by Leonardo S
The article I chose for this week is titled “Managing Data Source quality for data warehouse in manufacturing services”. The main topic of the article is focused around data quality. According to the article, one of the primary success factors of a data warehouse is the quality of the data. There are a few downsides from getting low quality data. Often times someone will have to go back into the database and fix the mistakes. This can take a lot of time and effort which could better be spent on other projects. Another flaw that comes from having bad data is that your data analysis will be all wrong. Database analysts will end up wasting even more time reviewing the data again after it has been fixed. The article mentions a few ways to reduce the amount of low quality data going into your database. Two methods of doing this are Total Data Quality Management and Quality Management System requirements. From what I understand, these are guidelines for collecting and inputting data that helps limit the amount of low quality data.
I picked this article because of our topic for last week about data quality. In class we learned about the seven characteristics of quality data. The article that I chose talked about what would happen if our data has any of those qualities. Wasting resources in order to go back and fix data is definitely something that a database administrator should not have to do. By following the guidelines from the article and those we learned in class, any of us should be able to help make sure that quality data is gotten on the first try.
I liked this article because it helped reenforce the idea of making an effort to get quality data for your database. If I ever decide to become a database administrator I’ll be sure to use this information in order to make sure the database is filled with high quality data. Similarly, if I find myself doing data analysis I can look out for the common characteristics of bad data which will help make the analysis more accurate.
Idris, N. (2011). Managing Data Source quality for data warehouse in manufacturing services. Electrical Engineering and Informatics (ICEEI), 2011 International Conference on. pgs.1-6.