{"id":11251,"date":"2018-05-29T23:31:37","date_gmt":"2018-05-29T23:31:37","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/wmintrobusiness\/?post_type=chapter&p=11251"},"modified":"2018-05-29T23:31:37","modified_gmt":"2018-05-29T23:31:37","slug":"reading-managing-data","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/wmintrobusiness\/chapter\/reading-managing-data\/","title":{"raw":"Reading: Managing Data","rendered":"Reading: Managing Data"},"content":{"raw":"
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Managing Data<\/h2>\r\n

Did you ever think about how much data you yourself generate? Just remember what you went through to start college. First, you had to fill out application forms asking you about test scores, high school grades, extracurricular activities, and finances, plus demographic data about you and your family. Once you\u2019d picked a college, you had to supply data on your housing preferences, the curriculum you wanted to follow, and the party who\u2019d be responsible for paying your tuition. When you registered for classes, you gave more data to the registrar\u2019s office. When you arrived on campus, you gave out still more data to have your ID picture taken, to get your computer and phone hooked up, to open a bookstore account, and to buy an on-campus food-charge card. Once you started classes, data generation continued on a daily basis: your food card and bookstore account, for example, tracked your various purchases, and your ID tracked your coming and going all over campus. And you generated grades.<\/p>\r\n<\/div>\r\n

And all these data apply to just one aspect of your life. You also generated data every time you used your credit card and your cell phone. Who uses all these data? How are they collected, stored, analyzed, and distributed in organizations that have various reasons for keeping track of you?<\/p>\r\n

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Data and Databases<\/h2>\r\n

To answer such questions, let\u2019s go back to our Caesars example. As we\u2019ve seen, Caesars collects a vast amount of data. Its hotel system generates data when customers make reservations, check in, buy food and beverages, purchase stuff at shops, attend entertainment events, and even relax at the spa. In the casino, customers apply for rewards programs, convert cash to chips (and occasionally chips back to cash), try their luck at the tables and slots, and get complimentary drinks. Then, there are the data generated by the activities of the company itself: employees, for instance, generate payroll and benefits data, and retail operations generate data every time they buy or sell something. Moreover, if we added up all these data, we\u2019d have only a fraction of the amount generated by the company\u2019s gaming operations.<\/p>\r\n

How does Caesars handle all these data? First of all, it captures and stores them in several databases<\/span><\/span>\u2014electronic collections of related data that can be accessed by various members of the organization. Think of databases as filing cabinets that can hold massive amounts of organized information, such as revenues and costs from hotel activities, casino activities, and events reservations at each of Caesars facilities.<\/p>\r\n

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Warehousing and Mining Data<\/h2>\r\n

What if Caesars wants to target customers who generate a lot of revenue, by using a program designed to entice return visits? How would it identify and contact these people? Theoretically, it could search through the relevant databases\u2014those that hold customer-contact information (such as name and address) and information about customer activity in the company\u2019s hotels, casinos, and entertainment venues. It would be a start, perhaps, but it wouldn\u2019t be very efficient. First of all, it would be time-consuming. Plus, what if the same data weren\u2019t stored in a similar fashion in each database? In that case, it would be quite hard to combine the data in a meaningful way. To address this problem, Caesars managers will rely on a system like the one illustrated in Figure 1, \"The Data Mining Process,\" which calls for moving all the relevant data into a data warehouse<\/span><\/span>\u2014a centralized database in which data from several databases are consolidated and organized so that they can be easily analyzed.<\/p>\r\n[caption id=\"attachment_5594\" align=\"aligncenter\" width=\"500\"]\"Internal<\/a> Figure 1. The Data Mining Process[\/caption]\r\n

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Data Mining<\/h2>\r\n

With the data in one central location, management can find out everything it needs to about a particular group of customers. It can also use the data to address some pretty interesting questions. Why do people come to our casinos? How can we keep customers coming back? How can we increase the number of visits per customer? How can we increase the amount they spend on each visit? What incentives (such as free dinners, hotel rooms, or show tickets) do our customers like most? To come up with answers to these questions, they\u2019ll perform a technique called data mining<\/span><\/span>\u2014the process of searching and analyzing large amounts of data to reveal patterns and trends that can be used to predict future behavior.<\/p>\r\n<\/div>\r\n

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Data Mining and Customer Behavior<\/h2>\r\n