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Sessions & Content
Sessions & Content
Tags
partitioning
(15)
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Video
15
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Conference
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Introduction to partitioning
Session will be aimed at Database Administrators\Developers who have not previously implemented partitioning within an OLTP database and is designed to give a overview into the concepts and implementation.
A Deep Dive Into Data Lakes
Learn the ins and outs of Azure Data Lake in this deep dive
Designing a database to best support multidimensional OLAP
Data warehouse designers often ignore the specific needs of an OLAP database. In this session, John will outline the best ways to optimise your relational database to support your multidimensional OLAP cubes
Superscaling SQL Server 2014 Parallel Insert
This session will take a look at how parallel select into can be scaled to the nth degree in SQL Server such that all available hardware resources are utilised as fully as possible.
When good SQL design goes bad
In this humorous session I’ll be contesting many of the so called "best practices" in SQL Server and demonstrating counter arguments. Come along to see how so called "pillars" of design are starting to break down.
Effective Index Partitioning, Compression Strategy
We all know that ‘Indexing’ is KING when it comes to achieving high levels of performance in SQL Server. When Indexing also combines 2 of the Enterprise features: Partitioning & Compression
Patterns & Practices for Scaling Windows Azure SQL Database
This session will discuss the recommended approaches and best practices for partitioning and scaling Windows Azure SQL Database, allowing you to fully leverage the managed relational database service and take advantage of massive scale-out scenarios.
Incremental processing of SSAS Multidimensional databases
Processing of SSAS OLAP databases can be a tricky business, particularly when it comes to incremental processing of dimensions. John will give you real life examples of why certain approaches work and others do not.
Layered Partitioning - manage very large data sets
“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.
Scaling Out SSIS With Parallelism
An introduction to scaling out packages using parallelism with the "Work pile" pattern, balanced data distributor and "Roll your own" techniques.
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