Big Data technologies: A survey

Oussous, Ahmed; Benjelloun, Fatima Zahra; Lahcen, Ayoub Ait; Belfkih, Samir

doi:10.1016/j.jksuci.2017.06.001

Cited by 628 publications

(491 citation statements)

References 36 publications

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“…With the help of Big Data analytics one can identify at-risk transformers and to detect abnormal behaviors of the connected devices. Energyforecasting analytics help to better manage power demand load, to plan resources, and hence to maximize prots [61]. E-health: Big Data is generated from different heterogeneous sources likes' laboratory and clinical data, patients symptoms uploaded from distant sensors, hospitals operations, and pharmaceutical data.…”

Section: Big Data Applicationsmentioning

confidence: 99%

“…Public health plans as per population symptoms, disease evolution. To optimize hospital functioning and to decline health cost [61].…”

Section: Big Data Applicationsmentioning

confidence: 99%

“…To minimize delivery routes. Smart city is one of the good and challenging research based on the application of IoT data [61]. Public utilities: In Water supply department to identify leakages, illegitimate water connections and remotely manage valves to make sure fair supply of water to different regions of the city [61].…”

Section: Internet Of Things (Iot)mentioning

confidence: 99%

See 2 more Smart Citations

Parallel processing on Big Data in the context of Machine Learning and Hadoop Ecosystem: A Survey

Brahmane¹,

R²

2018

IJET

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Emergent Big Data applications have become gradually more essential. In reality, a lot of institutes, businesses and in general entire society from diverse segments depend more and more on information take out from enormous quantity of raw information, statistics and numbers. On the other hand, in Big Data perspective, customary information methods and policies are not as much of capable. They prove a time-consuming receptiveness and are short of quantifiability, measurability, presentation and accurateness. To solve the composite Big Data constraints and difficulties, a large amount effort has been carried out. As an effect, different categories of packages, distributions and technologies have been developed. In this paper an evaluation is done, this studies recent technologies developed for Big Data. It aims to assist to choose and adopt the exact combination of diverse Big Data technologies according to their technological, scientific needs and particular applications requirements. It provides not only a worldwide sight of most important Big Data technologies but also relationship according to special organizational, classifications levels

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Section: Big Data Applicationsmentioning

confidence: 99%

“…Public health plans as per population symptoms, disease evolution. To optimize hospital functioning and to decline health cost [61].…”

Section: Big Data Applicationsmentioning

confidence: 99%

See 1 more Smart Citation

Parallel processing on Big Data in the context of Machine Learning and Hadoop Ecosystem: A Survey

Brahmane¹,

R²

2018

IJET

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“…For example, Wal-Mart (an international discount retail chain) produces more than 2.5 petabytes of data per hour via the transactions of its customers. YouTube is a good example that shows the velocity of big data [5].…”

Section: Velocitymentioning

confidence: 99%

“…Big data is composed of more than one form of various sources (e.g., videos, documents, comments, and journals). Big data sets are composed of public or private, local or distant, shared or confidential, completed or missing, and structured or unstructured data [5].…”

Section: Varietymentioning

confidence: 99%

Big Social Network Data and Sustainable Economic Development

Can

Alataş

2017

Sustainability

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New information technologies have led to the rapid and effective growth of social networks. The amount of data produced by social networks has increased the value of the big data concept, which is one of the popular current phenomena. The immediate or unpredictable effects of a wide array of economic activities on large masses and the reactions to them can be measured by using social media platforms and big data methods. Thus, it would be extremely beneficial to analyze the harmful environmental and social impacts that are caused by unsustainable business applications. As social networks and big data are popular realms currently, their efficient use would be an important factor in sustainable economic development. Accurate analysis of people's consumption habits and economic tendencies would provide significant advantages to companies. Moreover, unknown consumption factors that affect the economic preferences of individuals can be discovered and economic efficiency can be increased. This study shows that the numerous solution opportunities that are provided by social networks and big data have become significant tools in dynamic policy creation by companies and states, in solving problems related to women's rights, the environment, and health.

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Hands on MAHOUT—Machine Learning Tool

Dulhare

Gouse

2020

Machine Learning and Big Data

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Big Data technologies: A survey

Cited by 628 publications

References 36 publications

Parallel processing on Big Data in the context of Machine Learning and Hadoop Ecosystem: A Survey

Parallel processing on Big Data in the context of Machine Learning and Hadoop Ecosystem: A Survey

Big Social Network Data and Sustainable Economic Development

Hands on MAHOUT—Machine Learning Tool

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