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Published by Seventh Sense Research Group. Abstract - Cloud computing is a most powerful technology which performs massive-scale and complex computing. It eliminates the requirement to maintain costly computing hardware, dedicated space requirement and related software. Massive growth in the scale of data or big data generated through cloud computing has been identified. Concept of big data is a challenging and time-demanding task that requires a large computational space to ensure successful data processing and analysis.
Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By , 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in
Heterogeneity, scale, timeliness, complexity, and privacy problems with Big Data integration is a major creator of value. We may need to figure out good questions based on the data. Alberto Espinosa and process efficiently by traditional database methods and tools. We concluded that best practices in managing big data-driven healthcare innovations in. Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv.
It will be useful for those who have experience in predictive This study proposes a service-oriented layered reference architecture for intelligent video big data analytics in the cloud. ISBN , This paper aims to research how big data analytics can be integrated into the decision making process. Die Aufgabe von Data Mining ist es, versteckte Informationen aus dieser Datenschwemme herauszufiltern. Data Mining. The mined tweets were filtered using certain criteria that would only remain with relevant tweets. Data mining techniques and algorithms are being extensively used in Artificial Intelligence and Machine learning.
Iranian Journal of Information processing and Management , , vol. Big Data is a collection of massive and complex data sets and data volume that has characteristics such as valence, validity, value, variability, variety, velocity, veracity, visualization, volatility, and volume. These features of big data make it difficult to process and manage with a typical database, but extracting value from it can improve many organizational and non-organizational processes, although it may cost and require the use of modern ICT infrastructure and techniques. The aim of this research was to identify, determine, prioritize and analyze the opportunities of big data; to analyze structural-interpretation of it; and to suggest solutions for managing big data in libraries and information centers in Tehran. The methodology of this applied research was descriptive survey and the total number of chief managers of central libraries of public universities in Tehran was considered as its research population 35 chief managers. The data were collected through library studies and questionnaire. In fact, previous studies and the documentary research method were used to review the fundamental opportunities of big data in order to design the questionnaire based on the research model.
Big data analytics tools have many functions that are common or similar to one another. This is a problem for many organisations that are either interested or have deployed some of the tools. The problem arises because there is no mechanism on how to determine appropriateness of the tools within context in an environment. Some of the implications of the problem are that it is difficult to assess appropriateness of the tools in an environment, which sometimes result to duplication; and the value of the tools. The qualitative method, case study approach and semi-structured interview technique were applied in the study. From the analysis, the role of criteria, business and IT alignment, governance, and skill-sets were revealed as critical factors. Based on the factors, a model was developed, which can be used as a building block through which evaluation of big data analytics tools in an organisation is carried out.
Big data is defined as large amount of data which requires new technologies and architectures so that it becomes possible to extract value from it by capturing.
We focus on a specific and critical IT capability, the use of data analytics, which is often leveraged by firms to improve decision making and achieve agility gains. In order to meet these needs, especially in Moroccan context, our research group is working on the development of the following educational and research lines that we describe in this paper: i Training program for both students and professionals, ii Analysis of Moroccan web content, iii Security and privacy issues, and iv Frameworks for Big Data applications development. Th e biggest reason for this growth of data could be found in technological advancement, since data can be easily and cheaply stored and shared today.
Citation: Sitalakshmi Venkatraman, Ramanathan Venkatraman. Big data security challenges and strategies[J]. AIMS Mathematics, , 4 3 : Article views PDF downloads Cited by 4. Figures 5.
Data Management Resource: Forrester Wave - Master Data Management, If you're in the market for big data solutions for your company, see our list of top big data companies. In Industrial Conference on Data Mining, pages In the IDG survey, less than half of those surveyed 39 percent said that they were using additional security measure for their big data repositories or analyses.
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Big Data: Issues, Challenges, Tools and Good. Practices. Avita Katal. Mohammad Wazid Big data technology, its tools (Hadoop) are also discussed in detail along interactions, to recorded meetings, to handling of PDF documents, fax.Trinette L. 21.05.2021 at 07:10
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