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.
In my previous post I covered options for adding “If-checks” into SSIS Packages – or SQL Server Maintenance Plans (which are, effectively, specialized SSIS packages). Once you’ve tackled that process, you’ll need to tackle something else when it comes to managing SSIS packages in conjunction with AlwaysOn Availability Groups. Or, more specifically, you’ll actually need to tackle two tasks....More
In my last post, we took a look at some of the details involved in actually implementing backups against databases being hosted in AlwaysOn Availability Groups. In addition to providing a high-level overview of how sys.fn_hadr_backup_is_preferred_replica() works, I also mentioned that integrating it into backups managed by SQL Server Maintenance Plans isn’t as easy as what you’ll run into with other types of backups....More