BIG DATA IN VARIOUS SECTORS AND BIG DATA MANAGEMENT
Shital B. Palaskar
INTRODUCTION
Big data refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes.
Analysis of big data allows analysts, researchers and business users to make better and faster decisions using data that was previously inaccessible or unusable.
Traditional databases are ineffective for storing, processing, and evaluating purposes; that is why big data terminology has been introduced in the IT field. The traditional approaches lack efficient cluster management and processing. Data management systems provide computing, analysis, storage, and control to resolve the issues of sustainability.
OBJECTIVE
To understand big data, big data management and its uses in various life sectors
BIG DATA MANAGMENT
Kostakis, P., & Kargas, A. (2021) stated Data Life-Cycle Processes, Technology, Information Security, and Business and Human Power as the four components of big data management. Data life-cycle processes are actions and procedures that are executed in both technological and business environments. Techniques included in big data are Data mining, Genetic algorithms, Machine learning and Neural networks. Business Intelligence, Cloud Computing, Oracle Big Data Appliance, MongoDB and Amazon Dynamo, Java, and Python programming languages etc are the technologies that can be used in big data management. Human power is undividable need, new skill development and training human power is a future business investment. Authentication, authorization, and encryption are the information security techniques.
MULTIMEDIA BIG DATA MANAGEMENT
Babar, et al (2021) referred the multimedia data to the various media types including videos and animations along with text and audio. The multimedia big data management in the IoT setting is serving to solve the challenges associated with people and society including lighting automation, controlling traffic, and automation of building. Multimedia systems provide computing, storage, and analysis, to solve the challenges. Multimedia big data sets utilises MMBD framework using parallel and distributed paradigms and premeditated algorithms Parallel and distributed (e.g. traditional Hadoop) processing platforms are used for processing big data followed by intelligent decision-making. Premediated algorithms (e.g., capacity algorithms, DP algorithms) are applied for data processing in the cluster.
BIG DATA USES IN EDUCATION
Mentsiev, A. U., Magomaev, T. R., & Dauletukaeva, K. D. (2020) stated video and voice-based learning in the study hall will change the methodology and learning speed and understanding. Making access to big data would help participate in colleges with bosses and decline the deficiency of experts in numerous fields, give better business chances to understudies and help them in picking an excellent vocation way. Creating customized learning, changing our insight into slender areas and based on gathered data and investigation, instructive programming we can fulfil both students’ and teachers’ needs.
BIG DATA IN 5G TRANSFORMATION
Bansal, R., Obaid, A. J., et al (2021) identified three machine learning (ML) algorithms to carry out digital transformation. 5G transformation requires massive amount of data. In addition to decision tree DT the other algorithms used for the classification are NB, LR. These algorithms run on the large data processing engine they work. These algorithms serve as an ensemble tool for examining old records of stroke outpatients (OPs) and body built IOT based sensors. These readings are available as Big Data. The proposed OP-Centric Optimization Framework may play an important role in constructing a scalable, trustworthy and versatile network.
AVIATION MANAGEMENT AND BIG DATA
Aarthy, C. C., Narayanan, et al (2021) proposed that safety and performance enhancement issues of aviation industry are expected to be resolve by big data. Big data of aviation technology, aircraft design and performance improvement, macro aviation management, route planning and air traffic management, flight and airport management, Frequency spectrum analysis and big data in aviation business management will help to increase the effectiveness of the system where big is the foundation to all. To provide basic protection for global aviation safety, all national aviation organizations must work together to create a global aviation big data cooperation system.
GEOSPATIAL BIG DATA
Li, H., Huang, W., et al (2021) believed in use of Geospatial big data in visualization of geospatial locations, comprehensive services of industrial thematic geographic information and research on geographic data science and knowledge services. Geographical Information is an important basic and strategic information resource for the country, which involves economic and social development, ecological civilization construction, national security and people’s life facilitation. To design a geospatial big data platform is an inevitable to all the countries for social public application services and administrative management decision-making.
BIG DATA ANALYSIS IN HEALTHCARE SYSTEM
Kornelia, B., & Ślęzak Andrzej (2022) believed, introduction of Big Data Analytics (BDA) in healthcare will allow to use new technologies both in treatment of patients and health management. Medical facilities use both structured and unstructured data in their practice. The adoption of a Big Data approach would allow the implementation of personalized and precise medicine based on personalized information, delivered in real time and tailored to individual patients. Big Data Analytics can provide insight into clinical data and thus facilitate informed decision-making about the diagnosis and treatment of patients, prevention of diseases or others.
SUPPLY CHAIN MANAGEMENT WITH BIG DATA ANALYTICS
Mageto, J. (2021) stated, big data analytics (BDA), can help create new insights that can detect parts and members of a supply chain whose activities are unsustainable and take corrective action. The application of BDA is likely to benefit supply chains to achieve sustainability in the social dimension by reducing the supply chain risks associated with the procurement of goods and services, especially from global markets. Relationship between BDA and SSCM is through corporate goals, sustainability culture, risk management and transparency. BDA enabled SSCM will have visibility, efficient, competitive, collaborative and high TBL (triple bottom line approach).
BIG DATA IN SEARCH ENGINE OPTIMISATION (SEO)
Drivas, I. C., Sakas, et al (2020) believed in the Big Data era, search engine optimization deals with the encapsulation of datasets that are related to website performance. In the context of the Big Data era, search engine optimization (SEO) plays a crucial role in the potential dissemination of personalized content that reflects quality. big data analytics offers new opportunities in strategic SEO planning and deployment. big data analytics can be retrieved and interpreted, while focusing on critical factors and omitting less relevant ones in organic traffic optimization.
UX STUDY USING BIG DATA
Kim, J. H., Nan, D., et al (2021) research on the issue of user satisfaction and user experience (UX) generated using uber services through big data. They employed a big data approach for exploring user satisfaction among Uber users. The proposed big data approach aims to address the limitations of the prior studies on Uber and similar services. The proposed big data approach can be used in future user experience UX studies. They obtained both positive and negative feedback of users using this system.
CONCLUSION
The big data and big data analytics help analyse data set quickly and cost effectively. There is clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability. With a broad set of managed services to collect, process, and analyse big data, BDA makes it easier to build, deploy, and scale big data applications. With big data, and its analysis more educated decisions can be made in every sector of human life.
REFERENCES:
Aarthy, C. C., Narayanan, M. K. B., Kumar, G. R., Jayasundaram, J., Saikrishna, S., & Kumar, C. R. (2021). Big data analytics and an intelligent aviation information management system. Turkish Journal of Computer and Mathematics Education, 12(11), 4328-4340. Retrieved from
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Bansal, R., Obaid, A. J., Gupta, A., Singh, R., & Pramanik, S. (2021). Impact of big data on digital transformation in 5G era. Journal of Physics: Conference Series, 1963(1) doi:http://dx.doi.org/10.1088/1742-6596/1963/1/012170
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Li, H., Huang, W., Zha, Z., & Yang, J. (2021). Application And Platform Design Of Geospatial Big Data. Gottingen: Copernicus GmbH. doi:http://dx.doi.org/10.5194/isprs-archives-XLIII-B4-2021-293-2021
Mageto, J. (2021). Big data analytics in sustainable supply chain management: A focus on manufacturing supply chains. Sustainability, 13(13), 7101. doi:http://dx.doi.org/10.3390/su13137101
Mentsiev, A. U., Magomaev, T. R., & Dauletukaeva, K. D. (2020). The impact of big data on the development of the education. Journal of Physics: Conference Series, 1691(1) doi:http://dx.doi.org/10.1088/1742-6596/1691/1/012181