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1. Much ambiguity exists in defining Big Data.
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2. For a data set to be considered Big Data, it must display all the “3 Vs” – volume, velocity and variety.
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3. Scaling out is keeping the same number of systems, but migrating each system to a larger one.
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4. In many ways, the issues of associated with volume and velocity are the same.
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5. The analysis of data to produce actionable results is feedback loop processing.
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6. Relational databases rely on unstructured data.
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7. One tenet of Big Data is that all data that is capable of being captured should be.
Question 8
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8. The ability to graphically data in a way that makes it understandable is the concept of value.
Question 9
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9. Characteristics that are important in working with data in the relational database model also apply to Big Data.
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10. Hadoop is a database that has become the de facto standard for most Big Data storage and processing.
Question 11
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11. Under the HDFS system, using a write-one, ready-many model simplifies concurrency issues.
Question 12
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12. A block report is used to let the name node know that the data mode is still available.
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13. A reduce function takes a collection of key-value pairs with the same key value and summarizes them into a single result.
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14. Hive is a good choice for jobs that require a small subset of data to be returned very quickly.
Question 15
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15. Hadoop is a high-level tool that requires little effort to create, manage and use.