data warehouses.
Event Date: 17-09-2016 - Session time: 10:15:00 - Track: Room 1
Event Date: 17-09-2016 - Session time: 10:15:00 - Track: Room 2
In this session we’ll take a look at what the QueryStore is and how it works, before diving into a scenario where overall performance suddenly degraded, and we’ll see why QueryStore is the best new feature in SQL Server 2016, bar none.
Event Date: 17-09-2016 - Session time: 10:15:00 - Track: Room 3
These relatively infrequent changes do not hone the skills needed for effective design.
This session will go through the fundamentals of database design. Topics such as normalization, Understanding Data Relationships as well as the Language of Data Modeling and Design will be discussed. The Database Design Sequence Phases of Conceptual, Logical and Physical will be introduced as well.
Event Date: 17-09-2016 - Session time: 11:30:00 - Track: Room 3
In your organization you have data stored all over the place, and your data may not always be relational. In this talk we will see how you can handle both relational as well a non relational data in SQL Server 2016. Among the things we will talk about are JSON support, Hadoop and Polybase.
Event Date: 17-09-2016 - Session time: 11:30:00 - Track: Room 2
Event Date: 17-09-2016 - Session time: 11:30:00 - Track: Room 1
The principals described in this approach have been applied and refined, especially within the Hadoop ecosystem. However in this talk we will look at using some of the Microsoft Azure based technologies, specifically Azure Stream Analytics and Azure Data Warehouse to implement this approach to data management and realize some of this benefits of this architecture.
Event Date: 17-09-2016 - Session time: 13:30:00 - Track: Room 1
Event Date: 17-09-2016 - Session time: 13:30:00 - Track: Room 3
Transactions are critical when multiple changes need to be made entirely or not at all, but even given that it’s rare to see transactions used at all in most production code
In this session, we’ll look at what transactions are and why we should use them. We’ll explore the effects transactions have on locking and the transaction log. We’ll investigate methods of handling errors and undoing data modifications, and we’ll see why nested transactions are a lie.
Event Date: 17-09-2016 - Session time: 13:30:00 - Track: Room 2
SSIS has loads of little settings and “hidden” features that can be tweaked, modified and changed to turn an standard package into a proper solution.
This presentation is just a highlight of some of the Tips, Tricks and Design Patterns that can be used to make your SSIS experience a joyful one.
Event Date: 17-09-2016 - Session time: 14:45:00 - Track: Room 3
For something like SQL server there are so many options: on-premise server, off-premise server. On-premise server with off-premise data. Then there are the various Azure offerings with fancy names like Azure SQL, Data Lake, Hadoop.
You also get graph databases and document databases.
This session will cover some of the more popular types of data stores that are available today and we will look at their use cases. While SQL server is great for many things, one has to be aware of the other options that are available out there.
Event Date: 17-09-2016 - Session time: 14:45:00 - Track: Room 1
Event Date: 17-09-2016 - Session time: 14:45:00 - Track: Room 2
Normally this type of problem is followed by someone blaming a process or shouting about peer reviews or arguing about training… What if there was a better way? Is it possible to create a short list of guidelines for non-Database developers to follow that remove almost all of the pain points?
Let’s find out!