Q. How does the Large Hadron Collider (LHC) handle the massive amount of data it generates?

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Q. Why is the cloud paradigm considered a desirable feature in Big Data solutions?

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Q. What is a limitation of using public cloud systems for extensive computations on large volumes of data?

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Q. Which project allows experiments on interlinked cluster systems for Big Data solutions?

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Q. What does the term "self-healing" refer to in the context of Big Data systems?

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Q. How can a system achieve self-healing in the event of a server or node failure?

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Q. What happens when a node/storage fails in a cluster with self-healing capabilities?

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Q. What is the BASE property in the context of NoSQL databases?

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Q. What is the primary goal of the CAP theorem in distributed storage systems?

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Q. Why is it challenging to implement a fault-tolerant BASE architecture for Big Data management?

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Q. How does the CAP theorem impact the design of Big Data solutions?

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Q. What role does the concept of "eventual consistency" play in the CAP theorem?

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Q. What characterizes Big Data solutions in terms of data management aspects?

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Q. What is the trend in data structures for Big Data?

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Q. According to the CAP Theorem, what are the three main features that a distributed storage system can provide?

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Q. What does the property of "consistency" mean in the context of the CAP Theorem?

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Q. How does the CAP Theorem impact Big Data solutions?

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Q. What properties are described by the ACID paradigm in relational databases?

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Q. What is one of the primary challenges associated with the database size in Big Data problems?

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Q. Which factor significantly influences the performance of data management in Big Data solutions?

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