Data Quality{6}


by David H
This article talks about how data quality is mundane and the issue how data quality affects to company. As we know working with data is very important.  Lou Gerstner mention that “Inside IBM, we talk about 10 times more connected people, 100 times more network speed, 1,000 times more devices and a million times more data.” This shows that as technology growth, we involve a lot with data. The poor data cost the company a lot. The author mentions that “it cost 10% to 20% of revenue to company”. In addition, author also mentions that there is some unfolding disaster. The most problems it comes from human mistakes such as input wrong data. For example, “incorrect prices on Amazon.com, where a 1GB memory module normally listed at $999.99 was on sale at Amazon.com for $19.99; hotel rooms at W Hotels sold for $59 instead of $259; and United Airline tickets selling for $5.” This shows that, because of poor quality data it makes image of company will be bad and customer will be upset. In addition, the company has difficult for making decision and implement new technologies. The other issue of poor data quality that company has is to link data of customer with different divisions, so they can do analysis and offer promotion or deals to customers. However, the data is simply unfit for doing so. The various divisions employ different data formats, they model customers differently and the data is erred, making linkage impossible.

I think this article relates to class because it talks about how poor data affect drastically to industry. In addition, we have been discussing some of the issue that makes data not quality. After reading this article, I think we need to follow the guide line which we have learned in class to improve quality of data.

 

Reference

Thomas C.Redman. (2008, July 18). Data: An Unfolding Quality Disaster. Information Management.