SQL Server Magazine

Many-to-Many Relationships in the Data Warehouse

Learn how to model your database to support both market basket and affinity analysis.

Who Can Do Backups?

Backup and Restore Fundamentals

Back up your SQL Server databases regularly to prevent lost data in the event of a disaster.

Data Warehousing: Degenerate Dimensions

Find out how to map control numbers to a fact table and associate them with each line item.

Data Warehousing: Junk Dimensions

Find out how you can keep your data warehouse design simple by placing miscellaneous attributes into junk dimensions.

Alternative Backup Strategies

Learn about advanced SQL Server backup options.

Data Warehousing: Horizontally Partitioning the Fact Table

Save yourself from having to deal with large, difficult-to-manage fact tables by partitioning the rows.

Who Can Do Backups?

Find out who can do database backups in your organization.

Database Recovery Models

Database recovery models include full, simple, and bulk-logged.

Standard Backup Commands

Learn the difference between DUMP and BACKUP.

Replacing a Database

Learn when to use the REPLACE option.

What Is a Tail-Log Backup?

In SQL Server 2005, a tail-log backup captures records on the transaction log that were written since the last transaction log backup.

How Do I Recover To A Point in Time?

Restore a database to a point in time.

Why Can’t My Database Restore Be an Online Operation?

Learn why you can’t access a database while it’s being restored.

Data Warehousing: Rapidly Changing Monster Dimensions

You can manage rapidly changing monster dimensions by splitting the stable and hot attributes or by creating non-overlapping value ranges for each rapidly changing attribute.

Data Warehousing: Rapidly Changing Monster Dimensions

Data Warehousing: Slowly Changing Dimensions

When dealing with slowly changing dimensions, you can respond in three different ways. Find out what these responses to change are, and under what circumstances each response type should be used.

Data Warehousing: Dimensional Role-Playing

Dimensional roles can play many different parts in an accumulating snapshot fact table. Find out how dimensional role-playing can benefit your star schema.

Indexed Views

If you ever have rows in the dimension that participate in more than one role, it's best to use indexed views rather than partitioned tables.

The Data Warehouse Bus Architecture

Find out how conformed dimensions and facts make up an enterprise data warehouse.