TY - JOUR
T1 - A SURVEY ON BIG DATA
T2 - INFRASTRUCTURE, ANALYTICS, VISUALIZATION AND APPLICATIONS
AU - Saraswathi, S.
AU - Deepa, G.
AU - Vennila, G.
AU - Parthasarathy, S.
AU - Ramadoss, B.
N1 - Funding Information:
The US Government supports big data research and development initiatives with an investment of more than $200 million6. China is utilizing AI to improve its defense capabilities and is expected to become the world leader in this field by 2030. Six federal Government agencies are included in the big data projects: the Department of Defense (DoD), Department of Energy (DoE), Defense Advanced Research Projects Agency (DARPA), National Science Foundation (NSF), National Institutes of Health (NIH) and US Geological Survey (USGS). Cyber security, warfare platforms, logistics and transportation, Battlefield healthcare, target recognition, threat monitoring and situational awareness, Combat simulation and training are the major defense applications, according to market research 2018. Government-related big data applications include tax calculations, traffic analysis and monitoring, and census. Germany and Andhra Pradesh Government signed MoU with Shivom for blockchain technology in 20187. Shivom is the blockchain-enabled healthcare platform that focuses on building the largest unique genomic and healthcare research hub on the planet. Wireless network problems such as storage, communication, and computation are handled by big data. Data mining and machine learning algorithms are used for solutions in the area of wireless networks and to improve network performance, such as energy efficiency (Cao et al., 2018). Spina (2019), a geologist from CNG (National Council of Geologists), mentioned that big data and machine learning algorithms are utilized for designing the first digital map of seabed lithologies. Big data utilization by Government sectors has applications such as E-Government (Al-Sai and Abualigah, 2017), military applications (Yang et al., 2016), and earth science (Baumann et al., 2016).
Publisher Copyright:
© INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING.
PY - 2022
Y1 - 2022
N2 - Big data is a collection of heterogeneous and autonomous data sources which are available abundantly in multiple formats. Knowledge discovery and decision-making from the ever-growing abundant data are challenging tasks for data-oriented business organizations. Big data analytics investigates a large amount of data to find correlations among the available data and finally provides useful information to business organizations. Big data analytics facilitates application domains such as business, banking, healthcare, transportation, social media, agriculture, and government sectors. Existing surveys on big data are based on either of the following dimensions: characteristics, analytics, and visualization, or discuss the applications of big data analytics in the field of agriculture, transportation, etc., separately. However, this article provides a survey of big data, which integrates different dimensions of big data, such as infrastructure, analytics, visualization, and their applications. It also discusses the technologies and tools involved in the domains mentioned above.
AB - Big data is a collection of heterogeneous and autonomous data sources which are available abundantly in multiple formats. Knowledge discovery and decision-making from the ever-growing abundant data are challenging tasks for data-oriented business organizations. Big data analytics investigates a large amount of data to find correlations among the available data and finally provides useful information to business organizations. Big data analytics facilitates application domains such as business, banking, healthcare, transportation, social media, agriculture, and government sectors. Existing surveys on big data are based on either of the following dimensions: characteristics, analytics, and visualization, or discuss the applications of big data analytics in the field of agriculture, transportation, etc., separately. However, this article provides a survey of big data, which integrates different dimensions of big data, such as infrastructure, analytics, visualization, and their applications. It also discusses the technologies and tools involved in the domains mentioned above.
UR - https://www.scopus.com/pages/publications/85141806845
UR - https://www.scopus.com/pages/publications/85141806845#tab=citedBy
U2 - 10.23055/ijietap.2022.29.5.7643
DO - 10.23055/ijietap.2022.29.5.7643
M3 - Article
AN - SCOPUS:85141806845
SN - 1072-4761
VL - 29
SP - 618
EP - 648
JO - International Journal of Industrial Engineering : Theory Applications and Practice
JF - International Journal of Industrial Engineering : Theory Applications and Practice
IS - 5
ER -