The employee dimension presents one of the trickier challenges in data warehouse modeling. These five approaches ease the complication of designing and maintaining a 'Reports To' hierarchy for ever-changing reporting relationships and organizational structures.
2009-08-26
3,651 reads
This paper provides an overview and guide to SQL Server® Fast Track Data Warehouse, a new set of reference architectures created for scale-up (SMP) SQL Server based data warehouse solutions. It includes a summary of the resources available in the reference configuration, the distinguishing features of the approach, and the steps necessary to take full advantage of the new architectures.
2009-06-26
4,002 reads
How can you do more with less? Follow this data warehousing/BI strengthening regimen to cut cost, avoid expenditures and bulk up the bottom line.
2009-03-24
2,851 reads
Visit ten randomly picked customers that own a data warehouse architecture, and you will see that at least eight have developed a classic data warehouse architecture (CDWA). What do I mean by a CDWA? In a CDWA, data is copied periodically from production systems to the central data warehouse.
2009-03-20
6,058 reads
At first glance, a client appeared to be violating a cardinal rule of data warehousing. However, Bill Inmon's further investigation revealed that perhaps their actions were acceptable.
2008-12-29
2,789 reads
The following article shows how Change Data Capture can be used to capture incremental data changes and use them in an ETL Process
2008-11-10
3,814 reads
This paper introduces the new performance and manageability features for data warehousing across all these components. All these features contribute to improved scalability.
2008-10-17
2,632 reads
Data warehouses aren't just exploding in size, they're also supporting more users and increasingly complex queries, all in shorter time frames. Here's how to make sure yours is ready to scale.
2008-10-16
2,707 reads
Capacity planning is a problem for a data warehouse because it sets contrasting functional requirements against each other. On one hand, data warehouse customers consume data warehouse capacity as they query the data in the data warehouse business intelligence (BI) reporting. Meanwhile, applications consume data warehouse capacity as they load data into a data warehouse through the extract, transform and load (ETL) process.
2008-09-19
3,269 reads
Murphy’s Law tells us that whatever can go wrong will go wrong. This axiom applies to all aspects of life, including data warehousing. The following corollaries to Murphy’s Law relate this inevitability of something going “bump” in the night to data warehousing.
2008-09-15
3,411 reads
By Brian Kelley
Here is another short video (~ 15 minutes). This is by the author of...
By Steve Jones
I had a briefing for the 2026 PASS Data Community Summit, which is just...
Your AI is busy. But do you know what it's worth? Most companies can...
Hello, We maintain an inventory table that captures monthly snapshots of item inventory levels....
Comments posted to this topic are about the item Azure SQL Hyperscale Unveiled
Hi. What is the most difficult aspect of using monitoring software like idera, redgate,...
What are vectors in SQL Server 2025, as related to the new AI features?
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