History and Background
Whenever a new technology arrives on the Information Technology field, it is not always clear about the implications of that particular technology. Although in some scenario, it offers savings to the cost and improves the operation services or handles business related problems for getting some advantage strategically (Rittinghouse and Ransome 2016). In 2011, Apple Computers entered the cloud computing market with the launch of Apple iCloud. Apple’s mobile services iPhone moved to cloud for all the applications that apple provide. With the launch of iCloud apple fully migrated to cloud computing and started providing all the services through cloud. It required all the users to synchronise their data that are of any kind from music to photos, videos and application data all needed to be in synchronised manner (De Mauro, A., Greco, M. and Grimaldi 2015). In comparison to traditional database system where data were stored in a compact way and the size of the data were also very less, but now after the web becoming popular for transferring other type of data like images, audio and video or application services. There the need for handling such huge sized data evolved thus the big data appeared. On the other hand, raw data from users are also kept from user’s activity on the web that is not consumable. However, analysing those data will result into understand the interests of a user. These are the very common usages of Big Data and cloud computing, there are many other advantages that these technologies provide which sparked a renaissance in the field of Information Technology.
Background and Definitions for Cloud Computing
The basic concept that we get about Cloud Computing is that it evolved in the 21st century. That is not the truth. At the very early period in computing around 1950, multiple users were capable of accessing a centralised system using weak terminals that provided access to the mainframe computer. Later in 1970, the concept of virtual machine evolved, that made it possible to execute more than one operating system simultaneously in an isolated environment, which took the centralised mainframe computing to another level. Earlier telecommunication companies offered point-to-point dedicated channels for each service provided (Sultan 2014). After that, the idea of cloud computing came into the frame, instead to building each dedicated channel for providing different services they worked on virtualized private network on the existing physical infrastructure which also reduced the cost along with that it made it possible to offer different distinct services over the same telecommunication channel. The beginning of 21st century saw rapid growth in the digital world, where the different type of organisations or fields embraced digitisation to ease the business processes and monitor processes in an integrated manner, which required each of the organisations to purchase hardware and software individually according to their required operations. The system costs much more because of its high-end processing power and the maintaining costs are also very high (Jeffery et al. 2017). Thus, it was not feasible for small organisations to own those systems. Therefore, tech giants like Amazon, Google, Microsoft and others came into the market with their concept of providing the high-end processing service to the clients without having to develop the whole system in-house. They made it possible by implementing system architecture where they put lots of processing units in their warehouses to process hard to hard or large to massive data within few moments. Using those resources, they started proving the processing services over the internet or the same dedicated channel to the clients with taking just a nominal fee from them (Chen, Mao and Liu 2014). In this system structure, the clients no more required to purchase the high-end system. Instead, the cloud service provider provides the client with an interface where the client manages all their tasks on the portal, and the processes are done in the background in the service providers’ machine. That is information sent from client’s end to the service provider’s end, and there it processes and stores all the information or data and the results of the computation. In this system architecture, not much system resources from the client’s end required except the business data. Cloud computation evolved in many phases throughout the history of Information Technology. The first technology that evolved was Grid computing that solved large problems with parallel computing (Kumar and Lu 2010). After a while, Utility Computing evolved that offered computing resources as a metered service. Soon after SaaS or Software as a Service technology evolved that provided network based subscription to the applications and finally, the time for Cloud Computing began where it made possible for the client to fully outsource all the processes and access those platform from anywhere and anytime.
Background and Definitions for Cloud Computing
A long time before the evolution of computers, the idea of expanding knowledge for academia was popular. Although it is easy to forget, human’s ability to store and analyse information made an evolution (Ward and Barker 2013). After the digital invention, it became much easier for the people to store information without taking the traditional pen and paper method. However, from the past two centuries along with the technological advancement vast information like official reports or the statistics of a nation or other massive organisational reports, the business reports became essential to be stored for the reason of future use, references, citation or analysis purpose and commercial use. Nevertheless, after the technological boom, the information or data also faced thousand times more boost, and the expansion of the web resulted in the existence of 12000 petabytes of data with the commencement of the Web 2.0. The difference that it created is that it is the user-generated web where the user rather than the service provider will provide the majority of content (Jagadish et al. 2014). Integrating traditional HTML web pages with back end tools like SQL millions of people are using Facebook to upload and share their data with friends. Also, the creation of Hadoop – an open source framework created specifically for storing and analysing big data sets. Its flexibility makes it particularly useful for managing unstructured data like video, audio and raw text that are increasingly generating and collecting. The rise of mobile devices allowed more people to access the digital data directly without using a computer. Along with the most important part of the digital revolution, Big Data is all about capturing and using data that will bring change to the way on which businesses run.
A mobile application development platform (MADP) is a sort of programming that enables a business to assemble, test quickly and maybe convey versatile requests for cell phone or tablets (Sultan 2014). These development platforms help to create Mobile Application Platform or Mobile Digital Platform that enables a business to operate, monitor and provide services to the customers using that particular mobile application. It is developed for the customers to have access while they are on the go.
A business can either manufacture its portable application advancement stage or get one of some outside items accessible available. The MADPs that outsider merchants offer frequently incorporate elements, for example, mobile Backend as a Service (BaaS) and administration apparatuses for application programming interfaces (APIs). An MADP may likewise give local, Web and half-and-half application advancement abilities and also mobile application management (MAM) instruments for conveying and securing applications. The term MADP is, for the most part, credited to the examination firm, Gartner (Pulier et al. 2015). It appears to have supplanted two different terms presented by Gartner, Mobile Enterprise Application Platform (MEAP) and Mobile Consumer Application Platform (MCAP).
Evaluation of Challenges and Benefits of Cloud Computing
Cloud Computing comes with some benefits that are essential for the clients, that is why customers are turning towards cloud. Some of the key advantages of cloud computing are –
- Ease of deployment and Management
- More flexibility in supporting evolving business needs
- Lower cost of operations
- Easier way to scale and ensure availability and performance
- Overall ease of use
Background and Definitions for Big Data
While all of these are the benefits of cloud, there are still many ye to get on to the train of cloud computing (Sadiku, Musa and Momoh 2014). There some also challenges that it faces. Some of them are –
- Security and Privacy – The top most concern about cloud computing is its security. It introduces another level of risk because essential services are often outsourced to a third party, making it harder to maintain data integrity and privacy, support data and service availability, and demonstrate compliance.
- Real Benefits/ Business Outcome – In spite of the fact that its contextual analyses exhibit the advantages that emerge after usage of the cloud innovation, a portion of the customers is never persuaded of the conceivable benefits. The arrival of speculation on the cloud should be substantiated by contrasting particular measurements of general IT and Cloud Computing arrangements that can indicate investment funds that show cost, time, quality, consistence, and income and productivity change.
- Service Quality – Service Quality is one of the greatest elements that ventures refer to as range on for not moving their business application to the cloud. They feel that the SLAs given by the cloud suppliers today are not adequate to ensure the necessities for running a creation application on cloud extraordinarily identified with the accessibility, execution and versatility. Without Proper administration quality, certification undertakings are not going to have their basic business foundation in the cloud.
- Integration – Numerous applications have complex combination needs to interface with other cloud applications. There is a need to connect the cloud application with the rest of the enterprise in a simple, quick and cost effective way.
As the volume of information keeps on developing, its potential for business is by all accounts developing exponentially as Big Data administration arrangements advance enabling organizations to transform crude information into important patterns, forecasts, and projections with remarkable precision –
- Identifying the root causes of failures and issues in real time
- Fully understanding the potential of data-driven marketing
- Generating customer offers based on their buying habits
- Improving customer engagementand increasing customer loyalty
- Revaluating risk portfolios quickly
- Personalizing the customer experience
- Adding value to online and offline customer interactions
Along with the benefits, there are also challenges that the Big Data technology faces (Hashem et al. 2015). Some of them are –
- Volume – lots of data (which is labelled as “Tonnabytes”, to suggest that the actual numerical scale at which the data volume becomes challenging in a particular setting is domain-specific, but we all agree that we are now dealing with a “tonne of bytes”).
- Variety – complexity, thousands or more features per data item, the curse of dimensionality, combinatorial explosion, many data types, and many data formats.
- Velocity – the high rate of information and data streaming into and out of our frameworks, ongoing, approaching (Azadnia, Saman and Wong 2015).
- Veracity – crucial and adequate information to test a broad range of speculations, tremendous preparing tests for vibrant small-scale show building and model approval, miniaturised scale grained “truth” about each question in one’s information accumulation, along these lines engaging “entire populace investigation.”
- Validity – data quality, governance, master data management (MDM) on massive, diverse, distributed, heterogeneous, “unclean” data collections.
- Value – the all-important V, characterising the business value, ROI, and potential of big data to transform one organisation from top to bottom (including the bottom line).
- Variability – dynamic, evolving, spatiotemporal data, time series, seasonal, and any other type of non-static behaviour in one’s data sources, customers, objects of study, etc.
- Venue – Distributed heterogeneous data from multiple platforms, from different owners’ systems, with different access and formatting requirements, private vs. public cloud.
- Vocabulary – schema, data models, semantics, ontologies, taxonomies, and other content- and context-based metadata that describe the data’s structure, syntax, content, and provenance.
- Vagueness – disarray over the significance of enormous information (Is it Hadoop? Is it something that we have had? What is new about it? What are the devices? Which devices would it be a good idea for me to utilise? And so forth.)
With the approach of cell phones, versatile applications are offering like hot cakes. There are various portable stages, which provide a significant number of users for the clients. In such a situation, a mobile application improvement organisation assumes a huge part. These application advancement organisations plan applications according to the necessities and the request of the market (Sultan 2014). These application development organisations likewise need to confront a great arrangement of difficulties while building up an application. It is merely in the wake of conquering these challenges that a request ends up plainly productive and across the board.
Making detectable applications: this must be the greatest test for any application engineer. Building an application that gets saw by the cell phone clients is a major test in itself. The designer needs to concentrate on everything from UI to configuration to illustrations to get the best application encounter for the clients. For building up an application that is both prominent and of real benchmarks, the designer needs to answer many inquiries like which is the objective gathering of clients?; what is the point and what ought to be the capacity, and so on.
The application ought to be good with numerous gadgets: outlining a request for an individual device can be the most exceedingly awful thought in this age where the decisions for brilliant devices are boundless. The application ought to be dynamic and responsive, that implies that the application ought to be perfect with various gadgets and ought to have the capacity to acclimate to different screen sizes.
The application ought to be intelligent: outlining an intuitive application is additionally one of the difficulties of the application improvement process. The application that does not have an intuitive UI will undoubtedly bomb in the market. The designers should go for an exhaustive application advancement process (Pulier et al. 2015). Figuring out how to deal with the application ought to be straightforward and easy to use. It ought not to be incredibly tedious as well.
The application ought to be straightforward and simple to utilise: the application ought to be created in a simple to employ and basic way. The application ought to be available to each client who wishes to have it introduced. Initiating a short instructional exercise on the best way to utilise the app would be a smart thought to make it direct and clear. Appropriate symbols and thumbnails must be utilised to give the coveted data about the application.
Background and Definition for Mobile Digital Platform
Apple’s aim is to expand its business and reach valuable customers providing devices integrated with its in-house operating system and services that are all based on cloud. Therefore, those can be accessed from anywhere and it will help the customers to have access to all the services on the go, which will increase the mobility of services (Kimball and Ross 2015). Apple has taken its business strategy to accomplish this effectively –
- A betterment coating loses concentration enhances the data through discovery, combining with the world’s data and by refining with advanced analytics. Effort of each captivating a quick answer to a question, but realised that one had no way of gathering and analysing the correct data without the IT department’s help. Apple provides the adeptness to connect and import data, create visualisations, and run reports on own whether that be at the desk or on the go.
- Apple outsources cloud space from Amazon AWS for its iCloud services, because of Amazon’s high-end service and live backup facility which helps the data to be saved from getting corrupt.
Apple’s motto was “Think Different” – and keeping in mind that it is presently resigned, and the ethos may not be as evident in the organisation’s items as it once seemed to be, it is valid on their way to deal with Big Data (Pulier et al. 2015). In some courses, in spite of being the most productive tech organisation on the planet, Apple ended up playing get up to speed with Big Data. While Apple customarily utilised groups of generously compensated specialists in style and configuration to deliver frameworks that they thought individuals would need to utilise, contenders like Google analysed client information to perceive how people were utilising them. Apple has regularly been undercover about the procedures behind its most prominent quality – item plan. In any case, it is realised that Big Data likewise has an impact here. Information is gathered about how, when and where its items – Smart telephones, tablets, PCs and now watches – are utilised, to figure out what new elements ought to be included, or how the way they are worked can be changed to give the most friendly and intelligent client encounter. The Siri voice acknowledgement elements of iDevices have demonstrated famous with clients as well, and this is additionally fuelled by Big Data. Voice information caught by the machine is transferred to its cloud investigation stages, which think about them close by a large number of other client entered charges to enable it to end up noticeably better at perceiving discourse designs (machine learning) and all the more precisely coordinate customers to the information they are looking for. Apple may have been slower in its take-up of Big Data and investigation than large portions of its adversaries, however, it has seen that it needs to have a significant influence in its future if it needs to remain in front of the pack (Kelley, Cranor and Sadeh 2013). It appears to be likely that it will attempt and utilise it to move far from depending on colossally costly, roundabout item discharges to drive its development as a business, and towards the more natural, always recovering model of development supported by its rivals in the product and administrations markets. For example, if the answer time is usually in proceedings, Big Data can reduce it to seconds. If it takes weeks for a customer to have their problem tackled, then reducing it to days is more convenient for the client. Customer retention is critical to the success of the organisation.
There are many opportunities for Apple Computers utilising the advantages of cloud computing and big data. The very first is its remarkably loyal client base that has extended past the Mac-leaders of the 1990s with the iPod and the iPhone. The iPad has had an exceptionally efficient dispatch. This is by all accounts prompting more offers of PCs. Along with that it has a merited notoriety for great items that work smoothly. New items are for the most part welcomed and had a worked in acquiring base. Move into other PC or media item spaces that are not served well (Sawhney et al. 2017). Can keep on designing the standard-setter for those spaces. Another form of Apple TV could exploit the present even more very created Web. Along with the time Apple Computer is also moving forward implementing new technologies in their system, like analysing the customer’s requirement Apple took the decision of implementing an on screen fingerprint sensor that will going to replace the old sensors placed in the back of a system.
Apple collects the data from the user for each of the different services it provides, like it accesses the GPS locations, Web Browsing history, Application Usage data, Contact information all are being shared with the cloud and are stored over there. APPLE, LIKE PRACTICALLY every super company, needs to know however much as could reasonably be expected about its clients. On the other hand, it has displayed itself as Silicon Valley’s security champion, one that—not at all like so a substantial portion of its publicising driven rivals—needs to know as meagre as conceivable about you (Kitchin 2014). So maybe it is nothing unexpected that the organisation has now openly bragged about its work in a dark branch of science that arrangements with precisely that Catch 22. Differential security, interpreted from Apple-talk, is a genuine art of attempting to learn however much as could reasonably be expected about a gathering while at the same time learning as meagre as conceivable about any person in it (Chang 2014). With differential security, Apple can gather and store its clients’ information in a configuration that gives it a chance to collect valuable thoughts about what individuals do, say, as and need. In any case, it cannot remove anything about a person, particularly one of those people that may speak to a security infringement. What is more, not one or the other, in principle, could programmers or insight offices. Regardless of whether Apple is utilising differential security systems with the thoroughness necessary to ensure its clients’ protection entirely, of course, is another inquiry. In his keynote, Federighi said that Apple had given the University of Pennsylvania’s Roth a “speedy look” at its execution of the scientific systems it utilised. Roth disclosed to WIRED he could not remark on anything particular that Apple’s doing with differential protection (Gamble and Thompson 2014). Rather, much like the systems is contemplated and create, Roth offered a general takeaway that effectively abstained from uncovering any points of interest: “It is believed that they are doing it right.”
Conclusion
Apple’s Big Data solution can enable breakthrough discoveries by combining data and models with publicly available data and services, including social media sites Like Twitter, Facebook, and LinkedIn. This enables customers to uncover hidden patterns, using the applications and mining algorithms on iCloud. It empowers clients to flawlessly store and prepare information of numerous kinds, including organised, unstructured, and continuous information, through a present day information administration stage. It gives the effortlessness of Cloud on Hadoop, broadens information distribution centres with Hadoop, and offers the flexible versatility of the cloud to Big Data. The chances of Big Data and progressed examination are as significant as the difficulties. The most advanced customary information distribution centre is changing to meet the prerequisites of the present day news venture. Volume increments are required to proceed. Business speed will keep on improving business operations and client collaborations. Information will turn out to be considerably more assorted and more accessible than any other time in recent memory. Massive Data can mean enormous effect on the business. The present day endeavour needs an advanced information stage to take advantage of the new chances of Big Data.
Apple’s presence in cloud computing shows that the organisation has real qualities that can be utilised to addresses to jump more into the market of cloud computing. The organisation can likewise utilise these qualities to abuse the chance to extend its dissemination arrange. In addition, Apple can utilise its solid image picture and fast advancement procedures to create and dispatch new product offerings. Nonetheless, the firm faces the noteworthy dangers of forceful rivalry and impersonation, which are significant difficulties influencing players in the business. A reasonable game plan is to address these vulnerabilities through a more grounded patent portfolio, alongside nonstop advancement to guarantee the upper hand of Apple items notwithstanding when contenders attempt to make up for lost time. Although apple does not the cloud platform, but its cloud services and their popularity in cloud computing will surely lead Apple Computers to own and provide their own services for the peoples.
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