Data Virtualization: A Supermarket for Data
What is data virtualization? Here’s an analogy using a concept that we can all relate to: a supermarket.
Picture the scene: Shopping list in one hand, shopping basket in the other, you’re ready to tackle your weekly shopping in your local supermarket. Your items range from fruit and vegetables to washing detergent, perhaps with some free-range eggs thrown in for good measure. Quite the eclectic mix, but you know that you’ll be able to find all you need under one roof.
The fact that this is possible is in itself quite remarkable. Think about it: In the average fruit section, you might find oranges imported from Seville, bananas from Latin America, and apples from France. The origin of each fruit is different, yet they have all been imported to arrive in front of you, the customer.
And now we’re only talking about fruits. If you think about the thousands of other products in the , all manufactured and/or produced in hundreds of different countries, the ease of buying these products in a supermarket becomes apparent. The idea of travelling to every country to purchase each individual product would be absurd—it would be expensive, time-consuming, and ridiculously slow. It would not even cross your mind as an option.
But how does this all apply to data?
In this analogy, if fruit were to represent data, then a supermarket would be a highly efficient system for delivering data to consumers. Just as every package of fruit has its origin, every set of data has its source. Each of the different forms of fruit offered in a supermarket, such as fresh, frozen, or dried varieties, are like the different ways that data is formatted. The different types of fruit, such as citrus fruits or berries, are like different types of data, and volume is a concept that is shared by retailer and data steward alike.
