Cloud computing is a model that enables on-demand access to shared computing resources like servers, storage, databases, networking, software, analytics and intelligence over the Internet. It allows users to access applications from anywhere rather than installing them on their own computers. While cloud computing provides benefits like reduced costs, increased flexibility and collaboration, it also poses security risks since data is stored externally on the Internet and controlled by third-party providers.
This document provides an introduction and overview of cloud computing. It defines cloud computing as a model that enables network access to configurable computing resources that can be rapidly provisioned and released with minimal management effort. The document discusses how cloud computing allows users and companies to avoid upfront infrastructure costs and adjust resources to meet fluctuating demand. It also examines different perspectives on cloud computing and provides definitions from industry leaders to clarify what cloud computing is and how it relates to concepts like utility computing.
Cloud Computing for Universities Graduation ProjectMohamed Shorbagy
The document discusses a university project that aims to implement cloud computing services within the university. Specifically, the project will virtualize the university's datacenter using VMware and OpenStack solutions. This will provide virtual servers, desktops, and applications to researchers, students, and staff to facilitate research and education. The cloud services will reduce costs and complexity while improving flexibility, mobility, and sustainability. The project team has already transformed their faculty's datacenter and is providing virtual resources to researchers and graduation projects. They organized the first cloud computing conference in Egypt to promote research clouds.
This document is a technical seminar report on cloud computing submitted in partial fulfillment of a Bachelor of Engineering degree. It introduces cloud computing as a concept where computing resources such as servers, storage, databases and networking are provided as standardized services over the Internet. The document discusses the history, characteristics, implementation and economics of cloud computing and provides examples of major companies involved in cloud services.
Cloud computing refers to storing and accessing data and programs over the Internet instead of a local computer's hard drive. It offers various online services through a network of remote servers. There are different types of cloud services and deployment models depending on who can access the cloud - public, private, hybrid or community. The main cloud service models are Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). While cloud computing provides benefits like flexible access to data and lower costs, it also poses security and privacy risks if data is not properly protected on remote servers.
Cloud computing refers to internet-based services and software hosted remotely. It allows ubiquitous access to data and applications from anywhere. There are several types of cloud services including Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). While the cloud provides opportunities like reduced costs and access from anywhere, there are also concerns about security, dependence on large internet companies, and lack of control over data.
Cloud computing allows users to access shared computing resources over the network. It maximizes resource use by dynamically allocating resources across users and locations. Cloud services include Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). While the term cloud computing has been used since the 1960s, it is still evolving today to provide on-demand access to computing resources and data from anywhere.
Cloud computing is a model that enables on-demand access to shared computing resources like servers, storage, databases, networking, software, analytics and intelligence over the Internet. It allows users to access applications from anywhere rather than installing them on their own computers. While cloud computing provides benefits like reduced costs, increased flexibility and collaboration, it also poses security risks since data is stored externally on the Internet and controlled by third-party providers.
This document provides an introduction and overview of cloud computing. It defines cloud computing as a model that enables network access to configurable computing resources that can be rapidly provisioned and released with minimal management effort. The document discusses how cloud computing allows users and companies to avoid upfront infrastructure costs and adjust resources to meet fluctuating demand. It also examines different perspectives on cloud computing and provides definitions from industry leaders to clarify what cloud computing is and how it relates to concepts like utility computing.
Cloud Computing for Universities Graduation ProjectMohamed Shorbagy
The document discusses a university project that aims to implement cloud computing services within the university. Specifically, the project will virtualize the university's datacenter using VMware and OpenStack solutions. This will provide virtual servers, desktops, and applications to researchers, students, and staff to facilitate research and education. The cloud services will reduce costs and complexity while improving flexibility, mobility, and sustainability. The project team has already transformed their faculty's datacenter and is providing virtual resources to researchers and graduation projects. They organized the first cloud computing conference in Egypt to promote research clouds.
This document is a technical seminar report on cloud computing submitted in partial fulfillment of a Bachelor of Engineering degree. It introduces cloud computing as a concept where computing resources such as servers, storage, databases and networking are provided as standardized services over the Internet. The document discusses the history, characteristics, implementation and economics of cloud computing and provides examples of major companies involved in cloud services.
Cloud computing refers to storing and accessing data and programs over the Internet instead of a local computer's hard drive. It offers various online services through a network of remote servers. There are different types of cloud services and deployment models depending on who can access the cloud - public, private, hybrid or community. The main cloud service models are Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). While cloud computing provides benefits like flexible access to data and lower costs, it also poses security and privacy risks if data is not properly protected on remote servers.
Cloud computing refers to internet-based services and software hosted remotely. It allows ubiquitous access to data and applications from anywhere. There are several types of cloud services including Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). While the cloud provides opportunities like reduced costs and access from anywhere, there are also concerns about security, dependence on large internet companies, and lack of control over data.
Cloud computing allows users to access shared computing resources over the network. It maximizes resource use by dynamically allocating resources across users and locations. Cloud services include Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). While the term cloud computing has been used since the 1960s, it is still evolving today to provide on-demand access to computing resources and data from anywhere.
Cloud computing provides on-demand access to shared computing resources like networks, servers, storage, applications and services over the internet. It aims to address growing IT needs like increasing server capacity, reducing costs through pay-per-use models, and integrating external web applications. Cloud computing exhibits characteristics of utility computing, virtualization, and elastic scalability. The key service models are Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). Cloud deployment models include private, public, community and hybrid clouds.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Cloud computing is the practice of using remote servers on the Internet to store, manage, and process data rather than local servers or personal computers. It enables users to access computing resources like applications and data storage over the Internet. The main benefits are flexibility, scalability, and pay-per-use pricing. Cloud services can be public, private, or hybrid. Public clouds are owned by third-party providers and sold on-demand. Private clouds are owned and operated within a single organization. Hybrid clouds combine private and public cloud services and resources.
Imagine yourself in the world where the users of the computer of today’s internet world don’t have to run, install or store their application or data on their own computers, imagine the world where every piece of your information or data would reside on the Cloud (Internet).
This document is a seminar report on cloud computing submitted by Vishnuvarunan.T. It provides an introduction to cloud computing, discussing its key characteristics including on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service. It also covers cloud service models such as Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). The document discusses cloud deployment models including private cloud, community cloud, public cloud, and hybrid cloud. It notes some benefits of cloud computing like cost savings and scalability, as well as challenges around security, privacy, lack of standards, and compliance concerns.
This document discusses cloud computing. It begins with an introduction defining cloud computing as allowing users to access virtually unlimited computing resources over the internet. It then discusses the architecture of cloud computing including front-end and back-end components. The main components of a cloud are infrastructure, storage, platform, applications, services, and clients. There are different types of clouds including public clouds, private clouds, and hybrid clouds that use a mix of internal and external providers. Cloud services are divided into infrastructure as a service, platform as a service, and software as a service. The document concludes with some key characteristics of cloud computing such as its cost effectiveness and features like platform and location independence.
Cloud computing is Internet based development and use of computer technology. It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them. Cloud computing is a hot topic all over the world nowadays, through which customers can access information and computer power via a web browser. As the adoption and deployment of cloud computing increase, it is critical to evaluate the performance of cloud environments. Currently, modeling and simulation technology has become a useful and powerful tool in cloud computing research community to deal with these issues. Cloud simulators are required for cloud system testing to decrease the complexity and separate quality concerns. Cloud computing means saving and accessing the data over the internet instead of local storage. In this paper, we have provided a short review on the types, models and architecture of the cloud environment.
A proposal for implementing cloud computing in newspaper companyKingsley Mensah
This proposal recommends implementing cloud computing for a newspaper company's management information system using Microsoft Azure's infrastructure as a service (IaaS) public cloud model. It analyzes cloud computing and virtualization concepts. The strategy is to move backup storage to the cloud, virtualize staff/management PCs for improved security, and implement the Azure cloud to cut costs by 50% compared to current on-premise infrastructure expenses. Virtualizing access through the cloud will strengthen security while taking advantage of Azure's competitive pricing and 30-day free trial.
This document provides a seminar report on cloud computing submitted by Vanama Vamsi Krishna in partial fulfillment of the requirements for a Bachelor of Technology degree. The 3-page report includes an abstract, table of contents, introduction on cloud computing concepts, a brief history of cloud computing, key characteristics of cloud computing including cost, scalability and reliability, components and architecture of cloud computing, types and roles in cloud computing, merits and demerits, and a conclusion. The report provides a high-level overview of cloud computing fundamentals.
This document discusses security issues related to data location in cloud computing. It notes that cloud computing allows on-demand access to computing resources over the internet, but users often do not know where their data is physically stored or which country's laws govern the data. The research aims to develop a model for controlling data resources stored in cloud servers and implementing data manipulation techniques to protect data from unauthorized access across different country servers. The proposed action research methodology involves investigating how cloud vendors control customer data on cloud servers located in various jurisdictions.
Cloud computing allows users to access software and store data on remote servers over the internet rather than locally on personal devices. It offers benefits like reduced costs, increased collaboration and accessibility of files from anywhere. The document outlines different cloud service models including Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). It also discusses major cloud providers, types of cloud storage, benefits of cloud computing and some challenges regarding data security, availability and regulatory compliance.
Cloud Computing? What is it and its future trends?ziaurrehman4484
About Cloud Computing. How it works? What are its uses, its types? What services it provides and what are its future trends. It was a presentation made by Zia-ur-Rehman, who is a student at National University of Sciences and Technology, Islamabad, Pakistan. It was his research work on the same topic.
1) Cloud computing refers to storing and accessing data and programs over the Internet instead of a computer's hard drive. It allows users and businesses to access files, applications, and computing resources from anywhere.
2) There are three cloud service models - Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS) - which differ in what resources they provide to users.
3) Cloud services can be deployed via private, public, community, or hybrid clouds, which differ in who has access to the cloud and who manages it.
International journal of computer science and innovation vol 2015-n2-paper2sophiabelthome
This document provides an overview of cloud computing, defining it as a model where applications and data are hosted on remote servers that can be accessed from anywhere via the internet. Key points made include:
- Cloud computing allows users to access files and programs from any device with an internet connection.
- Data and applications are stored on servers that make up the "cloud" rather than individual computers.
- Cloud computing offers benefits like collaboration, mobility, and scalability of resources.
Cloud computing has evolved from earlier technologies like grid computing, utility computing, and software as a service (SaaS). It allows users to access computing resources like storage and applications over the internet. Key developments included private network services in the 1990s, the use of "cloud" to signify the space between companies and customers, and Amazon's introduction of web-based retail services in 2002. Technologies like virtualization and service-oriented architecture allow flexible provisioning of resources and enable the scalable, on-demand access that defines modern cloud computing.
Cloud computing has evolved from earlier technologies like grid computing, utility computing, and software-as-a-service. It allows users access to IT resources over the internet on an as-needed basis. Key developments included private network services in the 1990s, the use of "cloud" to signify the processing space between companies and customers, and Amazon's introduction of web-based retail services in 2002. Technologies like virtualization and service-oriented architecture allow cloud computing to efficiently provide flexible, on-demand access to shared computing resources and applications.
This document defines and explains cloud computing. It begins by defining cloud computing as computing done on servers accessed over the internet, with users connecting through a web browser without knowing the physical location of data or programs. It then discusses different types of cloud services and models including SaaS, PaaS, and IaaS. The document outlines key benefits of cloud computing such as scalability, low upfront costs, and reduced maintenance burden. It also provides examples of how consumers and businesses utilize cloud computing applications and services.
Cloud computing is basically storing and accessing data and sharing resources over the internet rather than having local servers or personal device to handle applications.
This document discusses cloud computing, big data, Hadoop, and data analytics. It begins with an introduction to cloud computing, explaining its benefits like scalability, reliability, and low costs. It then covers big data concepts like the 3 Vs (volume, variety, velocity), Hadoop for processing large datasets, and MapReduce as a programming model. The document also discusses data analytics, describing different types like descriptive, diagnostic, predictive, and prescriptive analytics. It emphasizes that insights from analyzing big data are more valuable than raw data. Finally, it concludes that cloud computing can enhance business efficiency by enabling flexible access to computing resources for tasks like big data analytics.
Cloud computing or Cloud hosting has transformed how businesses operate. Despite increased adoption of Cloud hosting and its associated benefits for enterprises, certain facts need to ‘cleared’ amongst Cloud users. Here’s a PPT to clear all your myths.
IRJET- A Scrutiny on Research Analysis of Big Data Analytical Method and Clou...IRJET Journal
This document discusses big data analytical methods, cloud computing, and how they can be combined. It explains that big data involves large amounts of structured, semi-structured, and unstructured data from various sources that requires significant computing resources to analyze. Cloud computing provides a way for big data analytics to be offered as a service and processed efficiently using cloud resources. The integration of big data and cloud computing allows organizations to gain business intelligence from large datasets in a flexible, scalable and cost-effective manner.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Cloud computing provides on-demand access to shared computing resources like networks, servers, storage, applications and services over the internet. It aims to address growing IT needs like increasing server capacity, reducing costs through pay-per-use models, and integrating external web applications. Cloud computing exhibits characteristics of utility computing, virtualization, and elastic scalability. The key service models are Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). Cloud deployment models include private, public, community and hybrid clouds.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Cloud computing is the practice of using remote servers on the Internet to store, manage, and process data rather than local servers or personal computers. It enables users to access computing resources like applications and data storage over the Internet. The main benefits are flexibility, scalability, and pay-per-use pricing. Cloud services can be public, private, or hybrid. Public clouds are owned by third-party providers and sold on-demand. Private clouds are owned and operated within a single organization. Hybrid clouds combine private and public cloud services and resources.
Imagine yourself in the world where the users of the computer of today’s internet world don’t have to run, install or store their application or data on their own computers, imagine the world where every piece of your information or data would reside on the Cloud (Internet).
This document is a seminar report on cloud computing submitted by Vishnuvarunan.T. It provides an introduction to cloud computing, discussing its key characteristics including on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service. It also covers cloud service models such as Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). The document discusses cloud deployment models including private cloud, community cloud, public cloud, and hybrid cloud. It notes some benefits of cloud computing like cost savings and scalability, as well as challenges around security, privacy, lack of standards, and compliance concerns.
This document discusses cloud computing. It begins with an introduction defining cloud computing as allowing users to access virtually unlimited computing resources over the internet. It then discusses the architecture of cloud computing including front-end and back-end components. The main components of a cloud are infrastructure, storage, platform, applications, services, and clients. There are different types of clouds including public clouds, private clouds, and hybrid clouds that use a mix of internal and external providers. Cloud services are divided into infrastructure as a service, platform as a service, and software as a service. The document concludes with some key characteristics of cloud computing such as its cost effectiveness and features like platform and location independence.
Cloud computing is Internet based development and use of computer technology. It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them. Cloud computing is a hot topic all over the world nowadays, through which customers can access information and computer power via a web browser. As the adoption and deployment of cloud computing increase, it is critical to evaluate the performance of cloud environments. Currently, modeling and simulation technology has become a useful and powerful tool in cloud computing research community to deal with these issues. Cloud simulators are required for cloud system testing to decrease the complexity and separate quality concerns. Cloud computing means saving and accessing the data over the internet instead of local storage. In this paper, we have provided a short review on the types, models and architecture of the cloud environment.
A proposal for implementing cloud computing in newspaper companyKingsley Mensah
This proposal recommends implementing cloud computing for a newspaper company's management information system using Microsoft Azure's infrastructure as a service (IaaS) public cloud model. It analyzes cloud computing and virtualization concepts. The strategy is to move backup storage to the cloud, virtualize staff/management PCs for improved security, and implement the Azure cloud to cut costs by 50% compared to current on-premise infrastructure expenses. Virtualizing access through the cloud will strengthen security while taking advantage of Azure's competitive pricing and 30-day free trial.
This document provides a seminar report on cloud computing submitted by Vanama Vamsi Krishna in partial fulfillment of the requirements for a Bachelor of Technology degree. The 3-page report includes an abstract, table of contents, introduction on cloud computing concepts, a brief history of cloud computing, key characteristics of cloud computing including cost, scalability and reliability, components and architecture of cloud computing, types and roles in cloud computing, merits and demerits, and a conclusion. The report provides a high-level overview of cloud computing fundamentals.
This document discusses security issues related to data location in cloud computing. It notes that cloud computing allows on-demand access to computing resources over the internet, but users often do not know where their data is physically stored or which country's laws govern the data. The research aims to develop a model for controlling data resources stored in cloud servers and implementing data manipulation techniques to protect data from unauthorized access across different country servers. The proposed action research methodology involves investigating how cloud vendors control customer data on cloud servers located in various jurisdictions.
Cloud computing allows users to access software and store data on remote servers over the internet rather than locally on personal devices. It offers benefits like reduced costs, increased collaboration and accessibility of files from anywhere. The document outlines different cloud service models including Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). It also discusses major cloud providers, types of cloud storage, benefits of cloud computing and some challenges regarding data security, availability and regulatory compliance.
Cloud Computing? What is it and its future trends?ziaurrehman4484
About Cloud Computing. How it works? What are its uses, its types? What services it provides and what are its future trends. It was a presentation made by Zia-ur-Rehman, who is a student at National University of Sciences and Technology, Islamabad, Pakistan. It was his research work on the same topic.
1) Cloud computing refers to storing and accessing data and programs over the Internet instead of a computer's hard drive. It allows users and businesses to access files, applications, and computing resources from anywhere.
2) There are three cloud service models - Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS) - which differ in what resources they provide to users.
3) Cloud services can be deployed via private, public, community, or hybrid clouds, which differ in who has access to the cloud and who manages it.
International journal of computer science and innovation vol 2015-n2-paper2sophiabelthome
This document provides an overview of cloud computing, defining it as a model where applications and data are hosted on remote servers that can be accessed from anywhere via the internet. Key points made include:
- Cloud computing allows users to access files and programs from any device with an internet connection.
- Data and applications are stored on servers that make up the "cloud" rather than individual computers.
- Cloud computing offers benefits like collaboration, mobility, and scalability of resources.
Cloud computing has evolved from earlier technologies like grid computing, utility computing, and software as a service (SaaS). It allows users to access computing resources like storage and applications over the internet. Key developments included private network services in the 1990s, the use of "cloud" to signify the space between companies and customers, and Amazon's introduction of web-based retail services in 2002. Technologies like virtualization and service-oriented architecture allow flexible provisioning of resources and enable the scalable, on-demand access that defines modern cloud computing.
Cloud computing has evolved from earlier technologies like grid computing, utility computing, and software-as-a-service. It allows users access to IT resources over the internet on an as-needed basis. Key developments included private network services in the 1990s, the use of "cloud" to signify the processing space between companies and customers, and Amazon's introduction of web-based retail services in 2002. Technologies like virtualization and service-oriented architecture allow cloud computing to efficiently provide flexible, on-demand access to shared computing resources and applications.
This document defines and explains cloud computing. It begins by defining cloud computing as computing done on servers accessed over the internet, with users connecting through a web browser without knowing the physical location of data or programs. It then discusses different types of cloud services and models including SaaS, PaaS, and IaaS. The document outlines key benefits of cloud computing such as scalability, low upfront costs, and reduced maintenance burden. It also provides examples of how consumers and businesses utilize cloud computing applications and services.
Cloud computing is basically storing and accessing data and sharing resources over the internet rather than having local servers or personal device to handle applications.
This document discusses cloud computing, big data, Hadoop, and data analytics. It begins with an introduction to cloud computing, explaining its benefits like scalability, reliability, and low costs. It then covers big data concepts like the 3 Vs (volume, variety, velocity), Hadoop for processing large datasets, and MapReduce as a programming model. The document also discusses data analytics, describing different types like descriptive, diagnostic, predictive, and prescriptive analytics. It emphasizes that insights from analyzing big data are more valuable than raw data. Finally, it concludes that cloud computing can enhance business efficiency by enabling flexible access to computing resources for tasks like big data analytics.
Cloud computing or Cloud hosting has transformed how businesses operate. Despite increased adoption of Cloud hosting and its associated benefits for enterprises, certain facts need to ‘cleared’ amongst Cloud users. Here’s a PPT to clear all your myths.
IRJET- A Scrutiny on Research Analysis of Big Data Analytical Method and Clou...IRJET Journal
This document discusses big data analytical methods, cloud computing, and how they can be combined. It explains that big data involves large amounts of structured, semi-structured, and unstructured data from various sources that requires significant computing resources to analyze. Cloud computing provides a way for big data analytics to be offered as a service and processed efficiently using cloud resources. The integration of big data and cloud computing allows organizations to gain business intelligence from large datasets in a flexible, scalable and cost-effective manner.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Big data refers to massive amounts of structured and unstructured data that is difficult to process using traditional databases. It is characterized by volume, variety, velocity, and veracity. Major sources of big data include social media posts, videos uploaded, app downloads, searches, and tweets. Trends in big data include increased use of sensors, tools for non-data scientists, in-memory databases, NoSQL databases, Hadoop, cloud storage, machine learning, and self-service analytics. Big data has applications in banking, media, healthcare, energy, manufacturing, education, and transportation for tasks like fraud detection, personalized experiences, reducing costs, predictive maintenance, measuring teacher effectiveness, and traffic control.
The software development process is complete for computer project analysis, and it is important to the evaluation of the random project. These practice guidelines are for those who manage big-data and big-data analytics projects or are responsible for the use of data analytics solutions. They are also intended for business leaders and program leaders that are responsible for developing agency capability in the area of big data and big data analytics .
For those agencies currently not using big data or big data analytics, this document may assist strategic planners, business teams and data analysts to consider the value of big data to the current and future programs.
This document is also of relevance to those in industry, research and academia who can work as partners with government on big data analytics projects.
Technical APS personnel who manage big data and/or do big data analytics are invited to join the Data Analytics Centre of Excellence Community of Practice to share information of technical aspects of big data and big data analytics, including achieving best practice with modeling and related requirements. To join the community, send an email to the Data Analytics Centre of Excellence
SECURITY ISSUES ASSOCIATED WITH BIG DATA IN CLOUD COMPUTINGIJNSA Journal
In this paper, we discuss security issues for cloud computing, Big data, Map Reduce and Hadoop environment. The main focus is on security issues in cloud computing that are associated with big data. 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. Moreover, cloud computing, big data and its applications, advantages are likely to represent the most promising new frontiers in science.
Security issues associated with big data in cloud computingIJNSA Journal
In this paper, we discuss security issues for cloud
computing, Big data, Map Reduce and Hadoop
environment. The main focus is on security issues i
n cloud computing that are associated with big
data. Big data applications are a great benefit to
organizations, business, companies and many
large scale and small scale industries.We also disc
uss various possible solutions for the issues
in cloud computing security and Hadoop. Cloud compu
ting 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 protecti
ng data, applications and the related
infrastructure with the help of policies, technolog
ies, controls, and big data tools
.
Moreover,
cloud computing, big data and its applications, adv
antages are likely to represent the most
promising new frontiers in science.
Analysis on big data concepts and applicationsIJARIIT
The term, Big Data ‘ h a s been referred as a large amount of data that cannot be handled by traditional database
systems. It consists of large volumes of data which is been generated at a very fast rate, these cannot be handled and processed by
traditional data management tools, so it requires a new set of tools or frameworks to handle these types of data. Big data
works under V’s namely Volume, Velocity, and Variety. Volume refers to the size of the data whereas Velocity refers to the
speed that the data is being generated. Variety refers to different formats of data that is generated. Mostly in today’s world
thee average volumes of unstructured data like audio, video, image, sensor data etc. One can get these types of data through
social media, enterprise data, and Transactional data. Through Big data analytics, one can able to examine large data sets
containing a variety of data types. Primary goals of big data analytics are to help the organizations to take important decisions
by appointing data scientists and other analytics professionals to analyses large volumes of data. Challenges one can face
during large volume of data, especially machine-generated data, is exploding, how fast that data is growing every year, with
new sources of data that are emerging. Through the article, the authors intend to decipher the notions in an intelligible
manner embodying in text several use-cases and illustrations
Introduction to big data – convergences.saranya270513
Big data is high-volume, high-velocity, and high-variety data that is too large for traditional databases to handle. The volume of data is growing exponentially due to more data sources like social media, sensors, and customer transactions. Data now streams in continuously in real-time rather than in batches. Data also comes in more varieties of structured and unstructured formats. Companies use big data to gain deeper insights into customers and optimize business processes like supply chains through predictive analytics.
big data on science of analytics and innovativeness among udergraduate studen...johnmutiso245
This document outlines the members of a group and then provides definitions and background information about big data. It discusses the history of big data, how big data works, the benefits and disadvantages of big data, current applications of big data, and the future of big data. It concludes that big data analysis provides opportunities but also faces challenges regarding data quality, security, skills shortage, and more. References are provided.
big data on science of analytics and innovativeness among udergraduate studen...johnmutiso245
This document outlines the members of a group and then provides definitions and background information about big data. It discusses the history of big data, how big data works, the benefits and disadvantages of big data, current applications of big data, and the future of big data. It concludes that big data analysis provides opportunities but also faces challenges regarding data quality, security, skills shortage, and more. References are provided.
This document discusses challenges and solutions related to big data implementation. Some key challenges mentioned include reluctance to invest in big data strategies, integrating traditional and big data, and finding professionals with both big data and domain skills. The document recommends starting small with proofs of concept and taking an iterative approach to derive early benefits from big data before making larger investments. It also stresses the importance of having an enterprise-wide data strategy and acquiring various skills needed for big data projects.
This document provides an overview and introduction to big data implementation strategies using Hadoop and beyond. It discusses how big data has evolved from technologies pioneered by companies like Google to analyze vast amounts of diverse data cheaper and more effectively than traditional methods. It also outlines some of the key challenges organizations face as data volumes, varieties, and velocities outgrow existing systems, and how new big data technologies like Hadoop provide more cost-effective solutions to process and analyze data at scale. The document notes that big data represents a shift in computing paradigms rather than just data size alone.
Big Data refers to large, complex datasets that traditional data processing applications are unable to handle efficiently. Spark is a fast, general engine for large-scale data processing that supports multiple languages and data sources. Spark uses resilient distributed datasets (RDDs) that operate on data stored in cluster memory for faster performance compared to the disk-based MapReduce model. DataFrames provide a distributed collection of data organized into named columns similar to a relational database, enabling SQL-like queries and optimizations.
This document discusses big data mining. It defines big data as large volumes of structured and unstructured data that are difficult to process using traditional methods due to their size. It describes the characteristics of big data including volume, variety, velocity, variability, and complexity. It also discusses challenges of big data such as data location, volume, hardware resources, and privacy. Popular tools for big data mining include Hadoop, Apache S4, Storm, Apache Mahout, and MOA. Hadoop is an open source software framework that allows distributed processing of large datasets across clusters of computers. Common algorithms for big data mining operate at the model and knowledge levels to discover patterns and correlations across distributed data sources.
This document provides an overview of big data and commonly used methodologies. It defines big data as large volumes of complex data from various sources that is difficult to process using traditional data management tools. The key aspects of big data are volume, variety, and velocity. Hadoop is discussed as a popular framework for processing big data using the MapReduce programming model. HDFS is summarized as a distributed file system used with Hadoop to store and manage large datasets across clusters of computers. Challenges of big data such as storage capacity, processing large and complex datasets, and real-time analytics are also mentioned.
Lecture given at the University of Catania on December 2nd, 2014.
Start from Big Data definitions, continue with real life examples of successful Big Data Projects, go a little bit deeper with Sentiment Analysis, and conclude with a brief overview of Big Data tools and Big Data with Microsoft.
Summary:
1. What is Big Data? (includes the 5Vs of Big Data)
2. Big Data Examples (includes 6 Real Life Examples and comments on Privacy concerns)
3. How to Tackle a Big Data Problem (my 4 Universal Steps to follow)
4. Sentiment Analysis (what is sentiment analysis? Why do we care? A Technique and a plan)
5. Big Data tools (Hadoop, Hadoop Ecosystem, Hive, Pig, Sqoop, Oozie; Azure HDInsight, Excel Power Query, Power Pivot, Power View, Power Map)
Big data is a broad term for data sets so large or complex that tr.docxhartrobert670
Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. The term often refers simply to the use of predictive analytics or other certain advanced methods to extract value from data, and seldom to a particular size of data set.
Analysis of data sets can find new correlations, to "spot business trends, prevent diseases, combat crime and so on."[1] Scientists, practitioners of media and advertising and governments alike regularly meet difficulties with large data sets in areas including Internet search, finance and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics,[2]connectomics, complex physics simulations,[3] and biological and environmental research.[4]
Data sets grow in size in part because they are increasingly being gathered by cheap and numerous information-sensing mobile devices, aerial (remote sensing), software logs, cameras, microphones, radio-frequency identification (RFID) readers, and wireless sensor networks.[5]
HYPERLINK "http://en.wikipedia.org/wiki/Big_data" \l "cite_note-6" [6]
HYPERLINK "http://en.wikipedia.org/wiki/Big_data" \l "cite_note-7" [7] The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s;[8] as of 2012, every day 2.5 exabytes (2.5×1018) of data were created;[9] The challenge for large enterprises is determining who should own big data initiatives that straddle the entire organization.[10]
Work with big data is necessarily uncommon; most analysis is of "PC size" data, on a desktop PC or notebook[11] that can handle the available data set.
Relational database management systems and desktop statistics and visualization packages often have difficulty handling big data. The work instead requires "massively parallel software running on tens, hundreds, or even thousands of servers".[12] What is considered "big data" varies depending on the capabilities of the users and their tools, and expanding capabilities make Big Data a moving target. Thus, what is considered to be "Big" in one year will become ordinary in later years. "For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration."[13]
Contents
· 1 Definition
· 2 Characteristics
· 3 Architecture
· 4 Technologies
· 5 Applications
· 5.1 Government
· 5.1.1 United States of America
· 5.1.2 India
· 5.1.3 United Kingdom
· 5.2 International development
· 5.3 Manufacturing
· 5.3.1 Cyber-Physical Models
· 5.4 Media
· 5.4.1 Internet of Things (IoT)
· 5.4.2 Technology
· 5.5 Private sector
· 5.5.1 Retail
· 5.5.2 Retail Banking
· 5.5.3 Real Estate
· 5.6 Science
· 5.6.1 Science and Resear ...
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INN530 - Assignment 2, Big data and cloud computing for management
1. Big data and cloud computing for
management
By
Simen Fivelstad Smaaberg (n8661260)
2. Abstract
Big data
What is it?
What possibilities and challenges lays within?
Cloud computing
Software as a Service
Platform as a Service
Infrastructure as a Service
How does big data relate to cloud computing?
Google / Facebook
How does Google and Facebook handle big data?
What big data/cloud services do they offer for others to
use?
3. Background
Internet today: a social web
Huge amounts of data are created by users daily
Creates your digital footprint
Need for methods to handle all these data
The data is used for analysis purposes
Improve customer experiences
Increase revenues
4. Big Data
The vast volume of data in existence (Arthur, E
2013)
Tweets, likes, videos, images, comments and so on
Group of collected information, spans 3 V’s of data
management (Gartner 2011)
Figure 1: Big data 3V’s ( Datameer 2013)
5. Volume
Big data is Big
Exists in one size: large
Challenges
Physical storage space
Logical structuring
Scaling
6. Volume
Big data is Big
Exists in one size: large
Challenges
Physical storage space
Logical structuring
Scaling
Opportunities
Finding trends, patterns and relationships between data
Possibilities for in depth analysis
8. Variety
Challenges
Infrastructure to handle
different kinds of media is
required.
Challenging for
engineers
Opportunities
Finding patterns and
relationships between
different types of data
Figure 2: Big Data (Orange 2011)
9. Velocity
Big data can have different kinds of time-sensitivity
Real time vs non real time
Challenges
Infrastructure that can handle different kinds of time-
sensitivity
10. Velocity
Big data can have different kinds of time-sensitivity
Real time vs non real time
Challenges
Infrastructure that can handle different kinds of time-
sensitivity
Opportunities
Combine slow moving data with fast moving time
constrained data to give the user a better user experience
11. Big data success story: Santam Insurance
About
South Africas largest short-term insurance company
Problem
6-10% of premium revenue were fraud
Solution
Big Data prediction analysis
12. Big data success story: Santam Insurance
About
South Africas largest short-term insurance company
Problem
6-10% of premium revenue were fraud
Solution
Big Data prediction analysis
Result
First four months: 1.98 million USD saved
First three years: ROI of 244%
Insurance fraud syndicate disceovered
13. « Big data has the potential to change the way
governments, organizations, and academic
institutions conduct business and make
discoveries, and its likely to change how everyone
lives their day-to-day lives »
– Susan Hauser, VP Microsoft Enterprise and partner
group (Microsoft Enterprise team 2013)
14. Cloud computing
Running applications elsewhere and accessing them through your
computer
You get an “infinite” amount of storage space and computing power
You pay for what you use
Figure 3: Cloud computing
15. Big Data and Cloud Computing
Big data requires enormous amounts of storage
space
Costly to build and maintain
Huge engineering challenges
16. Big Data and Cloud Computing
Big data requires enormous amounts of storage
space
Costly to build and maintain
Huge engineering challenges
Solution: Cloud Computing!
Put your data and programs into “the cloud”
Avoid the hardware problem of big data
Pay for the computing power you actually use,
Opens up for smaller companies stepping into big data analysis
17. Big Data and Cloud Computing
Big data requires enormous amounts of storage
space
Costly to build and maintain
Huge engineering challenges
Solution: Cloud Computing!
Put your data and programs into “the cloud”
Avoid the hardware problem of big data
Pay for the computing power you actually use,
Opens up for smaller companies stepping into big data analysis
Issues: Privacy and trust
You put your data into someone else's hand
Is that someone trustworthy?
18. Google and Hadoop
2004: Google revolutionized the field of Big Data
and Cloud Computing
Released papers describing how they handled these
topics
19. Google and Hadoop
2004: Google revolutionized the field of Big Data
and Cloud Computing
Released papers describing how they handled these
topics
From this Yahoo spawned Hadoop
Platform that can process and analyse huge amounts of
data on interconnected commodity servers
Great fit for cloud computing
Data is spread out and duplicated across servers
Data is analysed in parallel through MapReduce
Backbone of Twitter, Facebook, Yahoo and eBay
20. Google
Huge competitor in the field of big data and cloud
computing
Big data used internally
Index searches
Provide email services
Provide advertizing
External Big data and cloud services
Software as a Service: Google docs, Gmail etc
Platform as a Service: Google app engine
Infrastructure as a Service: Google compute engine
Gives developers access to the same infrastructure google itself
is run on
21. Facebook
Forerunner in the field of Big Data
Handling massive amounts of data daily
2.5 billion status updates, wall posts, photos, videos and
comments
2.7 billion likes
300 million uploaded photos
500 Tb new integrated data every day (2012)
22. Facebook
Forerunner in the field of Big Data
Handling massive amounts of data daily
2.5 billion status updates, wall posts, photos, videos and
comments
2.7 billion likes
300 million uploaded photos
500 Tb new integrated data every day (2012)
Facebook is run on top of Hadoop
100 Petabytes of storage
Underpins analysis and everyday services
New data is put into one of their Hadoop clusters physically
residing in one of their data centers
Data is analysed when needed or at specific intervals
(hourly/daily) through MapReduce
23. Facebook Insight
Tool that provides page owners (both facebook pages and
ordinary web pages) with metrics about their content.
(Facebook 2013)
Number of visits
Facebook referrals
Visitor demographics (age, gender, location, language)
Connects Facebook’s big data with users visiting your page to
provide metrics that can be used to improve your business’s
online performance
Generated through Facebook’s Hadoop cluster
Figure 4: User demographics (Campalyst 2012)
24. Facebook graph search
Search engine for your social circle (Bea, F 2013)
Allows for search on relationships between
people, likes, comments, photos etc.
Possible because of
Facebook’s big data
Privacy concerns
Figure 5: Facebook restaurant search Figure 6: Facebook TV show search
25. The Future
Big data and cloud computing is in constant change
More and more usage areas are found
Medical diagnostics
Weather forecasts
Particle physics
Fraud prevention and detection
Etc.
Prediction: We have barely seen the start of its
dominance
26. References
Arthur, E. 2013. "Big Data“. Alaska Business Monthly, vol. 29, no. 1, pp. 72-72. Retrieved from
http://search.proquest.com.ezp01.library.qut.edu.au/docview/1271622055
Gartner. 2011. “Solving Big Data Challenge involves more than just managing volumes of data”.
Accessed June 4, 2013. http://www.gartner.com/newsroom/id/1731916
Strickland, J. “How Cloud Computing Works”. Accessed June 6, 2013.
http://computer.howstuffworks.com/cloud-computing/cloud-computing.htm
Gartner. “Software as a Service (SaaS)”. Accessed June 6. 2013. http://www.gartner.com/it-
glossary/software-as-a-service-saas/
Chong, R. 2011. “The perfect marriage: Hadoop and Cloud”. Accessed June 4, 2013.
http://thoughtsoncloud.com/index.php/2011/10/the-perfect-marriage-hadoop-and-cloud/
Microsoft Enterprise Team. “The Big Bang: How the Big Data Explosion Is Changing the
World”. Last Modified March 27, 2013.
http://www.microsoft.com/enterprise/it-trends/big-data/articles/The-Big-Bang-How-the-Big-Data-
Explosion-Is-Changing-the-World.aspx#fbid=8RIFw1BLCG2
Metz, C. 2011. “How Yahoo Spawner Hadoop, the Future of Big Data”. Accessed June 5, 2013.
http://www.wired.com/wiredenterprise/2011/10/how-yahoo-spawned-hadoop/all/1
Big Data Insights. 2013. “How Facebook uses Hadoop and Hive”. Accessed June 05, 2013.
http://hortonworks.com/blog/how-facebook-uses-hadoop-and-hive/
Facebook. “Insights”. Last modified May 30, 2013.
https://developers.facebook.com/docs/insights/
Bea, F. 2013. “How Facebook’s Graph Search Works…Sort Of". Accessed June 05, 2013.
http://www.digitaltrends.com/social-media/how-facebook-graph-search-works/
IBM. 2013. “IBM Business Analytics SPSS: Santam insurance”. Last modified May 28, 2013.
http://www-01.ibm.com/software/success/cssdb.nsf/CS/SANS-
985HX2?OpenDocument&Site=default&cty=en_us
27. References - Illustrations
Datameer. 2013. “What is Big Data?”. Digital
Image. Viewed June 8, 2013.
http://www.datameer.com/product/big-data.html
Orange. 2011. “Analyst insight”. Digital Image.
Viewed June 11, 2013. http://www.orange-
business.com/en/magazine/analyst-insight-
december-2011
Campalyst. 2012. “How to measure website visitors’
demographics: hidden Facebook Insights gem”.
Digital Image. Viewed June 11, 2013.
http://blog.campalyst.com/2012/10/10/how-to-
measure-website-visitors-demographics-hidden-
facebook-insights-gem/