Q. Why is it challenging to tune modern database systems for Big Data?

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Q. What is the main assumption behind the design of traditional database systems?

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Q. Why is it difficult to tune a database system for Big Data exploration?

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Q. What is one critical side effect of using Big Data clusters for scalability?

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Q. Why is energy consumption considered a critical side effect of dealing with Big Data?

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Q. Why does the query-processing paradigm need to change with more data?

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Q. In the context of business analytics, why is changing the processing paradigm considered important?

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Q. What is the primary purpose of data exploration in the context of query processing for Big Data?

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Q. What is a common characteristic of scenarios where data exploration is needed?

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Q. How should next-generation database systems interpret queries?

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Q. What is the key benefit of systems that support data exploration?

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Q. What major costs can exploration-based systems help avoid?

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Q. What is the primary goal of an efficient data exploration system?

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Q. What does the system need to remember in order to guide the user effectively in data exploration?

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Q. What is the purpose of adaptive indexing?

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Q. What is the primary purpose of adaptive indexing?

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Q. What is the main problem with the set of potential indices in database systems?

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Q. How has the complexity of index selection in database systems changed over time?

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Q. What is required for offline indexing to make tuning choices and perform tuning actions?

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Q. In dynamic environments with Big Data, what are described as scarce resources?

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