An empirical study of cloud computing and big data analytics
Dr. Emad Al-Shawakfa2018, International Journal of Innovative Computing and Applications
Sign up for access to the world's latest research
checkGet notified about relevant papers
checkSave papers to use in your research
checkJoin the discussion with peers
checkTrack your impact
Abstract
The rapid growth in social media usage introduced new trends to be in line with social media technologies such as 'big data' and 'cloud computing'. Organisations collect data to use it at new levels to share accurate and stable business experimentation that direct decision makers to make brilliant decisions and help organisations make decisions in real time. These trends have also guided into a revolutionary transformation in research, invention, and business marketing. This paper highlights some aspects of big data and cloud computing with their effects on an organisation's business. Furthermore, some issues of using big data and cloud computing in various environments and the usage of cloud computing for Internet of things and issues about it were also discussed. The paper is organised into five sections: introduction, background, literature review; with subsections about Hadoop, cloud computing, and big data. Section 4 gives challenges while Section 5 gives the conclusions.
Figures (6)
Related papers
Big Data Analytics and Cloud Computing-Implementation Issues and Effects
SSRN Electronic Journal, 2021
The study presents a research paper on big data analytics and cloud computing and some of the issues and implications associated with these technologies. The research specifically aimed at identifying the implications and issues of the two technologies and what business leaders should do to prevent the issues identified. The TAM model is reviewed in the theoretical framework. The data analysis section shows that the applications and ease of use of big data analytics and cloud computing have contributed to their increased use. Big data analytics is identified to be especially crucial in decision-making. Cloud computing, on the other hand, helps in cost saving and scalability of operations within a business. Business leaders should, therefore, implement these technologies and improve their overall growth and effectiveness.
Impact and Implications of Big Data Analytics in Cloud Computing Platforms
International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022
Big Data and Cloud Computing as two mainstream technologies, are at the center of concern in the IT field. Cloud Computing refers to the processing of anything, including Big Data Analytics, on the "cloud". The "cloud" is just a set of highpowered servers from one of many providers. They can often view and query large data sets much more quickly than a standard computer could. Essentially, "Big Data" refers to the large sets of data collected, while "Cloud Computing" refers to the mechanism that remotely takes this data in and performs any operations specified on that data. Cloud Computing services largely exist because of Big Data. Likewise, the only reason that we collect Big Data is because we have services that are capable of taking it in and deciphering it, often in a matter of seconds. The two are a perfect match, since neither would exist without the other. The combination of both yields beneficial outcome for the organizations. Not to mention, both the technologies are in the stage of evolution but their combination leverages scalable and cost-effective solution in big data analytics. Big data and Cloud computing are perfect combination. Besides that, there are also some real-time challenges to deal with. In this paper, discribes both the aspects. This paper introduces the characteristics, trends and challenges of big data. In addition to that, it investigates the benefits and the risks that may rise out of the integration between big data and cloud computing.
HOW BIG DATA, CLOUD AND ANALYTICS (BDCA) HAVE
TRANSFORMED INFORMATION TECHNOLOGY
Integration of architectures that make use of big data analytics and cloud computing can help Information technology departments, both public and private agencies, gain competitive advantage. This dynamic encourages innovations and leads to increased revenues. The actualization of cloud computing technologies provides a timely and cost-effective data management aimed at increasing the efficiency and effectiveness of these services. Such outcomes contribute to increased security and agility. Setting: The paper highlights the current global and regional trends of Big Data, Cloud Computing and Analytics (BDCA). The regions under study include Africa, Asia, Europe, North and South America. The paper seeks to identify the impact of using big data analytics and cloud computing by information technology departments at academic institutions, private and public agencies, and determine the progress registered globally and by each region, respectively. Audience: The target audience of the paper includes and is not limited to academia, private and public organizations as well as the general population at large. Methodology: Various academic research articles/journals covering the topic of big data, cloud computing and analytics were reviewed during preparation and compilation of this paper. The relevant articles illustrate the trend of big data analytics and cloud computing globally and in the five regions of interest. There were different levels of how big data analytics and cloud computing have been embraced by both private and public agencies in their Information Technology departments of academic institutions. Attempts were also made to highlight developments in sampled thematic areas. However, limited access to the appropriate data and to relevant reports continue to be a major challenge. Findings: The research revealed the regional variations in the application of BDCA. North America and Europe registered a higher level of cloud computing services, at 363,804 and 240,780 petabytes in 2016, respectively (Giannakouris & Smihily, 2017, p.1). On the other hand; Africa, South America and Asia, excluding countries like Japan, were still struggling to achieve increased application of the new technology in the management and application of big data analytics (Giannakouris & Smihily, 2017, p.1). The successful application of Big Data Analytics and Cloud Computing has not only revolutionized information technology departments across the world, but also its impacts have been witnessed in almost every sector of society. Thematic areas such as health, aviation, science and technology, research, education, manufacturing and finance have been among the main beneficiaries of this technological advancement. Also, people are effectively able to share information through social networks and stream live events from their remote areas, which is an advantage all on its own for this generation of technologically advanced individuals. Conclusion: The evidence shows the numerous benefits resulting from application of BDCA. The technology increased information sharing and promoted economic growth by optimizing the efficiency of services delivered 349 350 How Big Data, Cloud and Analytics (BDCA) have Transformed Information Technology in the society. The biggest and evolving challenge in BDCA is the ability to mitigate malware, phishing and spams.
The Rise of Big Data and Cloud Computing
Internet of Things and Cloud Computing, 2019
Big Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for digital earth applications including business, sciences and engineering. At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. Cloud computing provides fundamental support to address the challenges with shared computing resources including computing, storage, networking and analytical software; the application of these resources has fostered impressive Big Data advancements. This paper surveys the two frontiers-Big Data and cloud computing-and reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains. While Big Data is responsible for data storage and processing, the cloud provides a reliable, accessible, and scalable environment for Big Data systems to function. Big Data is defined as the quantity of digital data produced from different sources of technology, for example, sensors, digitizers, scanners, numerical modeling, mobile phones, Internet, videos, social networks. Cloud Computing and Big Data are complementary to each other. Rapid growth in Big Data is regarded as a problem. Clouds are evolving and providing solutions for the appropriate environment of Big Data while traditional storage cannot meet the requirements for dealing with Big Data, in addition to the need for data exchange between various distributed storage locations. Cloud Computing provides solutions and addresses problems with Big Data. Big data and Cloud computing both the technologies are valuable on its own. Furthermore, many businesses are targeting to combine the two techniques to reap more business benefits. Both the technologies aim to enhance the revenue of the company while reducing the investment cost. While Cloud manages the local software, Big data helps in business decisions. In paper introduces the relationship between Big Data and Cloud Computing, Cloud Computing role of Big Data, advantages of Big Data and Cloud computing, cloud architecture, importance of Cloud Computing.
Big Data and Cloud Computing
Joe Celko’s Complete Guide to NoSQL, 2014
Cloud computing is one of the most significant shifts in modern ICT and service for enterprise applications and has become a powerful architecture to perform large-scale and complex computing. Big data provides users the ability to use commodity computing to process distributed queries across multiple datasets and return resultant sets in a timely manner. Big data utilizes distributed storage technology based on cloud computing rather than local storage attached to a computer or electronic device. Big data evaluation is driven by fast-growing cloud-based applications developed using various categories of big data. Cloud computing, big data and its applications, advantages are likely to represent the most promising new frontiers in science. Clouds are also being used to deal with the Big data to effectively store and exploit the unstructured data of the organizations. This paper presents an overview of the cloud computing scenario today, different examples of the cloud services, different enterprises in the field of cloud computing are being mentioned in the paper. How cloud is related with big data and what are the possible solutions of big data in today's scenario is also discussed in the paper.
Big Data and Cloud Computing: Trends and Challenges
International Journal of Interactive Mobile Technologies (iJIM), 2017
Big data is currently one of the most critical emerging technologies. Big Data are used as a concept that refers to the inability of traditional data architectures to efficiently handle the new data sets. The 4V’s of big data – volume, velocity, variety and veracity makes the data management and analytics challenging for the traditional data warehouses. It is important to think of big data and analytics together. Big data is the term used to describe the recent explosion of different types of data from disparate sources. Analytics is about examining data to derive interesting and relevant trends and patterns, which can be used to inform decisions, optimize processes, and even drive new business models. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its own challenge of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big ...
Cloud Computing and Big Data is there a Relation between the Two : A Study
2017
Communicating by using information technology in various ways produces big amounts of data. Such data requires processing and storage. The cloud is an online storage model where data is stored on multiple virtual servers. Big data processing represents a new challenge in computing, especially in cloud computing. Data processing involves data acquisition, storage and analysis. In this respect, there are many questions including, what is the relationship between big data and cloud computing? And how is big data processed in cloud computing? The answer to these questions will be discussed in this paper, where the big data and cloud computing will be studied, in addition to getting acquainted with the relationship between them in terms of safety and challenges. We have suggested a term for big data, and a model that illustrates the relationship between big data and cloud computing.
Cloud Computing and Big Data Analytics
2013
A large volume of data is generated by many applications which cannot be managed by traditional relational database management system. As organizations use larger and larger data warehouses for ever increasing data processing need, the performance requirements continue to outpace the capabilities of the traditional approaches. The cloud based approach offers a means for meeting the performance and scalability points of the enterprise data management providing agility to the database management infrastructure. As with other cloud environments, data management in the cloud benefits end users by offering a pay-as-you-go (or utility based) model and adaptable resource requirements that free up enterprises from the need to purchase traditional hardware and to go through extensive procurement process frequently. The data management, integration and analytics can be offloaded to public and/or private clouds. By using public cloud, enterprises can get processing power and infrastructure as needed, whereas with public cloud enterprises can improve the utilization of the existing infrastructure. By using cloud computing, enterprises can effectively handle the wide ranging database requirements with minimum effort, thus allowing them to focus on the core work rather than getting bogged down with infrastructure. Despite all these benefits, decision to move from dedicated infrastructure to the cloud based Data processing depends on several logistics and operational factors such as security, privacy, availability etc
Analysis of issues and trends in Big Data Platforms
In this paper, we discuss the Big Data issues and related solutions in market. We are living in an era where information.is of utmost importance. Due to emergence of new technologies in recent years, data production is also increased for example IOT technology. Internet of things technology created a data production opportunity for every device in the world. We also see that different organizations are also using their raw data for statistical purposes as it is helping in predicting customer's behavior and market trends. Use of social network sites is also increased in past few years. Social sites are producing a large amount of big data that is not useful every time so to make sense of this useless data is a big challenge. In business perspective it is also important to know whether storing, managing and describing this raw data is useful in terms of business output or not. Different techniques and tools are being used to manage and understanding the big data. Map Reduce and Hadoop are well known in BigData market. We also presented big data production trends since last few years and new challenges to big data. We also lined up some big data solutions in market with some features that can be helpful for big data implementation for a business organization. We also conducted a test using different frameworks and presented the results. We also presented some good practices for big data implementation to achieve high business goals.
Big Data in Cloud Computing: A Resource Management Perspective
Scientific Programming, 2018
The modern day advancement is increasingly digitizing our lives which has led to a rapid growth of data. Such multidimensional datasets are precious due to the potential of unearthing new knowledge and developing decision-making insights from them. Analyzing this huge amount of data from multiple sources can help organizations to plan for the future and anticipate changing market trends and customer requirements. While the Hadoop framework is a popular platform for processing larger datasets, there are a number of other computing infrastructures, available to use in various application domains. The primary focus of the study is how to classify major big data resource management systems in the context of cloud computing environment. We identify some key features which characterize big data frameworks as well as their associated challenges and issues. We use various evaluation metrics from different aspects to identify usage scenarios of these platforms. The study came up with some in...
A Review on Cloud Based Big Data Analytics
— Today's computing world is facing tsunami and driving without riding on this tsunami towards next generation computing is no choice. So many IT companies decided to grow up with this tsunami like technology. One of these is cloud computing and another is Big data. Currently more than 5 billion mobile users, nearly same facebook, and other social media user generate this tsunami of data. On another side to deliver this services of big data a model called as cloud computing is spreading everywhere as next generations IT Service model. Both technologies continue to evolve. Ultimately, as a cloud, computing development matures, every top mind of organizations will think for development of efficient and agile cloud environment. At the other side, every cloud provider offers the services to the huge number data processing companies that generate data process data and make decision on cloud infrastructure. Ultimately its today's need to think on futures efficient cloud based Big data analytics In this review paper we are focusing on, how we can club Big data and cloud Computing in one frame of development.
The Future of Big Data in Cloud
Big data describes a large volume of data. This data is used on daily basis, it is not the amount of data that is most important, it is what the data is used for that matters and is most important, especially when it has to do with using the data to increase the efficiency and effectiveness of the business. Big data can be analyzed for insights that lead to better decisions and strategic business moves. The size of this data created is beyond the ability of typical database software tools to capture, store, manage, and analyze. Nowadays Big data ranges from a few dozen of terabytes to multiple petabytes (thousands of terabytes). This data can be measure in the value of data initiatives along the dimensions of the four Vs of big data. Measuring the value of data is an endless process, it is the way we make use of data that allows us to fully recognize its true value and importance to improve our decision making capabilities. These approach place high emphasis on the importance of every individual data item that goes into these systems and, as a result, highlight the importance of every single outcome linking to business impacts delivered. Big Data is now becoming a critically important driver of business success across sectors, but many executives say they don’t think their companies are equipped to make the most of it.
Big Data and Current Cloud Computing Issues and Challenges
Big data applications are a great benefit to organizations, business, companies and many large scale and small scale industries .We also discuss various possible solutions for the issues in cloud computing security and Hadoop. Cloud computing security is developing at a rapid pace which includes computer security, network security, information security, and data privacy. Cloud computing plays a very vital role in protecting data, applications and the related infrastructure with the help of policies, technologies, controls, and big data tools. Big data is a data analysis methodology enabled by recent advances in technologies and architecture. Cloud computing is a set of it services that are provided to a customer over a network on a leased basis and with the ability to scale up or down their service requirements. It advantages includes scalability, resilience, flexibility, efficiency and outsourcing non-core activities. This paper introduces a detailed analysis between big data and cloud computing security issues and challenges focusing on the cloud computing types and the service delivery types. However, big data entails a huge commitment of hardware and processing resources, making adoption costs of big data technology prohibitive to small and medium sized businesses. It offers an innovative business model for organizations to adopt it services without upfront investment irrespective of the potential gains achieved from the cloud computing, the organizations are slow in accepting it due to the security issues and associated challenges security is one of the major issues which hamper the growth of cloud. The use of big data could provide sufficient benefit to a small to medium sized company to the extent that the business would be willing to commit resources to implement big data technology in-house. However, the level of benefit is difficult to determine without some experience. The main focus is on security issues in cloud computing that are associated with big data. Moreover, cloud computing, big data and its applications, advantages are likely to represent the most promising new frontiers in science
IRJET- The Upsurge of Cloud Computing and Big Data
IRJET, 2020
Big Data has emerged on the scene in the initial years of 21 st century. Companies like Google, LinkedIn, Facebook, eBay were created around big data from their beginning. It has become an uprising Model which provides large data and opportunities to progress and enables research, decision making in almost all the branches of study. While allowing for all these opportunities it is difficult for firms to store, process, transport, mine and serve the data. To minimize these difficulties the Cloud computing is introduced, which basically provides essential support to address the challenges with shared resources such as computing, storages, networking and software based on analytics. This paper investigates the two edges-Big Data and cloud computing-and analyses the advantages and significances of utilizing cloud computing to tackling Big Data in the digital world and applicable science provinces. While Big Data is accountable for data storage and processing, the cloud provides a dependable, accessible, and scalable environment for Big Data systems to operate. Big Data is defined as the amount of digital data produced from diverse sources of technology, for example, sensors, digitizers, scanners, numerical modeling, mobile phones, Internet, videos, social networks. Cloud Computing and Big Data are corresponding to each other. Swift development in Big Data is observed as a problem. Clouds are developing and providing solutions for the suitable environment of Big Data while outdated storage cannot meet the necessities for dealing with Big Data, in addition to the essential for data exchange between several scattered storage sites. Cloud Computing provides solutions and addresses difficulties with Big Data. Big data and Cloud computing both the technologies are respected on its own. Furthermore, many trades are targeting to combine the two techniques to gain more business benefits. Both the technologies intention to enhance the profits of the company while reducing the investment cost. While Cloud achieves the local software, Big data helps in business decisions. In paper presents the connection between Big Data and Cloud Computing, Cloud Computing role of Big Data, advantages of Big Data and Cloud computing, cloud architecture, importance of Cloud Computing.
A Roadmap Towards Big Data Opportunities, Emerging Issues and Hadoop as a Solution
International Journal of Education and Management Engineering (IJEME), 2020
The concept of Big Data become extensively popular for their vast usage in emerging technologies. Despite being complex and dynamic, big data environment has been generating the colossal amount of data which is impossible to handle from traditional data processing applications. Nowadays, the Internet of things (IoT) and social media platforms like, Facebook, Instagram, Twitter, WhatsApp, LinkedIn, and YouTube generating data in various formats. Therefore, this promotes a drastic need for technology to store and process this tremendous volume of data. This research outlines the fundamental literature required to understand the concept of big data including its nature, definitions, types, and characteristics. Additionally, the primary focus of the current study is to deal with two fundamental issues; storing an enormous amount of data and fast data processing. Leading to objectives, the paper presents Hadoop as a solution to address the problem and discussed the Hadoop Distributed File System (HDFS) and MapReduce programming framework for storage and processing in Big Data efficiently. Future research directions in this field determined based on opportunities and several emerging issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal solutions to address Big Data storage and processing problems. Moreover, this study contributes to the existing body of knowledge by comprehensively addressing the opportunities and emerging issues of Big Data.
The importance of big data technology
International Journal of Engineering & Technology, 2018
The adoption of Web 2.0 technologies, Internet of Things, etc. by individuals and organization has led to an explosion of data. As it stands, existing Relational Database Management Systems (RDBMSs) are incapable of handling this deluge of data. The term Big Data was coined to represent these vast, fast and complex datasets that regular RDBMSs could not handle. Special tools or frameworks were developed to deal with processing, managing and storing this big data. These tools are capable of functioning in distributed industry- standard environments thereby maintaining efficiency and effectiveness at a business level. Apache Hadoop is an example of such a framework. This report discusses big data, it origins, opportunities and challenges that it presents, big data analytics and the application of big data using existing big data tools or frameworks. It also discusses Apache Hadoop as a big data framework and provides a basic overview of this technology from technological and business ...
Big Data using Cloud Computing - Opportunities for Small and Medium-sized Enterprises
European Journal of Economics and Business Studies, 2016
Big Data has been listed as one of the current and future research frontiers by Gartner. Large-sized companies are already investing on and leveraging big data. Small-sized and medium-sized enterprises (SMEs) can also leverage big data to gain a strategic competitive advantage but are often limited by the lack of adequate financial resources to invest on the technology and manpower. Several big data challenges still exist especially in computer architecture that is CPU-heavy but I/O poor. Cloud computing eliminates the need to maintain expensive computing hardware and software. Cloud computing resources and techniques can be leveraged to address the traditional problems associated with fault tolerance and low performance causing bottlenecks to using big data. SMEs can take advantage of cloud computing techniques to avail the advantages of big data without significant investments in technology and manpower. This paper explores the current trends in the area of big data using cloud re...
Emerging Trends on Big Data & Cloud Computing
International journal of machine learning and networked collaborative engineering, 2017
In this paper we focused on the emerging trends and various approaches for carrying out analytics on clouds for Big Data application. It revolves around four important analytics and Big Data. We also discussed about the some of the real world challenges in this cloud and Big Data computing era. This paper also focused on the implementation strategy of Big Data like Management, Data Varity etc. It helps to identify the technology gaps which may help to research communities so that they will have a directions for future scope of Big Data based on cloud computing.
REVIEW : Big Data on Cloud Computing
2015
Today, the world has become closer due to the development of Internet. More people communicate via Internet, and the volume of data to be handled also grows. Nowadays, we talk about petaand zettabytes of data and this volume of data needs to be processed and analyzed further which had led to the research field of big data storage and analysis. Cloud computing is another emerging area in which the services such as infrastructure, storage, and software are provided to the consumers on demand basis. In this paper, we discuss about the big data, cloud computing, and how big data are handled in cloud computing environment. Furthermore, The definition, characteristics, and classification of big data along with some discussions on cloud computing are introduced. The relationship between big data and cloud computing, big data storage systems, and Hadoop technology are also discussed. Lastly, research challenges are investigated, with focus on scalability, availability, data integrity, data ...
Survey Paper on Challenges of Big Data and Cloud Computing
2016
Big data is more important in providing more accurate analysis, which may lead to better decision making resulting in greater efficiencies, cost reductions, and reduced risks for the business. To harness the power of big data, you would require an infrastructure that can manage and process huge volumes of structured and unstructured data in real time and can protect data privacy and security. The issue of computing, security, storing, and privacy, and analytics are all exaggerated by the volume, velocity and diversity of big data, such as large-scale cloud infrastructures, diversity of data sources and formats, streaming nature of data attainment and high volume intercloud relocation.
Related topics
Loading Preview
Sorry, preview is currently unavailable. You can download the paper by clicking the button above.