Information Systems and Big Data Analysis - A1 Big Data
Verified
Added on 2023/06/08
|8
|1838
|198
AI Summary
This report defines big data and its attributes, discusses the challenges faced in big data and the techniques used for solving these issues, and explains how big data technology supports businesses with certain examples.
Contribute Materials
Your contribution can guide someone’s learning journey. Share your
documents today.
Information Systems and Big Data Analysis - A1 Big Data
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
Contents INTRODUCTION...........................................................................................................................3 MAIN BODY..................................................................................................................................3 Define big data and its attributes.................................................................................................3 Discuss the challenges faced in big data and the techniques used for solving these issues........4 Explain Big Data Technology Supporting Businesses with certain examples............................5 Poster...............................................................................................................................................7 REFERENCES................................................................................................................................8
INTRODUCTION Anaccumulationoforganised,semiorganisedandunorganiseddatacollectedby organisation that can be extracted for information and can be used in anticipatory modelling, technological projects and other advanced analytical techniques is termed as big data (Hou and et.al., 2020). This report consists of Big data definition and its characteristics.It also includes challenges faced due to analytics of Big Data and the techniques which are presently accessible for Big data analysis. Support to business due to the use or Big Data technology have also been considered in the following report. MAIN BODY Define big data and its attributes. Big data is an assemblage of data that is huge in quantity, still has a potential or power to grow speedily with time. The capacity of data is so huge and large in size that none of the conventional data management techniques and tools can store it or operate it with efficiency. Applications or technology that operates or stores big data have become a common factor of data management structures in entities that supports use of big data analytics. Organisations uses big data technology to upgrade their operations or working, and also to make available better and improve services to its customers and promotional or marketing activities which in turn results in increase in revenue and profits of the entity. Big data technology carries multiple advantages with it such as: Provides better consumer or customer services Improves functional efficiency of the organisation Determines the risk to the product or services offered by the entity Enterprises can use external intelligence services in decision making process Features of Big data:Big Data is an assemblage of data from a wide and different variety of sources and commonly describe its five characteristics: 1.Volume:It refers to the unthinkable quantity of information that is created from social media, cell phones, photographs, videos and credit cards. The name big data is itself related to a size which means huge or enormous (Ianni and et.al., 2020). Size of data plays a crucial role in determination of value of data. Also, the size of data totally
depends on the volume of the data. While dealing with Big data solutions, volume should be kept into mind. 2.Variety:This refers to the heterogeneous sources and the quality of data, both organised or unorganised are included. In the initial days, the only source of data considered by most of the applications were databases and spreadsheets. IT is generated in different varieties. In present scenario, photos and videos are also considered in the analysis of application (Mangla and et.al., 2020). 3.Velocity: This term means to the generation of speed of the data that how fast a data can be created or processed to meet the demands and determines the potential of the data. It plays a vital role as compared to the other features of Big data. It makes available data on demand and at a faster rate. 4.Variability: This means to the non-uniformity which can be shown by the data in some cases, therefore restricting the procedures of being able to manage the data efficiently. 5.Value: It is the major concern of the entity using Big data technology. It is the amount of important, dependable and honest data that needs to be preserved, progressed and analysed to find and understand the insights. Discuss the challenges faced in big data and the techniques used for solving these issues. In this digital era, organisations use big data technology for better decision making, growth in accountability, increase productivity, make improved and healthier predictions, performance monitoring and to acquire a competitive advantage over its rivalries. Major problems faced by using Big data technology are discussed below: Unable to provide new or timely insights: Organisations in order to take better and improved business decisions uses analytics but in some cases it can be observed that the information’s provided by the new system or applications resemble to the information which has been provided earlier. This can be due to insufficiency of data, using traditional approaches in a new system and data takes longer time to respond (Nguyen, 2018). Incorrect analytics: This is the main and important challenge faced by the enterprises and it needs special and speedily attention of the management of the organisation to resolve it. Inaccurate analytics can be occurring due to poor or inappropriate quality of data
Paraphrase This Document
Need a fresh take? Get an instant paraphrase of this document with our AI Paraphraser
which is incomplete or contains defects or errors and also due to faults in the system of flow of data. Complications in using data analytics: Organisations find it difficult to extract value from data when using data analytics becomes complicated. This complexity arises due to less technical knowledge and when the users find it difficult to understand the system, data and the reports (Sharma, Borah and Namasudra, 2021). Techniques for analysing Big data:Machine learning: It involves software program that can learn from data. It provides systems the capability to grasp without being defining programmed, and focuses on building projections supported on known properties absorbed from sets of instructing data. It aids in differentiating between junk and non-junk mail messages and make suggestions based on the provided substance.Regression Analysis: It concern with contriving some independent variable to perceive how it influences a dependent variable. It states how the value of a dependent variable alters when the independent variable is deviated. It works best with continual quantifiable information like mass, velocity or age group.Social network analysis: A method that was initially utilised in the telecom sector and then rapidly acquired by sociologists to learn interpersonal relation and applied to examine the relationships between groups in many sectors and commercial undertakings. Explain Big Data Technology Supporting Businesses with certain examples. With the use of Big Data, organisations can utilize analytics, and illustrate or build out the most valuable or cherished customers. It can also assist industries in creation of new experiences or content, services and products. Big data technology can aid businesses in five ways which are discussed below: Making improves business decisions:Big data assist the businesses in taking smarter decisions that are supported by data and not merely on assumptions. Users of the company across the world have an ability to investigate and question data so that they can response their most crucial business questions. This organisation's wide approach to data is referred to as data democratisation(Vo and et.al., 2019). Walmartis an outstanding example of this data democratisation. Significantly, Walmart supplies its people to
approach to data in a well organised manner securing that people who are not known of the technology do not get engulf by data and can easily discover the solution they want. Delivering Smarter services or products:When an organisation come to know about its customers, it starts delivery smarter or suitable products or services for its customers which fulfil their needs completely and satisfies them to the fullest. Royal Bank of Scotland (RBS) is agreat example of organisation using Big Data to deliver a better service to its clients. RBS is beginning to support the potential of this knowledge to amend and improve its efficiency in order to meet its customer wants or needs. Improving business operations:The outgrowth in automation is supported by Big Data. Robotics and high technology may be outdated in production industry lines. But, progressively, a number of business sectors and operations are becoming more efficient, effective and automated(Zhao, Xu and Wang, 2019).PeopleDoc, a HR software company, that has launched a Robotic Process Automation platform, that operates besides present system of the company and perceive for procedure or events that could be automate Generating an Income: Big Data is not just about rising procedure and conclusions, or knowing more about its customer's data can be processes and decisions, or understanding more about customer’s data can be monetised to encourage or create an auxiliary income stream.American Expressis generating income by the aid of Big Data technology. CONCLUSION From the above prepared report, it can be concluded that, the Big data technology assist the businesses along with facing various challenges and providing techniques or methods to face those challenges and aid in the growth of the organisation.
Poster
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
REFERENCES Books and Journals Hou, R., and et.al., 2020. Unstructured big data analysis algorithm and simulation of Internet of Thingsbasedonmachinelearning.NeuralComputingandApplications,32(10), pp.5399-5407. Ianni, M., and et.al., 2020. Fast and effective Big Data exploration by clustering.Future generation computer systems,102, pp.84-94. Mangla, and et.al., 2020. Mediating effect of big data analytics on project performance of small and medium enterprises.Journal of Enterprise Information Management. Nguyen, T.L., 2018, December. A framework for five big v’s of big data and organizational culture in firms. In2018 IEEE International Conference on Big Data (Big Data)(pp. 5411-5413). IEEE. Sharma, P., Borah, M.D. and Namasudra, S., 2021. Improving security of medical big data by using Blockchain technology.Computers & Electrical Engineering,96, p.107529. Vo, A.H., and et.al., 2019. An overview of machine learning and big data for drug toxicity evaluation.Chemical research in toxicology,33(1), pp.20-37. Zhao, Y., Xu, X. and Wang, M., 2019. Predicting overall customer satisfaction: Big data evidencefromhotelonlinetextualreviews.InternationalJournalofHospitality Management,76, pp.111-121.