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Data Warehousing

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Active Server Pages (ASP), On Line Analytical Processing (OLAP), data warehouses, and data marts are all part of a three tier architecture. The three tier architecture is used to analyze and extract data from databases. This process makes uses databases more efficient and allows for the data to be analyzed in a strategic manner.

OLAP is an acronym for On Line Analytical Processing. OLAP is used to provide answers to queries in a multidimensional database. OLAP provides rapid execution of queries and does this by treating each data attribute as a dimension.

OLAP uses MDX (MultiDimensional Expressions) to access and define multidimensional data (Hernandez, 2006). MDX is a similar scripting language to SQL but it is used for retrieving data from multidimensional objects.

A Data warehouse is a repository of integrated information, available for queries and analysis (Wikipedia, 2006). The data stored in the data warehouse may have come from many different sources, but by having the data stored in a data warehouse, the information can be extracted more readily. This makes it much easier and efficient to run queries, especially when the data has come from multiple sources. Data warehouses are set up to provide quick responses to queries and work well with OLAP.

A data mart is a specialized version of a data warehouse. The data mart will hold specific groupings of data, such as one particular department or subject. This grouping allows for more rapid queries and easier access to relevant data. The data mart may either be part of a data warehouse or stand by itself.

In a three tier architecture the top tier includes a user system interface where user services (such as session, text input, dialog, and display management) reside. The middle tier provides process management services (such as process development, process enactment, process monitoring, and process resourcing) that are shared by multiple applications (Sadoski, 2006). The third tier is database management. The three tier architecture added a middle tier to make processing the data can be analyzed using business rules and logic.

The three tier architecture also increased the number of users that can access the system. In the older two tier architecture only a hundred users could use the system, the three tier architecture allow for hundreds of users. This was a major advantage for major corporations with hundreds to thousands of employees.

Also, in the three tier architecture each tier is developed separately. This allows for each different tier to be written in different languages. Having the processing element in a separate tier also makes it easier to develop and upgrade. If only one part of the architecture needs further development, then you can work on just that part rather than having to work on the whole system.

ASP stands for Active Server Pages. ASP uses different objects that correspond to a group of frequently used functions. This allows for information to be pulled more easily and efficiently. It also allows for content on the page to be changed without having to reload the whole page. ASP pages often utilize ActiveX Data Objects to link to SQL Server databases and other data sources (Chapple, 2006).

In a three tier architecture, ASP would be used for the user interface, the top tier. ASP would be responsible for the presentation and the user interaction. The user would never interact with the third tier directly. The user would go through the ASP that would then interact with OLAP which would pull the information from the data ware house or data mart.

Allowing information to be updated on the page without having to reload the whole page, makes a more efficient system. It also allows users to be able to use a web browser to access the database. This makes the system more efficient, not having to rely on particular type of access point.

The middle tier would be OLAP. OLAP would be used as the process manager. OLAP would execute the queries. OLAP pulls information from the data warehouse to form strategic information.

OLAP processes information through cubing. The different data is formed into a cube and where the data intersects is a query. Although cube implies that there can only be three intersections, OLAP allows for up to 64 intersections. OLAP is able to analyze the data in a data warehouse or data mart and provide relevant information. This information may be what items are generally sold together or which employees call in sick around a holiday, etc. The user would then be able



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