by Jasmine C
The article I read discussed how database systems are more efficient at information extracting than information extraction systems. Information extraction systems are used to remove the information relevant in a particular situation. This is efficient because only the information pertaining to a particular job can be extracted. However, information extraction systems are also inefficient. If from a list of criteria’s only one criteria needed to be changed, a whole new extraction process would need to be generated instead of just changing the criteria that was affected. By using database systems, the extraction process is not only simplified but also attains higher quality results. Database systems use queries which, according to Luis Tari, “enables generic extraction and minimizes reprocessing of data by performing incremental extraction to identify which part of the data is affected by the change of components or goals.” This way, instead of starting a new extraction everytime only the data that is affected is changed. The processing time from an information processing system to a database system was reduced by 89.64%.
This article relates to class because it talks about databases and how queries are used to improve the information people use for decisions. In any business, when information is used for decision making, the people using that information want to make sure that they are receiving the most accurate and updated information available to them. Using old and outdated information doesn’t benefit anyone and the way businesses world operates, people want to receive information in the fastest, most least expensive way.
In one of my accounting courses, I completed a project using the Access database. From experience I can say that creating queries was very easy and when I wanted to change one aspect of my query criteria I did not have to create a whole new query. The use of databases is very efficient and hopefully throughout the quarter I can learn more about them.
Tari, L. (2012, November 21). Incremental information extraction using relational databases. IEEE Transactions on Knowledge & Data Engineering, 24(1), 86-99. Retrieved January 6, 2012, from http://0-ieeexplore.ieee.org.opac.library.csupomona.edu/xpls/abs_all.jsp?arnumber=5611526&tag=1