Data is not a monolithic asset. Data about customers, for example, can contain aspects about their purchasing patters, about their demographics (gender, age, etc), financial information (how much money do they make), education information (school degrees), personal information (preferences, tastes), and many different aspects that describe a person. In addition, often the data may be further subdivided based on the type of business someone is interested in. A large finacial corporation may store data about its credit card business separately from the data about its banking business. Even in the same business, data can be further divided, because, for example, credit card use may differ depending on the type of card the customer uses.
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Divide and be conquered
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Data is not a monolithic asset. Data about customers, for example, can contain aspects about their purchasing patters, about their demographics (gender, age, etc), financial information (how much money do they make), education information (school degrees), personal information (preferences, tastes), and many different aspects that describe a person. In addition, often the data may be further subdivided based on the type of business someone is interested in. A large finacial corporation may store data about its credit card business separately from the data about its banking business. Even in the same business, data can be further divided, because, for example, credit card use may differ depending on the type of card the customer uses.