Presently and in future years to come, technical and scientific insights derived from big data problems can help provide direction on the development of next-generation solutions for different organisations and operations based on data-driven decision making.
Big data presents challenges to mining and query answering processes from theoritical to technological level. From many researches, a significant amount of questions have to be settled.
1. What queries are tractable on big data?
2. How can we make query answering feasible in big data?
3. When are exact query answers are beyond reach in practice, what approximation theory can help us strike a balance between the quality of approximate query answers and the cost of query processing?
4. Big data = quantity + quality. How can we improve the quality of big data so that we can get sensible query answers from it?
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