Description: New analytics technology is predicting behavior—and building businesses. In the early 2000s a wave of startups made it possible to gather huge volumes of data and analyze it in record speed—à la SecureAlert. A retailer such as Macy’s (M) that once pored over last season’s sales information could shift to looking instantly at how an e-mail coupon for women’s shoes played out in different regions.
Source: BusinessWeek .com.
Date: Sept 12, 2011
Past technology worked with data that fell neatly into rows and columns—purchase dates, prices, the location of a store. Amazon.com (AMZN), for instance, would use traditional systems to track how many people bought a certain type of camera and for what price. Hadoop can handle data that don’t fit into spreadsheets. That ability, combined with Hadoop’s speedy divide-and-conquer approach to data, lets users get answers to questions they couldn’t even ask before. Retailers can dig into not just what people bought but why they bought it. Amazon can (and does) analyze its website logs to see what other items people look at before they buy that camera, how long they look at them, whether certain colors on a Web page generate more sales—and synthesize all that into real-time intelligence. Are they telling their friends about that camera? Is some new model poised to be the next big hit? “These insights don’t come super easily, but the information is there, and we do have the machine power now to process it and search for it,” says James Markarian, chief technology officer at data specialist Informatica.
Questions for discussion:
- How is new analytics technology predicting behavior different from traditional databases such as oracle?
- If an organization adopts this technology , what roles and goals of technology can be achieved by the organization