Information Systems and Big Data Analysis for BSc (Hons) Business Management
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This report discusses the concept of big data, its characteristics, challenges, techniques for analysis, and how big data technology can support businesses. It also provides insights into BSc (Hons) Business Management.
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BSc (Hons) Business Management BMP4005 Information Systems and Big Data Analysis Poster and Accompanying Paper Submitted by: Name: ID: 0
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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 Referencesp 1
Introduction Information systems and big data is important for every business. Data is the most important thing because it will help company to grow but managing such large data is also challenging. This report has discussed about the concept of big data and its challenges. Further it will evaluate techniques of big data and how technology can help today’s business. What big data is and the characteristics of big data Big data is refers to those information or data which cannot be processed or evaluated by using the traditional method of processing or technique. Nowadays organisations are having more big data but they are unable to find out value from within because of the availability in the raw form or in the unstructured form and also company do no have knowledge that they should use big data where and how (Dash and et.al., 2019). As per the research managers of the company doesn’t have the insights access of their jobs.as companies are working in the environment where they are having the capacity to store as much data they want but they does not have idea to how to saturate the raw data. As it name suggests that big data means the data which is large in size and does not gets processedeasily. Butwiththehelpof informationtechnology, things are becoming easy and also people and technology have got interconnected. Characteristics of big data- Volume: The volume of data which is stored is increasing day by day and the data which is created and stored in today’s world are not analysed at all.which is the biggest problem. For every big organisation now it has become normal to generate terabytes of data everyday. If think properly than it can be seen that every activity which is doing through electronic medium is generating data where it is downloading something to changing TV channel etc. organisatiosn are facing the problem of big data because they have data stored with them in large volume (Allam and Dhunny, 2019). Variety: Asthetechnologyisevlovingandtheuseofsmartphonesarealsoincreasing, companies are becoming more complex. The have variety of big data availble with them which are raw data, structured, unstructured data etc. traditional analytic platforms are unable to handle the varieties of big data. Velocity: As the volume and variety of data has increased just like that the velocity of data which is generated should be handled properly. Velocity means the speed of the data arriving and stored. The challenges of big data analytics There are many challenges which are associated with big data which are as follows: Lack of knowledge professionals- Organisations required skilled and knowledgeable experts for the purpose of using modern technologies and handling data tools (Kolajo, Daramola and Adebiyi, 2019). These experts can be data analysts, data engineers, data scientists etc. which can work with diffferent tools and can handle giant data. Nowadays companies are lacking over data professionals. As data handling tools are changing and individual do not have much knowledge on the advanced tool. 2
No proper understanding over massive data: Employees of the enterprize are not efficient in understanding the importance, storage andprocessingofthebigdata.Dataprofessionalshaveideaofexactlywhatis happening but other employees does not have the clear picture of it. If the employees are unaware of the data importance than they will not store the sensitive data. Data growth issues: One of the major challenge is the stroing the large data in proper manner. As the quantity of data which is stored in companies are increasing rapidly. When the quatity grows with time than it becomes difficult to handle it (Favaretto and et.al., 2020). Confusion is selecting big data tools: Often it has seen that organisation are confused in regards of selecting easy tool which can store and handle big data easily.there are lots of tool available in the market so selection the best tool within the variety of tool is the complex process. There are high chances that companies make poor decisions and select inappropriate technology which results in wasting of time, money, efforts etc. Integration of data from spread of soruce: Data is generated from various platforms which are cutomer logs, social media page, emails, financial reporting, presentations etc. combining all the data together to make one report is the difficult process. Intergrating daata is complex for the purpose of reporting, evaluation, business intelligence etc. Security of data: Keeping security of such huge data sets is the other major challenge. Often it is notices that enterprizes are busy with storing and analyzing the data and they neglect the security part of it. If data is not secured than it can be hacked by hackers and hackers will use the data in blackmailing company. The techniques that are currently available to analyse big data A/B testing- This is the big data analyse technique which compares variety of test groups with the control group, in order to find out that what are the treatments required for improving the objective variable (Zhu and et.al., 2018). This technique is used to test large number which is availble in big data. Random method is used in this test within two variants which is A or B. in this particular statistics statistical hypothesis testing is being used. Data mining: This is the most common tools which are used by many data experts. This data mining tool is used in extracting the different data patterns from the huge data sets by using combined methods of machine learning and statistics. Example while understanding that which segment of customer will reach to the discount or offers given by the company, customer data is mined by the experts. Machine learning: This technique belongs to the area of artificial intelligence, machine learning process are utilized by the data experts. It has evaluated from the computer science and used computer algorithms for providing the data assumptions. Coding is done from taking out assumptions from the data sets. It also helps in providing various predictions to the experts. In simple language this technique is based on the computer algorithms which is helpful in improvisation of data. 3
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Data integration: Itcombinesvarious techniquewhichintegrateandevaluatethedatafromvarious sources (Lv and Qiao, 2020). The insights which is arised from the single source of data are accurate and more efficient. HowBigDatatechnologycouldsupportbusiness,an explanation with examples Big data is the technique which is used in managing huge data sets. Big data can be used by the business for attaining growth and success. Big data helps the business in making new services, experience and products. There are various benefits which big data can provide business which are as follows- Providing competitive advantage to business- Manyfirmsareusingbigdataforgainingthecompetitiveadvantage.Manynew companies are providing tough competition to other companies by using data driven strategies for capturing the market and by providing innovative products. It can be find out that every organisation from IT to healthcase industry all are using big data from gaining the competitive advantage. Experts are also saying that big data can provide lot of opporttunities in terms of growth to the business. Dialogue with consumers- Nowadays consumers are smart enough and they know exactly what they want. Before purchasing anything consumers compare each and everything. They have conversation with the business by using various social media platforms and also raise their query if they are having any. Big data helps companies in reaching towards their target customer group. This help company in engaging with real time conversation with the consumers. It is important for the cmpany to give priority to the customers and also to fulfil their demand if company want to survive in the market for the long time period. Redeveloping products: Big data can be used by the firms for gathering feedbacks from the customers. When company will take feedback from the customers then they will understand needs of the customers.Byknowingtheneedsofthecustomerscompanycanredevelopthe productsaccordingtothecustomerpreference.Byreadingthecommentswhich customer gives on social media through that also company can find out the customer needs. Example: if company want to know the customer preference than they can carry question and answer activity on social media platforms which will be helpful in getting knowledge about the customers taste (Oussous, Benjelloun, Lahcen and Belfkih, 2018). Likewise company can also collect information on material affect costs, lead times, performance etc. company can even upgrade the productivity of their production unit with the help of big data. Data safety: There are various big data safety tools which can be used by the company for securing their data. As it will be helpful to the company in knowing about the internal threats. With the help of tools and technique company can keep their sensitive information safe. That is why there are many organisation which is focusing on big data for the protection and safety purpose. Conclusion Through this report it can be conlcuded that big data is said to as the large data sets or information which is available and stored with the company and which are also difficult to 4
handle. This report has discussed about various challenges regarding big data which can be massive data, lack of data experts etc. there are also many techniques which is used for big data analysis which are A/B testing, data mining etc. big data is used by business for attaining safety and growth and success. Characteristics of Big data Volume: The volume of data which is stored is increasing day by day and the data which is created and stored in today’s world are not analysed at all which is the biggest problem. Variety: Asthetechnologyisevolvingandtheuseofsmartphonesarealsoincreasing, companies are becoming more complex. Velocity: 5
As the volume and variety of data has increased just like that the velocity of data which is generated should be handled properly. The challenges of big data analytics Lack of knowledge professionals- Organisations required skilled and knowledgeable experts for the purpose of using modern technologies and handling data tools. No proper understanding over massive data: Employees of the enterprize are not efficient in understanding the importance, storage and processing of the big data. Data growth issues: One of the major challenge is the storing the large data in proper manner. As the quantity of data which is stored in companies are increasing rapidly. Confusion is selecting big data tools: Often it has seen that organisation are confused in regards of selecting easy tool which can store and handle big data easily. there are lots of tool available in the market so selection the best tool within the variety of tool is the complex process. Techniques that are currently available to analysis big data A/B testing- This is the big data analyze technique which compares variety of test groups with the control group, in order to find out that what are the treatments required for improving the objective variable. Data mining: This is the most common tools which are used by many data experts. This data mining tool is used in extracting the different data patterns from the huge data sets by using combined methods of machine learning and statistics Machine learning This technique belongs to the area of artificial intelligence, machine learning process are utilized by the data experts Data integration: Itcombinesvarious techniquewhichintegrateandevaluatethedatafromvarious sources. How Big Data technology could support business Providing competitive advantage to business- Manyfirmsareusingbigdataforgainingthecompetitiveadvantage.Manynew companies are providing tough competition to other companies by using data driven strategies for capturing the market and by providing innovative products. Dialogue with consumers- Nowadays consumers are smart enough and they know exactly what they want. Before purchasing anything consumers compare each and everything. Redeveloping products: Big data can be used by the firms for gathering feedbacks from the customers. When company will take feedback from the customers then they will understand needs of the customers. Data safety: There are various big data safety tools which can be used by the company for securing their data. As it will be helpful to the company in knowing about the internal threats. 6
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References Allam,Z.andDhunny,Z.A.,2019.Onbigdata,artificialintelligenceandsmart cities.Cities.89. pp.80-91. Dash, S. and et.al., 2019. Big data in healthcare: management, analysis and future prospects.Journal of Big Data.6(1), pp.1-25. Favaretto,M.andet.al.,2020.WhatisyourdefinitionofBigData?Researchers’ understanding of the phenomenon of the decade.PloS one.15(2). p.e0228987. Kolajo, T., Daramola, O. and Adebiyi, A., 2019.Big data stream analysis: a systematic literature review.Journal of Big Data.6(1). pp.1-30. Lv, Z. and Qiao, L., 2020. Analysis of healthcare big data.Future Generation Computer Systems.109. pp.103-110. Oussous, A., Benjelloun, F.Z., Lahcen, A.A. and Belfkih, S., 2018. Big Data technologies: Asurvey.JournalofKingSaudUniversity-ComputerandInformation Sciences.30(4). pp.431-448. Zhu, L. and et.al., 2018. Big data analytics in intelligent transportation systems: A survey.IEEE Transactions on Intelligent Transportation Systems.20(1). pp.383-398. 7