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.
An option when creating new AlwaysOn Availability Groups is to specify Backup Preferences.
It’s also something you can easily configure once the Availability Group has been set up as well – by simply right-clicking on the Availability Group and selecting Properties – then navigating into the Backup Preferences tab. ...More
The quest for the Golden Record to achieve a single, accurate and complete version of a customer record is worth the pursuit to attain survivorship. Record matching and consolidation are only the beginning. Melissa Data takes a new approach. Learn how to apply intelligent rules based on reference data to make smarter and better decisions for data cleansing....More
On SQL Servers where Availability Groups (or Mirroring) isn’t in play, I typically recommend keeping a combination of on-box backups along with copying said backups off-box as well. Obviously, keeping databases AND backups on the SAME server is the metaphorical equivalent of putting all of your eggs in one basket – and therefore something you should avoid like the plague....More