David Peter Hansen
David Peter Hansen is a Microsoft Certified Master (MCM) and has over a decade of experience with database development and administration on SQL Server and the Microsoft Business Intelligence platform. Today, he works as Consulting Manager at Advectas. He specializes in developer coaching as well as scalable architecture and performance tuning on large-scale data warehouses and BI solutions. He is a frequent speaker at conferences, and have given talks in Europe, USA, and South Africa.
David Peter Hansen has submitted 4 sessions for SQLBits XIV, although the agenda hasn't been chosen yet. See all submitted sessions
When loading a large amount of data, e.g. into your data warehouse, you want the data inserted into the table as fast as possible. You know you have to use bulk load, but what do you need to do to ensure that data is loaded as fast as possible?
Deployment to production is typically a manual process and can take a lot of time. Many companies use continuous integration for testing their software and continuous deployment to push code to production. But what about SQL Server development?
Your relational Data Warehouse is suffering from performance problems. In this session we will take a look at some of the most common performance problems that tend to occur in a relational data warehouse.
One day we woke up and SQL Server were cloud-ready. But is the cloud ready for SQL Server? 2014 got a number of new features that are related to Azure. What's up with that? And what is this hybrid cloud thing that people keep talking about?
“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.
In this session, you will learn what SSIS is, what components it consists of, and how to use the SSIS catalog to track the execution of packages and how to troubleshoot packages.
In this session, you will learn the internals of SSIS and why having a deep understanding is important to solve performance problems, and how the control flow and data flow engine work.