Big Data Analytics: Techniques, Challenges and Business Support
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This report discusses the characteristics of big data, challenges faced in big data analytics, techniques used for analyzing big data, and how big data technology can support businesses. It also includes a poster and references. Course code, course name, and college/university are not mentioned.
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BSc (Hons) Business Management BMP4005 Information Systems and Big Data Analysis Poster and Accompanying Paper Submitted by: Name: ID: 1
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Contents Introductionp What big data is and the characteristics of big datap The challenges of big data analyticsp The techniques that are currently available to analyse big data p How Big Data technology could support business, an explanation with examplesp Posterp Referencesp 2
Introduction Bigdata refers tocollectionof datawhichis inlargeinvolumeandgrowing continuously with time. It It consist large size and complexity of data which can be stored by traditional data management tool in effective manner(Ghasemaghaei and Calic,2019).Thisprojectreportconsistdescriptionofbigdataalongwithits characteristics. It includes different challenges related to data analytic and includes different techniques used in current business environment. Moreover, it consist different ways in which data is used in business. What big data is and the characteristics of big data Big data is one of field which treats different ways for analyses, extract or deal with different data set which are too complex and large in order to dealt with traditional data processing application software(Ghasemaghaei, 2020). In today's competitive technology world, big data is emerges as a tool which create impact on many industry specially in IT industry. There are different types of Big Data technology which consist Spark, Hive, SQL, Cloud and Spark. It is one of software which helps to store as well as manage big data which is related to business. It is one of technology which consist assessment of different factors related to data storage, data management which are important for purpose of growth of an organization and also develop synchronization of big data. There are mainly two types of data like operational data and analytical data. It is important in organization as it ensure effective resource management and also leads to improve operational efficiency. It optimism development of products and which helps business to drive revenue and getting growth opportunities. Characteristics of Big Data: Variety:Varietyinbigdatareferstounstructured,structureaswellassemi structured data which is gathered from different source(Grover and Kar, 2017). In past, data can be collected only from data vases as well as spreadsheet but in today's time, data can be collected in different forms like videos, emails, audios, PDF, SM posts, photos and others. Verity in data is important and is one of feature of big data. 3
Velocity:Velocity refers to speed with which data can be created in real time. In a wider prospect, it comprise linking of incoming set of data with different speeds, activity bursts and rate of change. Volume of data:Volume is one of characteristic of big data as it indicate data in huge volume which can be generated from different source on daily basis like business process, social media platform, human interaction, machine work and many more. These large numbers of data can be stored in warehouses. The challenges of big data analytics There are different organization which can be stuck in process of managing big data. These big data are important for growth and success of company(Gupta and Rani, 2019). It is important for them to protect this data from different things. It can be due to various reason which are as follows: Lack of understanding of Big Data:Due to insufficient understanding, many time companies fails to big data initiates. Employees of companies sometimes does not have understanding about data, ts importance, process, storage as well as source. Only data professional have proper knowledge of data and other people does not have clear understanding of it. Issues related to growth of data:Issues related to growth of data is another challenge for big data. It is difficult to store these large size of data properly. There is increase in data which is stored in different data centers and also in data of an organization which is increased day by day. These data is growing on continuous basis and it is difficult for company for handle these types of data. Confusion of Big data tool selection:It is one of another challenge for big data selection which create confusion for selection of best tool for purpose of big data analysis along with storage(Manogaran and Lopez, 2017). In order to select best tool for big data, it is important for them to have understanding of big data. Securing data:Security is another issues for big data as it is difficult for a company toprotecttheselargeamountofdata.Businessareoftenengageinstoring, understanding as well as analyzing of different data set which create different stage of data security. These data can be lost due to mistake of a person or can be access through unauthorized use which create problems for business. 4
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Integration of data from different sources:There are different types of data which camefrom differentsourceinbusiness likefinancial reports, ERP application, customer logs, social media pages, Presentation as well as reports developed from employees(Shah, Steyerberg and Kent, 2018). In this combination of different data for purpose of preparation of report create challenge for business. The techniques that are currently available to analyse big data Data Fusion:Data Insights are potentially accurate and efficient by combining different set of techniques which helps to analyses as well as integrate data from various sources as well as solution. Data mining:It is another tool which is used in anlytics of big data. Data mining helps to extracts different patterns from big sizeof data withcombining from machine learning as well as statistics in data base management(Surbakti, Wang, Indulska and Sadiq, 2020). Data is mined for determining segment which is likely to react to different offers of company. Machine learning:It is one of commonly used term in artificial intelligence field and also used for data analysis(Taleb, Serhani and Dssouli, 2018). It is emerged in computersciencewhichworkinalgorithmsincomputerinordertoproduct assumptions of data. It offer different prediction which is impossible for analytic of human. A/B testing:It is another technique which consist comparison of control group with different variety of test group that helps to discern different changes and treatment for purpose of improvement in given objectives. HowBigDatatechnologycouldsupportbusiness,an explanation with examples In today's competitive environment, big data helps business to grow and handle customer data. There are different organization which get competitive advantage on 5
basis of big data technology. It support to business with use of different factors which are mentioned below: Management of Data:Management of data is important for a business which can be done with help of big data. It consist use of different advance systems and software which helps business to manage big data effectively. Thee data can be managed with big data technology and make it available for them for long period of time. For instance, Hilton is one of largest hotel chain in world which is managing customer data effectively in different parts of world with use of big data technology. Customer engagement:Big data also helps business in increasing engagement of customers with help of synchronization of data. It is important for IT department to handle data effectively as per numbers of customers. It is essential priority of businesswhichhelpsbusinesswithincreaseinvaluesalongwithcustomer satisfaction that is important to develop trust in business. For instance, H&M is one ofretailorganizationwhichisincreasinglyengagingtheircustomersandalso enhancing their satisfaction with use of big data technology Privacy of data:Privacy of data is one of important component for both customers and company. It consist use of big data technology which is important for maintaining data privacy of customers. It helps to increase faith and loyalty of customers in company. For instance, Amazon is an organization which is providing different product and service to their customers is maintaining strong privacy priority which helps them to protect private information of customers and also increase CONCLUSION From above mentioned project report, it can be concluded that Big data is one if important technology for business which helps them to protect data of company efficiently. It also helps company to manage data in a way which increase trust of customers on organization. Big data consist different features like volume of data, velocity of data as well as variety of data. It includes different challenges for business likelackofunderstanding,growthandmanymorewhichcreateimpacton performance of company. There are different tool can be used by company for purpose of data mining, data fusion, data integration and others. There are different ways in which big data provide support to business like management of data and privacy of data and many more. 6
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References Ghasemaghaei, M. and Calic, G., 2019. Can big data improve firm decision quality? Theroleofdataqualityanddatadiagnosticity.DecisionSupport Systems,120, pp.38-49. Ghasemaghaei, M., 2020. The role of positive and negative valence factors on the impact of bigness of data on big data analytics usage.International Journal of Information Management,50, pp.395-404. Grover,P.andKar,A.K.,2017.Bigdataanalytics:Areviewontheoretical contributions and tools used in literature.Global Journal of Flexible Systems Management,18(3), pp.203-229. Gupta,D.andRani,R.,2019.Astudyofbigdataevolutionandresearch challenges.Journal of Information Science,45(3), pp.322-340. Manogaran, G. and Lopez, D., 2017. A survey of big data architectures and machine learningalgorithmsinhealthcare.InternationalJournalofBiomedical Engineering and Technology,25(2-4), pp.182-211. Shah,N.D.,Steyerberg,E.W.andKent,D.M.,2018.Bigdataandpredictive analytics: recalibrating expectations.Jama,320(1), pp.27-28. Surbakti, F.P.S., Wang, W., Indulska, M. and Sadiq, S., 2020. Factors influencing effectiveuseofbigdata:Aresearchframework.Information& Management,57(1), p.103146. Taleb, I., Serhani, M.A. and Dssouli, R., 2018, July. Big data quality: A survey. In2018 IEEE International Congress on Big Data (BigData Congress)(pp. 166-173). IEEE. 8