Research about Database technology and Mobile computing (OS, Tools, Apps)
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Contents Abstract 3 1.0 Introduction 4 1.1 Topic and Its significance 4 1.2 Drivers for Big Data in Cloud Adoption 5 1.3 Need for Present Research 6 2.0 Literature Review 7 2.1 Big Data Concept 7 2.2 Cloud Computing Concept 8 3.0 Discussion 10 3.1 Advantages 10 3.2 Disadvantages and Issue 12 4.0 Conclusion and Implications 14 5.0 References 15
Abstract
Big Data are growing into national and international contest for scientific advancements and application advances. Big Data are generated on a daily basis from the Earth observations, in-situ sensors, social networks, scientific research, model simulations, application analyses, and many different ways. The data are big and multifaceted in that they aren’t well constituted and that many relationships among various data are buried by either the volume of data or the way data are gathered, modeled, or directed. So as to generate exceptional information that can be managed from the Big Data, modernistic computing and examinations methods are required to manage, access, discover, and process the Big Data for instinctive decision support of scientific exploration, application set-ups, and individual living.
The evolving of Cloud Computing as a new generation of computing structure provides possible computing solutions to the discovery, access, management, and processing of the Big Data for instinctive decision support knowledge. These Cloud Computing and Big Data share comparable intrinsic features, for example distribution, space-time, parallelization, and being geographically dispersed. Exploiting these intrinsic aspects would help offer Cloud Computing answers for Big Data with high computing infrastructure proficiency to process and obtain exceptional information. Simultaneously, Big Data pose substantial challenges as prospects to advance the Cloud Computing. In the geospatial information science (GIS) domain, many scientists performed active research to deal with urban, social, environment, population, climate, and other problems related to Big Data by means of Cloud Computing. This distinctive issue of Computers, Environment, and Urban Systems (CEUS) is among one of the first efforts to acquire the latest developments in this direction and attempt to develop a preliminary research agenda for the field of research.
1.0 Introduction
1.1 Topic and Its significance
Big data and cloud computing are suitable approaches for store, examine, handle, describe and access the information. Services are provided by cloud computing like platform, application and infrastructure that will be accessible through internet instead of desktop. In addition, cloud computing can allow the data to be accessed and shared and retrieved from desktop, mobile devices, automobile and vending machine. In addition, cloud computing have stagger, price, and accessibility that created new abilities that did not exist before. These abilities include organization-centric uses of information where data of the customer can be accumulated to support organization requirements and in the immediate future, customer-centric usages where data and smart products accumulation can be used to authorize individuals to make acquisitions to their precise needs without turning to intermediaries (Catlett, 2013). In addition, the tactics of marketing in the past was persuasion advertisements to customer, so big data and cloud computing techniques will help salespersons to convince the customers to buy anything and make a lot of profit from those customers. The term of big data is growing fast these days and can be applied more these days; also it is available to users more than before. From many articles I have read about big data we can describe big data as a tool, methods, process and procedures that allow the organization to manage, maintain, and manipulate the huge data and store it. In addition, big data function can be managed locally as a base of establishing to cloud computing, so there will be a corporate data.
1.2 Drivers for Big Data in Cloud Adoption
Cost reduction: Cost reeducation is very important thing to be consider, so we need to find ways in cloud computing that support dig data technologies, after some research we found that cloud computing is offering a cost-effective method and ways to help support big data technologies , also it is support the advanced analytics applications , both of these thing will drive business value .To support tools that process the high velocity, large volume ,and numerous formats of big data , we need something called clusters of servers , it is required in big data environment to do these things. So the organizations should take on consideration that the cloud computing is the structure to keep the costs low.
Reduce overhead: To implement solutions for big data we need to have different components and good integration (Weinman, 2012).so to have less complexity and to reduce it, and to improve productivity for the team you are working with, you need a cloud computing with the component that can be automated.
Rapid provisioning/time to market: Supplying some servers in cloud it is become really simple it is like buying something on the net. Process requirement can play a really important role of controlling the scale of big data environment up or down .The value of data is very important, so to keep value for the data you need to do faster supplying for big data applications because the value of the data is going to reduce quickly over time.
Flexibility/scalability: To do analysis for a big data, you need a really big compute power just for a little amount of time. In this situation of analysis the servers should be available in minutes. To achieve this level of flexibility and scalability cloud would be the best thing to use, instead of use the large computers.
1.3 Need for Present Research
We need to do a lot of research about big data and cloud computing because of four things:
1. The huge amount of data that is produced every day.
2. The way and methods to manage and manipulate this data.
3. The relationship between big data and cloud computing, we need to understand that through a lot of research.
4. How to have more analysis expert and scientist to understand working with the huge amount of data.
Because of these things we need to do a present researches and studies regarding big data and cloud computing technology.
2.0 Literature Review
2.1 Big Data Concept
Big data is a developing term that defines any voluminous quantity of organized, semi-organized and unstructured data that has the capacity to be mined for info. Although big-data doesn't refer to any precise quantity, the term is often applied when speaking about petabytes and Exabyte of data.
We can describe big data in three versions, the great volume, data and velocity of extensive different types in which data must be processed.
For analysis the regular personal database, big data is consuming a lot of time and costs a huge amount of money. We need to depend in less on quality of the data and the schema of the data, so there are a new methods for storing and examining data had developed to do this job. (Chorafas, 2011).As an alternative, lengthy metadata with raw data is accumulated in three things, machine learning, and data lake and (AI) programs , are exploit a complicated algorithms to find the most repeated array.
Analyzing big data is linked to cloud computing, for examining the large set of data in real-time we need platform or an environment like Hadoop for accumulate a large sets of data, through map reduce for manage , disseminated cluster , process and unite data that come from several source.
Even though analytics of big data become more and high demand than before, now there is not enough analysts and experts who have a good understanding of dealing with big data in open source environment and in a disseminated. In the initiative, vendors are creating more of Hadoop appliances to response and face the shortage of not enough experts or analysts, by doing this it is helping companies to get more benefit of semi-organized and unorganized of data they own.
We can differentiated big data form little amount of data or (small data) to another promote term that can be used to point to some data whose format and amount can be straightforwardly used for analytics. There is a regularly saying "small data is for people, big data is for machines".
2.2 Cloud Computing Concept
To run many consistent realistic servers on static physical machine you need engaged and connect visualization of source of computing. Economies of scale play a major role to achieve cloud suppliers which will provide license with very low prices and do charging based on time periods like hourly.
We need an option that is flexible and very accessible for computing requirement, best thing is to use normalization. To get and to ensure the accessibility you need two things, interchangeability, and invite area of replacements. This effect needs and design decision to manage with case of failure with rhythm (Weinman, 2012).
The consequences for an IT project or organization using cloud computing are substantial and change the old-fashioned approach to planning and exploitation of resources. Firstly, resource scheduling becomes less important. It is necessary for costing scenarios to ascertain the viability of a project or product. Nevertheless, deploying and eliminating resources routinely based on demand requires to be focused on to be fruitful. Vertical and horizontal scaling turn out to be viable once a resource becomes easily utilized.
To replace a single small computing resource with a perfect huge one for make the demand high, we need something to defines and give the ability to do this replacement which is the horizontal scaling which control this thing. Cloud computing can support this by allowing numerous resource types to be accessible to do switching between them. It also expand in the opposite direction, for example, to switch to a cheaper and smaller request if the demand is drops. In addition, two things are blocking implementation and decision making which are capital expense and cost being sunk, since the cloud resources are paid on a usage (Chorafas, 2011).
3.0 Discussion
3.1 Advantages
It is clear that significant data is used in business structures in many ways; big data gives businesses access to more data than ever before. The previously unstructured data that would have been previously considered dead with no value is analyzed big data in order to benefit the organization; many organizations are using the power of insights that is provided by big data to establish a variety of activities in the business. Among them include determining who did what, where and when. These moves have been made possible due to the use of the said of big data in organizational management. Big data enable timely insights from the vast amount of data that includes those already stored in company databases, the internet, social media, from external third party sources and remote sensors. This helps in business decision making since the organization has the required information vital for decision-making. Big data provides the ability for real-time monitoring and forecasting of events that impact either business performance or operation (Mayer, &Cukier, 2013). This is done by analyzing the information flow that enables the business in making the right accurate prediction of the business future.
The usage of big data gives the organizations using it the ability to find, extract, acquire, manipulate, connect, analyze and visualize data with the tools of choice, such as SAPHANA, SAP Sybase and SAP intelligence analysis for public sector application. Information is considered as the greatest asset and weapon that organizations use to survive in a given market structure. Therefore, information helps the organization to remain relevant in a given area.
Big data allow businesses to identify most significant information that can improve the decision quality. Information is ever significant in decision-making process this is because such information can help the decision makers have the required information vital for informed decision-making. With such big data, information managers are confident in making organization choices. Additionally, big data enable marketing strategies to be improved and more accurately target. This increases the customer base and then pushes the organization ahead of the competition (Mohantyet, al., 2013). Big data also provide the management in mitigating the risk by optimizing the complex decisions of any unplanned events that may arise in the organizational structure.
Universally there are four models of cloud computing technology include the network as a service (Naas), the software as a service (Saas), Platform as a service and (Paas) and infrastructure as a service (Iaas). All the four models offer biggest advantages of cloud computing technology where the advantage goes to the end users and all businesses of all sizes from small enterprises to bid corporations (Shroff, 2010). The most pronounced advantage is that the burden has been lifted since the organization does not need to support the infrastructure or have the skills that are required to develop and maintain or develop the infrastructure.
Cloud computing technology is cost effective in that it eliminates the investment in stand-alone software or servers. Companies are able to save on licensing fees and also eliminate overhead charges such as the cost of data storage, management and software updates. Additionally, cloud computing technology is available in the market with cheaper rates that the traditional computing methods. This helps in lowering all the overall IT expenses (Marks, & Lozano, 2010). Connectivity, convenient and scalable model have emerged where people are able to pay as a pay as you go or a onetime pay making the technology more convenient.
Cloud computing technology is convenience and also offers a continuous service which is available any place where the end user might be located. Easy access is promoted to information and accommodates the needs of users in different geographical locations and time zone. People can view and modify shared documents and files since service uptime in most cases is guaranteed where it provides a continuous availability of resources (Shroff, 2010). Cloud computing technology sellers use multiple services for maximum prevention of redundancy where in case there is a system failure, then the alternatives with switches to other machines.
Backup and recovery using cloud computing are simplified since various cloud providers are able to provide reliable and flexible backup/recovery solutions. Cloud is also environmentally friendly in that it takes fewer resources to compute thus saving allot of energy. A cloud technology has an easy integration and a quick deployment which can be up and running in a short time. Additionally, new user introduction to the system happens almost instantaneously thereby eliminating waiting periods. Other advantages include location independence and increased storage capacity.
3.2 Disadvantages and Issue
Bid data may come with un-relevant information about the business this data leads to wastage of time and business resources that could have been used in other projects. Information collected may also be misleading to the business such information may cause failure in the businessfor such misleading information will be used in decision-making. Decisions made based on irrelevant information causes the business to undergo failure and the total decline such organization may experience loss in its revenue generation owing to the irrelevant data from big data. Bid data require skilled and trained personnel to analyze the data, for such people analyze the data they will require more and sophisticated infrastructure. The more the data collected,the more sophisticated the infrastructure needed the additional cost hence. The cost of analyzing big data may be more than the benefits achieved from the information this makes the process to be an economical drain to the business (Ohlhorst, 2013). Some business can have the information
analyzed interpreted and presented to them in the best way possible; however, some organizations do not implement such information for the better of the organization.
Privacy and security in the cloud are threatened since a company gives away private data and information. The things that might be sensitive and confidential are left in the open for public consumption. The cloud service provider, then manages, retain and then protect thus the provider’s reliability is very critical. A company in existence is put in jeopardy and risked, it is important to explore all the alternatives before making an ultimate decision (Shroff, 2010). Cloud vendors should assure their clients that they will protect their data from any unauthorized users. The using company has no control over the processes and functions and the execution of the hardware and software since the servers run on a remote.
Cloud computing technology has an increased vulnerability, this is because cloud based solution is exposed to the general public making them vulnerable and easy target to malicious users and hackers. The buying or subscribing company virtually depends on the provider otherwise called vendor lock-in (Marks, & Lozano, 2010). This is mainly due to the impossibility to move from a vendor to the other owing to the huge data that will be required to be transferred from a vendor to the other.
4.0 Conclusion and Implications
Bid data is a convenient way of using and analyzing large amount of data this is due to the advantages that comes with its usage. However, it is advisable to look for new ways of dealing with such large amount of information. Cloud technology is still underdeveloped, nevertheless it is one of the best and strongest ways with a great potential for future use. User base grows constantly where bigger players are attracted to it which makes it to offer better and fine tuned services and computing solutions to its client. With time the disadvantages should be eliminated.
5.0 References
Benefits and Drawbacks of Cloud-Based versus Traditional ERP Systems. (n.d.). Retrieved February 10, 2015, from http://www.academia.edu/2777755/Benefits_and_Drawbacks_of_Cloud-Based_versus_Traditional_ERP_Systems
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Big Data Cloud Computing & Cloud Database | Qubole. (2014, January 13). Retrieved February 10, 2015, from http://www.qubole.com/resources/articles/big-data-cloud-database-computing/
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Big-data in cloud computing: A taxonomy of risks. (n.d.). Retrieved February 10, 2015, from http://www.informationr.net/ir/18-1/paper571.html#.VNnKI_mUdLE
Catlett, C. (2013). Cloud computing and big data. Amsterdam: IOS Press.
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Chorafas, D. (2011). Cloud computing strategies. Boca Raton, Fla.: CRC Press.
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Weinman, J. (2012). Cloudonomics: The business value of cloud computing. Hoboken, N.J.: Wiley.
Mayer-Schönberger, V., &Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. Boston: Houghton Mifflin Harcourt.
Mohanty, S., Jagadeesh, M., &Srivatsa, H. (2013). Big data imperatives: Enterprise big data warehouse, BI implementations and analytics.
Ohlhorst, F. (2013). Big data analytics: Turning big data into big money. Hoboken, N.J: John Wiley & Sons.
Shroff, G. (2010). Enterprise cloud computing: Technology, architecture, applications. Cambridge: Cambridge University Press.