Date and time-stamped dimensions are dimensions that track the history of changes in the dimension tables themselves. (Star Schema, 2012) The easiest way to think about these type of dimensions are regular data dimensions that have the added columns necessary to show each record by a specific date or [...]
As we slowly move towards a more data focused society as well as with companies well entrenched in the usage of data, analytics, and business intelligence we see that analysts that are hyper-focused in their area of expertise and job function are increasingly more capable with the nitty-gritty details. However, you’ll see that the [...]
For some this will be a no-brainer and for those I apologize, however for a good majority of you I think this is going to be a good post to remind you that any report you are building whether in Cognos, SAP, MicroStrategy, Microsoft, or what have you, strive to always do [...]
A Data warehouse is a repository of an organization’s electronically stored data. Data warehouses are designed to manage and store the data whereas the Business Intelligence (BI) focuses on the usage of data to facilitate reporting and analysis. The purpose of a data warehouse is to house standardized, structured,
![041902_schraml_2[1]](/wp-content/uploads/2011/07/041902_schraml_21-150x150.gif)
There are three types of slowly changing dimensions: Type 1, Type 2, and Type 3. Each of these types tries to help the designer of the star schema eliminate paradox from their dimensional model (just as the three interpretations of the Schrödinger’s Cat thought experiment tries to eliminate the paradox of the living dead).
![h-00100020000_image002[1]](/wp-content/uploads/2011/05/h-00100020000_image0021-150x150.gif)
The reporting, analysis, and interpretation of business data is of central importance to a company in guaranteeing its competitive edge, optimizing processes, and enabling it to react quickly and in line with the market.
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