One of the major applications of fu

One of the major applications of future generation parallel and distributed systems is in big-data analytics.
Data repositories for such applications currently exceed exabytes and are rapidly increasing in size.
Beyond their sheer magnitude, these datasets and associated applications’ considerations pose significant
challenges for method and software development. Datasets are often distributed and their size and privacy
considerations warrant distributed techniques. Data often resides on platforms with widely varying
computational and network capabilities. Considerations of fault-tolerance, security, and access control are
critical in many applications (Dean and Ghemawat, 2004; Apache hadoop). Analysis tasks often have hard
deadlines, and data quality is a major concern in yet other applications. For most emerging applications,
data-driven models and methods, capable of operating at scale, are as-yet unknown. Even when known
methods can be scaled, validation of results is a major issue. Characteristics of hardware platforms and the
software stack fundamentally impact data analytics. In this article, we provide an overview of the stateof-
the-art and focus on emerging trends to highlight the hardware, software, and application landscape
of big-data analytics.

ผลลัพธ์ (อังกฤษ) 2:

One of the Major Applications of Future Generation parallel and Distributed Systems is in Big-Data Analytics.
Data repositories for such Applications currently Exceed exabytes and are rapidly increasing in Size.
Beyond their sheer magnitude, these datasets and associated Applications' considerations Pose significant
challenges for. method and software development. Distributed and their datasets are often Size and privacy
considerations warrant Distributed Techniques. Data often resides on platforms with widely varying
and Network Computational capabilities. Fault-tolerance of considerations, Security, and Access Control are
in many Critical Applications (Dean and Ghemawat, two thousand and four; Apache Hadoop). Analysis Tasks often have hard
deadlines, and Data quality is a Major Concern in yet Other Applications. Most emerging for Applications,
Data-driven models and methods, Capable of operating at scale, are as-yet Unknown. Known even when
Can be Scaled methods, validation of results is a Major Issue. Hardware platforms and the characteristics of
fundamentally Impact Data Analytics Software stack. In this Article, we provide an overview of the Stateof-
the-Art and Focus on emerging Trends Highlight to the Hardware, Software, and Application Landscape
of Big-Data Analytics.