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The aforementioned enormous values of big data are embodied in practical big data applications which bring a large number of big data-related challenging research issues.
We reviewed several examples of big data applications, which can be considered as guides to lead smart city applications development efforts.
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A new generation of big data applications have blossomed in this ecosystem, which in turn has put pressure on enterprise vendors to modify existing software suites.
The firm has always made futuristic bets in companies like Counsyl, which is handling big data applications for gene testing and sequencing.
However, these methods are not necessarily applicable for big data applications.
For the big data applications RDBMS systems are forced to use distributed storage, which includes table partitioning, data redundancy and replication; because of disk size limits and to avoid hard disk failures [10].
These are the first guidelines on data protection provided by an international body which specifically address the issues surrounding big data applications.
There is a variety of available data processing platforms for big data analytics, which provide the stream processing required by real-time big data applications in relation to various urban domains.
In this paper, we propose an improved K-means clustering algorithm that is augmented by a Tabu Search strategy, and which is better adapted to meet the needs of big data applications.
In May, it launched a data beta project, LucidWorks Big Data, which certifies and integrates Apache open source components to develop and manage big data applications.
And there are cloud-based services emerging for big data applications.
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