Fig 1- - uploaded by Shoban Babu Sriramoju
Content may be subject to copyright.
Big data is measured in Peta bytes or higher (Intel, 2013)

Big data is measured in Peta bytes or higher (Intel, 2013)

Source publication
Article
Full-text available
Data mining has been around for many years. The term data mining becomes Big Data mining when mining involves huge amount of data with characteristics such as volume, velocity and variety. Big data mining assumes importance as the enterprises are producing data with exponential growth. Big data mining refers to mining voluminous data and extracting...

Similar publications

Conference Paper
Full-text available
The need to ensure privacy and data protection in educational contexts is driving a shift towards new ways of securing and managing learning records. Although there are platforms available to store educational activity traces outside of a central repository, no solution currently guarantees that these traces are authentic when they are retrieved fo...
Conference Paper
Full-text available
This is quite usual nowadays that some university courses are taught for hundreds of students simultaneously. To accomplish the practical part of such courses, students are requested to implement practical assignments or projects and upload them into the Learning Management System for further evaluation and getting the final grade. Grading such stu...

Citations

... These data from various channels will inevitably raise problems pertaining to moral, social, and data security while providing rich data sources. As the Internet technology gradually develops, many privacy solutions and privacy protection methods have been developed and designed to solve the above problems, but these solutions and methods cannot provide adequate protection [58]. Based on relevant statistical studies, security and moral problems in data mining are mainly classified from users and information security at present. ...
Article
Full-text available
With the rapid development of various types of industrial big data technologies, in the context of industrial big data and systems science, intelligent optimization algorithms and other technologies have been widely used in the field of intelligent manufacturing. In recent years, it has not only become an important engine for the transformation and upgrading of smart manufacturing industry, but also brought new opportunities and challenges to the development task integrated management of intelligent manufacturing equipment. This paper reviews the research on task integrated management of intelligent manufacturing equipment development from the following four aspects: task analysis and management of intelligent manufacturing equipment in big data environment, task decomposition and resource allocation, task network analysis and evaluation, and task integration analysis and verification evaluation progress. Prospects for further research are pointed out, including the customized research into high-end equipment developed for the individual needs of users, data-driven optimal allocation of resources research, multi-layer interaction of complex network modeling, intelligent systems integration, and verification evaluation.
... Uncertainty in relation to technologies is influencing decision-making processes of all stakeholders, but for businesses, data extraction, analysis, and representation are becoming especially crucial. However, there are some challenges accompanying Big Data mining, such as risks to privacy, security, and complexity [15]. As traditional mining techniques are not able to provide cost-effective solution besides being unable to leverage parallel processing power of resources, it is inevitable to go for Big Data mining with newly built data mining technologies. ...
... Privacy and Security risks Sriramoju [15] Big Data mining such as risks to privacy, security and complexity. ...
Article
Full-text available
The importance of energy security for the successful functioning of private companies, national economies, and the overall society cannot be underestimated. Energy is a critical infrastructure for any modern society, and its reliable functioning is essential for all economic sectors and for the well-being of everybody. Uncertainty in terms of the availability of information, namely reliable data to make predictions and to plan for investment as well as for other actions of stakeholders in the energy markets is one of the factors with the highest influence on energy security. This uncertainty can be connected with many factors, such as the availability of reliable data or actions of stakeholders themselves. For example, the recent outbreak of the COVID-19 pandemic revealed negative impacts of uncertainty on decision-making processes and markets. At the time point when the market participants started to receive real-time information about the situation, the energy markets began to ease. This is one scenario where Big Data can be used to amplify information to various stakeholders to prevent panic and to ensure market stability and security of supply. Considering the novelty of this topic, our methodology is based on the meta-analysis of existing studies in the area of impacts of energy security on private companies, the national economy, and society. The results show that, in a fast-paced digital world characterized by technological advances, the use of Big Data technology provides a unique niche point to close this gap in information disparity by levering the use of unconventional data sources to integrate technologies, stakeholders, and markets to promote energy security and market stability. The potential of Big Data technology is yet to be fully utilized. Big Data can handle large data sets characterized by volume, variety, velocity, value, and complexity. Our conclusion is that the challenge for energy markets is to leverage this technology to mine available socioeconomic, political, geographic, and environmental data responsibly and to provide indicators that predict future global supply and demand. This information is crucial for energy security and ensuring global economic prosperity.
... For businesses, data extraction, analysis, and representation are crucial for decision making. However, some challenges are coming along with big data mining such as risks to privacy, security and complexity [15]. As traditional mining techniques are not able to provide cost-effective solution besides having inability to leverage parallel processing power of resources, it is inevitable to go for big data mining with newly built data mining technologies. ...
Preprint
Full-text available
The importance of energy security for successful functioning of private companies, national economies, and the overall society should not be underestimated. Energy is a critical infrastructure for any modern society, and its reliable functioning is essential for all economic sectors and for the well-being of everybody. Uncertainty in terms of the availability of information, reliable data to make predictions and to plan for investment as well as for other actions of stakeholders at the energy markets is one of the factors, which has the highest influence on energy security. This uncertainty can be connected with many factors such as the availability of reliable data or the actions of stakeholders themselves. For example, the recent outbreak of the COVID-19 pandemic revealed negative impacts of uncertainty on decision-making processes and markets. At the time point when the market participants started to receive real-time information about the situation, the energy markets began to ease. This is one scenario where Big Data can be used to amplify information to various stakeholders to prevent panic and to ensure market stability and security of supply. In a fast-paced digital world characterized by technological advances, the use of Big Data technology provides a unique niche point to close this gap in information disparity by levering the use of unconventional data sources to integrate technologies, stakeholders, and markets to promote energy security and market stability. The potential of Big Data technology is yet to be fully utilized. Big Data can handle large data set characterized by volume, variety, velocity, value, and complexity. The challenge for energy markets is to leverage this technology to mine available socioeconomic, political, geographic, and environmental data responsibly as well as to provide indicators that predict future global supply and demand. This information is crucial for energy security and ensuring global economic prosperity.
... So far, there are numerous pieces of system software for HRM, but these system types are very homogeneous and are used for statistical data, with little interactivity as well as compatibility and more repetitive operations, which waste a lot of system resources [9]. With the emergence of integrated HRMS, management resources can be fully integrated to create favourable conditions for the development of various other tasks [10]. ...
Article
Full-text available
In this paper, the optimization of the enterprise HR information system is studied based on IoT first-off technology, the system demand phase is analysed, and the edge control system is designed and built. The hardware and software system and edge node management platform are implemented first, and then the communication scenarios between the edge layer of the system and the sensing layer, the edge layer, and the cloud layer are analysed, and the business type-driven link selection algorithm and the northbound multilink switching algorithm are designed and implemented, respectively, to guarantee the communication reliability between different layers of the system. Based on the implementation of the above functions, the edge control system can meet the intelligence, expandability, and security requirements of IoT applications. An in-depth investigation and research are launched mainly on the enterprise demand to determine the functional requirements and performance requirements of the enterprise and to achieve the basic logical structure; in the system design phase, the system architecture and other aspects of the design are realized. According to the conditions of the system function structure, a number of system module functions are designed in detail. The system is composed of the following modules, namely, personnel change management, organization management, and salary and benefits management. The system consists of the following modules, namely, personnel change management, organization management, compensation and benefits management, and personnel information management. The system modules run through the process of human resource management; in the system implementation stage, the system coding and page operation are realized based on the development tools and software development techniques. The system finally achieves the system design objectives and is put on a trial operation to meet its actual business requirements.
... At the point when shortcomings are recognized in built up ways, an adaptive testing method is propelled trying to identify the broken connections. Broken connections are given diminished rating and are therefore stayed away from.Just and Kranakis[18] and Kargl et al[19] proposed schemes for recognizing egotistical or noxious nodes in an ad hoc network. The schemes include examining mechanisms which are comparative in usefulness to that of Awerbuch et al[6] above Patwardhan and Lorga [20] exhibited a secure routing convention called Sec AODV. ...
Article
Full-text available
Mobile Ad hoc Network (MANET) is gathered as a self-sorted out network with mobile nodes with a dynamic foundation. Designing of secure routing protocols is extremely troublesome as a result of its attributes. Also, protocols are designed with suspicion of no vindictive or childish nodes in network. Subsequently, to design robust and secured routing protocols a few impacts made from scientists. In this paper, audit on writing review on essential secure routing protocols exhibited. The overview is arranged to Basic Routing Security Schemes, Trust-Based Routing Schemes, Incentive-base plans Schemes which utilize detection and isolation mechanisms.
... [14] Big Data Mining focuses on information that provides comprehensive knowledge that can represent predictive, current and historical views that can help in making accurate business decisions. [15] Data mining can be applied to various fields that have a number of data, but because the research area has a long history, and has not passed through the 'adolescence' period, data mining is still being debated. the position of the field of knowledge that has it. ...
... (2) Managerial Implications : Decision makers continuously spend hours to understand the insights out of the data received from different sources (Sriramoju, 2017). At the same time, business decision making capacity lies in the application of data logic and processes to find the business information, that is, forecasting problem solving metrics, opportunity of innovation, and long-term sustainability, etc. (Oswaldo, Sergio, Cáceres, & Schweimanns, 2016). ...
Article
Full-text available
Review of literature is a very critical part of the research journey. The tenacity of this research was to explain a step-by-step guide to expedite understanding by presenting the critical components of the literature review process. We collected and synthesized business intelligence specific research papers from relevant journals with the help of web aggregator. This research paper discussed the strategy of analyzing 553 business intelligence research papers published from 2007-2018. We utilized exploratory research methodology to analyze the research conducted on BI solutions during the defined period. The research ripened a holistic, theoretically grounded, and relevant approach for reviewing the literature on business intelligence. It specified, defined, and positioned the existing BI solution research and helped identify the areas which need further exploration.
... Data mining is a modern concept for analyzing data that may at first be inaccurate, heterogeneous, contain gaps, and also have huge volumes. The need for regular analysis of such data has arisen as a result of the spread of information technologies that allow for a detailed logging of the processes of production, trade and finance (Sriramoju, S. B. (2017)). Literally, data mining translates as mining or digging data. ...
Article
Full-text available
The behavior of agents to ensure financial security on the basis of game theory was analyzed, the winning strategy taking into account risk and uncertainty was determined. Using Data Mining the useful functions of this technology were identified to ensure financial security: suspicious transactions determination, credit risks analysis, client account reliability analysis, financial indicators predicting and risks control. A comparison was made of the assessment of the effectiveness of various data mining algorithms on the nature of financial transactions and decision-making procedures in the financial security system. It was proved that the development of information technology has created a whole range of vulnerabilities in the financial system, in particular, has transformed the form of money in modern conditions - the emergence of a cryptocurrency. The influence of the formation and development of cryptocurrency on financial security at all levels of the economy: micro and macro was analyzed.
... Today schedule of high-capacity networks, inexpensive computer systems and also storage space gadgets along with the prevalent fostering of equipment virtualization, serviceoriented design, as well as free and also energy computer have actually caused a development in cloud computing. Cloud suppliers are experiencing development prices of 50% per year [16]. ...
Article
Full-text available
Typically Cloud Computing solutions are supplied by a 3rd party company that possesses the infrastructure. Cloud Computer holds the possibility to get rid of the needs for establishing of high-cost computer framework for IT-based options as well as solutions that the industry makes use of. It guarantees to give a versatile IT style, easily accessible with the net from lightweight mobile devices. Many sectors, such as financial, health care and also education and learning are relocating in the direction of the cloud as a result of the effectiveness of solutions supplied by the pay-per-use pattern based upon the sources such as refining power utilized, purchases performed, data transfer taken in, information moved, or storage area inhabited etc. In a cloud computing setting, the whole information lives over a collection of networked sources, making it possible for the information to be accessed via digital machines. As the trends of making use of all solutions create the remote system without making it personal by pay-per-use basis is expanding on enhancing, the service classifications are cloud system is expanding their service locations. In this paper, we are offering a lot of solutions in various computer systems as well as applications. As the cloud Computing system is playing a significant function in typically all companies, we offer several of the dislike trends in the cloud computing systems.
... Data mining is a modern concept for analyzing data that may at first be inaccurate, heterogeneous, contain gaps, and also have huge volumes. The need for regular analysis of such data has arisen as a result of the spread of information technologies that allow for a detailed logging of the processes of production, trade and finance (Sriramoju, S. B. (2017)). Literally, data mining translates as mining or digging data. ...
Article
Full-text available
The behavior of agents to ensure financial security on the basis of game theory was analyzed, the winning strategy taking into account risk and uncertainty was determined. Using Data Mining the useful functions of this technology were identified to ensure financial security: suspicious transactions determination, credit risks analysis, client account reliability analysis, financial indicators predicting and risks control. A comparison was made of the assessment of the effectiveness of various data mining algorithms on the nature of financial transactions and decision-making procedures in the financial security system. It was proved that the development of information technology has created a whole range of vulnerabilities in the financial system, in particular, has transformed the form of money in modern conditions - the emergence of a cryptocurrency. The influence of the formation and development of cryptocurrency on financial security at all levels of the economy: micro and macro was analyzed.