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Big Data and Cloud Computing Assignment

Introduction - Big Data and Cloud Computing

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There has been a stark increase in the number of crimes since the beginning of the worldwide lockdown. This change had been observed since people’s options of making money had diminished initially. As a result, a section of people had to look for opportunities to make money. However, that was not the only aspect of violent crimes that rose. A rise in hate crimes, as well as household fights, had also risen over this time.

Layoffs and furloughs

Several organisations had their hands tied as the noose of low funds kept on tightening around their necks. Coupled with this, the lack of jobs was another issue that the organisations were facing. This was significantly worse in the case of smaller firms. As a result, these institutions were bound to lay off employees. In many cases, organisations even had to be shut down; thus, even the government tied its hands. Smaller organisations have a more significant number of ethnically diverse populations working. Thus, they had a far higher chance of losing their jobs (Allas, Canal and Hunt, 2020).

As per Szulc and Smith (2021), in most cases, the people selected to be furloughed were not consulted. This resulted in their mental health dropping drastically. This aspect with staying at home-brewed people's frustrations even more. This leads to several cases of violent crimes increasing every day. People not being able to leave their homes and head outside also played a major role in increasing violent conduct. People had to be confined within their homes; this further broke down their mental health. These vast amounts of data are used to study the changes that can be made in the world, thus ensuring such issues do not arise in future.

Impact of covid 19

The year 2020 showed people the true wrath of this worldwide pandemic. People had to be locked in their rooms and had no other option than to live in their homes for days at a stretch. This resulted in people feeling low, reminding the world of the situation during the outbreak of SARS in 2003 (Williamson Lombard and Brooks-Hay, 2020). People had to live within their boundaries and were not allowed to meet their acquaintances, this added fuel to the degrading aspect of mental health.

People in several nations faced drastic mental health breakdowns. This was proven by the nation’s violent conduct increasing during the time of this covid 19 pandemic. India saw a doubling of domestic violence reports during the period of the pandemic. Several developed nations faced similar wraths as well. France and Singapore had their DVA helplines rung by more than 30%. While in the UK there was a major rise in the number of calls made to the Domestic Violence Assistance helpline as well (Gray and Hansen, 2021). The UK has a major number of alcoholics; this was a major factor in aggravating violent conduct across the UK.

Figure 1: Alcohol statistics in the UK

(Source: Alcoholchange.org.uk, 2021)

These Big data are collected and are used to find opportunities that can be used to improve conditions in the UK. Cloud computing uses this information and gives a definitive idea through the identification of patterns in the data.

Analysis of big data and cloud computing

Cloud computing provides a software as a service model that allows customers to easily proce[ss variety of data as per organization requirements. The main relationship between big data and cloud computing is very necessary for enhancing the business benefit. Both of the technology7 has been used to enhance the particular revenue of the organization while reducing the investment cost (Khan and Ansari, 2019). In that case, the cloud helps to manage different types of local software and big data helps to make a proper business decision that is a very important part of increasing the business workflow as per company requirements. Big data can deal with different types of data including massive, structured and semi-structured data that helps in data analysis purposes (Bashar, 2019). Several aspects are present for analysing big data including a variety of data, velocity, data values and many others. In the case of cloud computing, it offers different types of services including software as a service, platform as a service and infrastructure as a service.

“IAAS” in public cloud

In the case of IAAS, the service provider offers the whole infrastructure that helps to maintain different types of work. It works as a cost-effective solution and helps to utilize different types of cost-effective solutions. According to Ali et al., (2018), the big data service in the public cloud, helps to enable users to access unlimited storage and its compute power. This solution is very cost-effective and also can manage a huge amount of data.

“PAAS” within the private cloud

In this service, the cloud provider offers several types of resources such as storage, runtime, database and many others (Namasudra, et al., 2020). It has been offered multiple services by eliminating the need for dealing with several complexities and also being able to manage single software and hardware elements that are the real concern of every business organization.

“SAAS” in hybrid cloud

SAAS vendors provide multiple services for conducting the big data analysis for managing different types of data as per company requirements.

Benefits of big data in cloud computing

Multiple benefits are present within the big data analysis and these benefits are given in the below session,

  • Improving the criteria of data analysis

Big data analysis has become more improved through the advancement of cloud technology and cloud service helps to integrate data from numerous sources (Namasudra, et al., 2020).

  • Improving security infrastructure

Cyber security threats are becoming a big headache for every business and other organization. According to Ionescu and Andronie (2021), in that case, attackers are trying to steal essential business information for the company's reputational and financial loss. Data security and data privacy are the two major concerns during a company dealing with enterprise data.

  • Optimization of Cost: The functionality of cloud computing is very cost-efficient as there is no implementation required for the company. All they need to do is subscribe to the respective cloud and use it as per the need of the company (Stergiou and Psannis, 2017). There will be no additional cost if all processes are involved in big data cloud computing.
  • Implementation time- there is no implementation time required for the use of the cloud in the system as there is no physical implementation process id associated with the system. Only the subscription part is needed when big data is used in the cloud computing part. Therefore, the implementation time will be reduced to almost negligible time.
  • Improvement in efficiency: Improvement of efficiency is vital in case organisations wish to survive for a long time. According to Deb, Cousins and Fuad (2018), there are aspects in an organisation that can only be improved once they can understand the problem. In these cases, Big data becomes key. Overall improvement of organisations is based on their internal development. This development is completed only by organisations if they have a large amount of data in their store.
  • Helps in improvement in sales and loyalty- using the big data, the company can achieve target marketing as it will provide the base of the customer management system and the marketing data is also included in the process (Stergiou and Psannis, 2017). In addition, analysis of data helps in identifying customer demand and helps in identifying customer demand and based on that companies can improve their products and can do targeted marketing. In addition, big data analysis helps in identifying sentiment analysis of customers hence helping in business improvement.
  • Helps in automated updates- Organisations use Big data to understand aspects of their systems that can be upgraded. This procedure is only possible if they have a large collection of data that can be used to improve their internal structure. Thus, the company will get automatic updates for company as the update will be done automatically.
  • Improvement of understanding of data: Big data is widely used in data science. In updated technologies such as the Internet of Things (IoT), big data is widely used. In usage in companies, big data helps in identifying hidden correlations in businesses and helps in understanding business flow. Understanding of data of companies helps in targeted marketing as well improvement of products based on customer sentiment analysis. Big data analysis also helps in identifying trends in the market and based on this analysis, companies can improve their products.

Characteristics of Big data

The characteristics of big data are considered very important and can be categorised as four parts starting with V are “Volume, Variety, Velocity, Veracity”. The “volume” is defined as the size of the data used in the entire system. This is the main attribute used in the entire system. The "velocity'' is termed as the rate for which the data is used for collection or changing rate (Ionescu and Andronie, 2021). It is important in the share market as the market prices in the stock market are checked as well as used at a very quick rate of velocity using a very less frequency of not more than one second. The “Variety” describes the origination of the sources that are from whether the data is coming that could be from social media accounts or any live streams." Veracity" is defined by determining the quality of data (Stergiou and Psannis, 2017). The quality will also be measured by observing the techniques about whether the data is consistent or not.

Management of storage in the cloud

There are different packages used by different software companies for facilitating cloud computing. In case of large data or texts used in the system, the warehouse system can also be used for updating the details. According to Deb, Cousins and Fuad (2018), for better functioning of the software, “NoSQL” can be used for controlling the storage devices in the cloud so that it will work more efficiently. “Big data Hadoop” is a mostly available software platform that could be used in the process, which is written by using Java that would be characterised for using the clusters of services based on the running server. The velocity depending on the entire process is based on the storage of the works based on the development of the software that also helps in enabling the releasing the workloads (Stergiou and Psannis, 2017). This system would allow in creating pipelines for proper optimization of the work by creating the cluster based on the demands that will help in reducing the costs of the process. The cloud will also help in merging with different forms for working efficiently in the systems. Many other programming languages could also use the features of Hadoop and they are “Java, .NET, Python, Go” and many more.

Literature gap

A large amount of information is used in big data to understand the patterns that can be observed in these packets of information. However, in most cases, the data is so varied that the chances of finding such patterns are lowered. In the case of a study presented by Szulc and Smith, (2021) there is an enhanced chance of an ethnically diverse population to lose their jobs. However, this study can not properly depict the issues that these diverse ethnicities are facing. As a result, the patterns that are finally received are not completely reliable. Thus, people may be severely misled by believing the issues that are being faced by people. Nevertheless, the collection of big data has several advantages. Organisations use these data to understand the problems that may presently be causing issues in their organisational structure.


The "Big data" is defined as the sets based on the sets that are already collected for controlling the large sets. Several mechanisms can be used for processing the data in the process that will also help in increasing the efficiency of the performance based on the specified data. Cloud computing will help in the processing of the resources.

Reference list

Alcoholchange.org.uk, 2021. https://alcoholchange.org.uk/alcohol-facts/fact-sheets/alcohol-statistics

Ali, H.B.Y., Abdullah, L.M., Kartiwi, M., Nordin, A., Salleh, N. and Bakar, N.S.A.A., 2018, May. A Systematic Literature Mapping of Risk Analysis of Big Data in Cloud Computing Environment. In Journal of Physics: Conference Series (Vol. 1018, No. 1, p. 012017). IOP Publishing.

Allas, T., Canal, M. and Hunt, V., 2020. Covid-19 in the United Kingdom: Assessing jobs at risk and the impact on people and places. Public Sector Practice. McKinsey & Company.

Bashar, A., 2019. Intelligent development of big data analytics for manufacturing industry in cloud computing. Journal of Ubiquitous Computing and Communication Technologies (UCCT)1(01), pp.13-22.

Deb, D., Cousins, S. and Fuad, M., 2018, May. Teaching Big Data and Cloud Computing: A Modular Approach. In 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (pp. 377-383). IEEE.

Gray, C. and Hansen, K., 2021. Did the first Covid-19 national lockdown lead to an increase in domestic abuse in London? (No. 21-27). Quantitative Social Science-UCL Social Research Institute, University College London.

Ionescu, L. and Andronie, M., 2021. Big Data Management and Cloud Computing: Financial Implications in the Digital World. In SHS Web of Conferences (Vol. 92). EDP Sciences.

Khan, M. and Ansari, M.D., 2019. Security and privacy issue of big data over the cloud computing: a comprehensive analysis. International Journal of Recent Technology and Engineering (TM)7(6s), pp.413-417.

Namasudra, S., Devi, D., Kadry, S., Sundarasekar, R. and Shanthini, A., 2020. Towards DNA based data security in the cloud computing environment. Computer Communications151, pp.539-547.

Stergiou, C. and Psannis, K.E., 2017, July. Algorithms for big data in advanced communication systems and cloud computing. In 2017 IEEE 19th Conference on Business Informatics (CBI) (Vol. 1, pp. 196-201). IEEE.

Szulc, J.M. and Smith, R., 2021. Abilities, motivations, and opportunities of furloughed employees in the context of Covid-19: preliminary evidence from the UK. Frontiers in Psychology12, p.632.

Williamson, E., Lombard, N. and Brooks-Hay, O., 2020. Domestic violence and abuse, coronavirus, and the media narrative. Journal of gender-based violence, 4(2), pp.289-294.

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