In this case, the dimension tables are fully normalized, reducing the space they occupy, although in some cases this difference is not https://www.zotero.org/sonyapadilla/items/itemKey/F5RKQUCQ significant. With the construction of the previous model only analyzed the tickets sales.
However, we can do the same to analyze the items sold in each of the tickets sold. The level of detail in the analysis is queue https://delicious.com/troybryan management what we call granularity.
In case you want to analyze each of the sales, the granularity is greater than if we want to analyze are selling tickets. http://www.stumbleupon.com/su/30wnN1/1OsRaZGS3:p5!EOb2Q/wandacook.virb.com/ We must decide the level of granularity needed to build a model that allows us to answer those questions.
We have formulated as to determine a level of granularity can answer some questions but not others. Let us now begin with the http://www.stumbleupon.com/su/452OVm/.7tRhPTh:p5!EOb2Q/wandacook.virb.com/are-your-electronic-documents-secure/14076305 analysis of the items sold.
The model which we break allows us to analyze the items for families and subfamilies, but also by the various manufacturers. We will https://www.diigo.com/user/rodneychavez be interested to know what the racial families, subfamilies or manufacturers total sales. This analysis is much more interesting if we can do by center, as it will allow us to understand the possible local differences.
Again, the first step in building the model star is to decide what should be the fact table. What are we analyze sales items, so we need http://www.reddit.com/r/technology/comments/2jeey6/queue_management/ the highest level queue management of detail, our fact table must have all lines of selling tickets.
We have omitted some attributes like id box as we believe that we will not provide information that allows us to improve http://www.reddit.com/r/technology/comments/2jefsi/queue_management_system/ management.
Let our scheme star of the lines for tickets sales. We have a fact table and six dimension tables. We have added the dimension table http://oknotizie.virgilio.it/info/5054c2390b6d779e/queue_management.html of items from the previous model of the tickets sales, allowing us to analyze sales by subfamily.
Family or company, and we have not considered analyzing the lines of the tickets sold payment method dimension: not queue http://oknotizie.virgilio.it/info/5055c231dd87ccdb/queue_management_system.html management have excessive sense as a whole ticket sales is paid by the same form of payment and this information and provides us the old model of selling tickets.
Might ask why we have not incorporated the attribute No. Description in the table Item Dimension; the reason is that if we do the http://www.dzone.com/links/queue_management_2.html analysis for items and once manufacturers need to be in different dimensions, and, if they are the same, it can not do.
This model allows us to analyze the sales of the items by queue management the size of the center, by the dimension date, slots, http://linkagogo.com/go/SiteSee?i=99801636&i=99801625&t=queue+management+s..&t=queue+management employees, manufacturers of articles and article.
In our system of ticket sales information it is possible to modify the selling price of the item. Comparing information from tickets http://www.dipity.com/sherrybradys/queue-management/ sales with articles and differ per employee, we can know who the great discounts that apply. If we analyze in detail the time dimension, we see that a hierarchy of time appear in this dimension.
However, we can do the same to analyze the items sold in each of the tickets sold. The level of detail in the analysis is queue https://delicious.com/troybryan management what we call granularity.
In case you want to analyze each of the sales, the granularity is greater than if we want to analyze are selling tickets. http://www.stumbleupon.com/su/30wnN1/1OsRaZGS3:p5!EOb2Q/wandacook.virb.com/ We must decide the level of granularity needed to build a model that allows us to answer those questions.
We have formulated as to determine a level of granularity can answer some questions but not others. Let us now begin with the http://www.stumbleupon.com/su/452OVm/.7tRhPTh:p5!EOb2Q/wandacook.virb.com/are-your-electronic-documents-secure/14076305 analysis of the items sold.
The model which we break allows us to analyze the items for families and subfamilies, but also by the various manufacturers. We will https://www.diigo.com/user/rodneychavez be interested to know what the racial families, subfamilies or manufacturers total sales. This analysis is much more interesting if we can do by center, as it will allow us to understand the possible local differences.
Again, the first step in building the model star is to decide what should be the fact table. What are we analyze sales items, so we need http://www.reddit.com/r/technology/comments/2jeey6/queue_management/ the highest level queue management of detail, our fact table must have all lines of selling tickets.
We have omitted some attributes like id box as we believe that we will not provide information that allows us to improve http://www.reddit.com/r/technology/comments/2jefsi/queue_management_system/ management.
Let our scheme star of the lines for tickets sales. We have a fact table and six dimension tables. We have added the dimension table http://oknotizie.virgilio.it/info/5054c2390b6d779e/queue_management.html of items from the previous model of the tickets sales, allowing us to analyze sales by subfamily.
Family or company, and we have not considered analyzing the lines of the tickets sold payment method dimension: not queue http://oknotizie.virgilio.it/info/5055c231dd87ccdb/queue_management_system.html management have excessive sense as a whole ticket sales is paid by the same form of payment and this information and provides us the old model of selling tickets.
Might ask why we have not incorporated the attribute No. Description in the table Item Dimension; the reason is that if we do the http://www.dzone.com/links/queue_management_2.html analysis for items and once manufacturers need to be in different dimensions, and, if they are the same, it can not do.
This model allows us to analyze the sales of the items by queue management the size of the center, by the dimension date, slots, http://linkagogo.com/go/SiteSee?i=99801636&i=99801625&t=queue+management+s..&t=queue+management employees, manufacturers of articles and article.
In our system of ticket sales information it is possible to modify the selling price of the item. Comparing information from tickets http://www.dipity.com/sherrybradys/queue-management/ sales with articles and differ per employee, we can know who the great discounts that apply. If we analyze in detail the time dimension, we see that a hierarchy of time appear in this dimension.
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