Vocabulary Practice: Data Mining

Read the text again and answer the questions with some of the words in bold.

Nowadays most, if not all, retail companies store and process customer data. However, analyzing the collected raw data can be quite a challenging task. In times when information is a hot commodity it is essential for businesses to make good use of it. What’s the point of extracting terabytes of statistics about the behavior of your customers and their preferences if it is next to impossible to sift through all the data stored in your corporate database?

This is where data mining, also known as Knowledge Discovery in Data (KDD), comes into play. Data mining is the process of analyzing data from various databases in order to recognize previously unidentified patterns which exist between them. By using sophisticated algorithms, analytical software, or data scraping – the process of extracting data from websites – companies collect useful information to identify the existence of said patterns. Once found, these patterns are simplified and are then used to forecast future outcomes and tendencies. This can be helpful for businesses in terms of planning successful marketing and management strategies or to simply enhance the browsing experience of individual users. By analyzing how a customer browses your website, an algorithm ensures that ads tailored to his interests are displayed during his next visit.