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.
Organizations risk being overwhelmed by data. How can you effectively provide a “single version of the truth”, while unlocking the key trends and insights that will allow your business to succeed? Come to this session to find out how.
Do you have complex dimensions in your data warehouse? Parent-child, late arriving, type 3 or type 6? In this session, we'll cover some SSIS patterns for handling each of these, along with tips for making them perform well.
Steps involved in implementing a near-real-time data warehousing solution.
Master Data Services has been given an overhaul in Denali, including a new Excel add-in and modified web front-end. Come to this session to see how MDS can be used to give greater control and process to your BI/DW dimension management.
When loading a Fast Track Data Warehouse it is important to ensure that your data is optimally laid out for Sequential I/O. Fragmentation is therefore the enemy. Know your enemy. Learn what it is, how it occurs and prevent it from happening to you!
In this session we will introduce the new modeling capabilities of Vertipaq, showing how the same scenarios can be modeled in both Multidimensional (MOLAP) and Tabular (Vertipaq), looking at how to enable your data warehouse to support both.
Many of us know what dimensions and fact tables are. But dimensional modelling is more than just dimensions and fact tables. This session is about advanced dimensional modelling topics, which are useful for anybody involved in the design of a DW.
A new and fresh approach to datwarehousing that is agile, performant and easy to do. Data Vault is a new methodology that tries to overcome traditional problems that plagued traditional datawarehousing in the past.
This session is taken from lessons learned in the field on being able to scale data models to handle multi-terabytes of data. Come to this session and understand the difficulties before you encounter them.
A step-by-step demo on BIDS of how to build an SSAS cube (DB) from an operational system (normalized database) such as Operational Data Store (ODS) or directly from the transactional business system, without building a star/snowflake schema Data Warehouse/Mart first.
Data warehousing features in SQL 2008
In this session we will take a deeper look at how SQL Server uses I/O and how you can design the I/O system to meet the requirements of your applications.
In this presentation, I will introduce the Madison architecture and provide a roadmap with major milestones for this product
Designing dimensional and fact tables using a case study to understand data modelling