When building a data warehouse, you often need to flatten the data when you move it from the Raw tables to the Stage tables. Flattening data can be a difficult concept for new warehouse designers to grasp, so here are two detailed examples.
If you're inexperienced with using SSIS, creating a data warehouse might seem like an impossible task—but it's not if you use some different strategies. For example, you can use a wizard to initially create an SSIS package that will move data from the source system into the data warehouse.
Don’t let bad data sneak up on you when and where you least expect it. Ferret out bad data with Melissa Data’s newest Profiling Component for SSIS. Learn how to take control of your data using knowledge-base-driven metadata. The truth shall set you free!...More
In my previous post, I provided a high-level outline of the core logic (and rationale behind that logic) that would be needed to set up regular synchronization checks on SQL Server Agent Jobs for servers where AlwaysOn Availability Groups have been deployed. In this post, I’ll walk through the steps--and the code--needed to setup those checks....More
Now that we’ve outlined the process to let servers in a SQL Server AlwaysOn Availability Group "talk to each other" by means of setting up linked servers, it’s possible to set up some additional or improved checks on Availability Group Health....More