FACULTY OF BUSINESS

FACULTY OF BUSINESS, COMMUNICATIONS AND LAW (FOBCAL) COURSEWORK COVER PAGE (GROUP) TO BE COMPLETED BY STUDENTSFULL NAMEMATRICULATION NO.1) 2) 3) 4) 5) 6) 1) 2) 3) 4) 5) 6)COURSE CODE AND COURSE NAMECSC1215 BASIC COMPUTING LECTURERS NAME Mr. Mohd Fakhri bin Mat Saad SECTION / GROUP 4A1 / 4D1 / 4G1 / 5A1 / 5D1 / 5G1 / SESSIONMAY 2018COURSEWORK DETAILS ( ASSIGNMENT ( OTHERS _________________ DUE DATE6TH JULY 2018 NOTE PLEASE SIGN THE STUDENTS DECLARATION ON THE NEXT PAGE Students declaration We understand what is meant by plagiarism. We declare that this is our own work except where due references are made. We hereby certify that no part of this assignment or product has been copied from any other students work or from any other source except where due acknowledgement is made in the assignment. We are aware that this work may be reproduced and submitted to plagiarism detection software programs (Safe Assign) for the purpose of detecting possible plagiarism (which may retain a copy on its database for future plagiarism checking). We hold a copy of this assignment which we can produce if the original is lost or damaged. NameSignature1) 2) 3) 4) 5) 6) 1) 2) 3) 4) 5) 6) Note Lecturer has, and may exercise, the right not to mark this coursework if the above declaration has not been signed. If the above declaration is found to be false, appropriate action will be taken which would lead to ZERO mark being awarded for this coursework. OFFICE USE ONLYMarkers comments Late submissionExtension GrantedDeductionFinal MarksYESNOYESNO CSC 1215 BASIC COMPUTING RESEACH REPORT RUBRIC CSC 1215 – RESEARCH REPORT ASSESSMENT FORM Level of AchievementExcellent 5Good 4Average 3Adequate 2Need Improvement 1PointsIntroduction Posed thoughtful, creative overview that contribute knowledge in a specific area. Posed focused overview that yield relevant information in a specific area. Relied on instructors generated responses or posed with little overview.Organization Information is very organized with well-constructed paragraphs. Content follows a logical sequence which adds clarity to reader. Information is organized with well-constructed paragraphs. Content flows nicely to add clarity to reader. Information is generally organized with only 1 or 2 problems separate ideas discussed in separate paragraphs content is generally clear to reader. 2 or 3 problems with organization of information separate ideas are not discussed in separate paragraphs reader must reread at times for clarity. Information is disorganized gaps in content leave reader confused.Quality of Information Information clearly relates to questions posed in the introduction 3 or more unique, creative supporting details and/or examples are used which add interest to reader. Information clearly relates to questions posed in the introduction 2 supporting details and/or examples are used to add interest. Information clearly relates to the questions posed in the introduction 1 supporting detail and/or example are used to add interest. Information is not entirely related to questions posed in the introduction No supporting details and/or examples provided. Information has little to do with the questions posed in the introduction.Diagrams Diagrams and illustrations are neat accurate to the questions posed in the introduction they provide additional insight to the content. Diagrams and illustrations are accurate and clearly relate to the questions posed in the introduction they add interest to the content. Diagrams and illustrations are accurate and are related to the questions posed in the introduction. Diagrams and illustrations where present are neither neat nor entirely accurate they dont add much to the content. Diagrams and illustration where present are neither neat nor accurate and they dont appear to relate to the questions posed in the introduction. Level of AchievementExcellent 5Good 4Average 3Adequate 2Need Improvement 1PointsPunctuation, Capitalization Spelling There are no grammatical, spelling or punctuation errors. There are 1 or 2 minor grammatical, spelling or punctuation errors. There are 3 or 4 minor errors in punctuation, grammar and/or spelling which do not break the flow for the reader. There are 1 or 2 major errors in punctuation, grammar and/or spelling which do interrupt the flow for the reader. There are a number of major errors in punctuation, grammar and/or spelling which make it difficult to read. Discussion Highlight important information conclusions are logical and reasonable and clearly relate to the questions posed in the introduction. Highlight important information conclusions are reasonable and clearly relate to the questions posed in the introduction. Important points indicated conclusions are reasonable and relate to the questions posed in the introduction. Not all of the important points are identified there are some gaps in logic relating conclusions to the questions posed in the introduction. Important points not identified conclusion does not relate to questions posed in the introduction. Sources All sources are accurately documented and in the desired format 5 or more sources were used. All sources are accurately documented and in the desired format 3 to 4 sources were used. All sources are accurately documented. Only 1 to 2 sources were used. Attempted to document source used is not completely accurate. Source used is not documented at all. Level of AchievementExcellent 5Good 4Average 3Adequate 2Need Improvement 1PointsContentThe deliverables are complete and meets the requirements specified in the assignment.The deliverables are complete and substantially meets the requirements of the assignment, but there are1 or 2 errors notedThe deliverable isalmost completeand almost meets the requirements of the assignment, but there are2 or 3 errorsnoted The deliverable isincomplete and only partially meets the requirements of the assignment. Overall, this is half of what was expected.The deliverable isnot completeand fails to meet the requirements of the assignment. Overall, the deliverables are substantially below the expected level.Document Formatting The document is formatted as requested and looks professional The document is generally formatted as requested, with 1 or 2 formatting errors The document has some formatting errors (3 to 4) which deter the effectiveness of the document The document has multiple formatting errors (5-7) which make the document look scattered The document has numerous formatting errors (more than 7) which make the document look scattered and unprofessionalStyle Correct elements of style are used. Correct elements have been applied all of the time. Correct elements have been applied most of the time. Correct elements have been applied some of the time. Correct elements are rarely or never used. Correct elements are never used.Spacing Correct elements of spacing are used. Correct elements have been applied all of the time. Correct elements have been applied most of the time. Correct elements have been applied some of the time. Correct elements are rarely or never used. Correct elements are never used.Margins Top, bottom and sides — are each time correct and appropriate for the assignment Top, bottom and sides — are often correct and appropriate for the assignment Top, bottom and sides — are sometimes correct and appropriate for the assignment Top, bottom and sides — are seldom correct and appropriate for the assignment Top, bottom and sides — are rarely correct and inappropriate for the assignmentBold Is used appropriately and correctly for the whole assignment. Is used appropriately and correctly for most of the assignment. Is used appropriately and correctly at times for the assignment. Is used appropriately but rarely for the assignment. Is used inappropriately and never for the assignment. Level of AchievementExcellent 5Good 4Average 3Adequate 2Need Improvement 1PointsFont Is used appropriately and correctly for the whole assignment. Is used appropriately and correctly for most of the assignment. Is used appropriately and correctly at times for the assignment. Is used appropriately but rarely for the assignment. Is used inappropriately and never for the assignment.Indentation Is used appropriately and correctly for the whole assignment. Is used appropriately and correctly for most of the assignment. Is used appropriately and correctly at times for the assignment. Is used appropriately but rarely for the assignment. Is used inappropriately and never for the assignment.Title/Heading Is used appropriately and correctly for the whole assignment. Is used appropriately and correctly for most of the assignment. Is used appropriately and correctly at times for the assignment. Is used appropriately but rarely for the assignment. Is used inappropriately and never for the assignment.Referencing Have only 1 error Have 2 to 3 errors Have 4 to 5 errors Have more than 5 errors Not implemented at allTOTAL /85 CSC 1215 BASIC COMPUTING RESEACH PRESENTATION RUBRIC CSC 1215 – RESEARCH PRESENTATION ASSESSMENT FORM VerbalAdvanced 4 Proficient 3Basic 2 Novice 1 Points1234Volume Speaker is heard by all in the classroom.Speaker is heard by most in the classroom.Speaker is heard by the front of the classroomSpeaker can hardly be heard.Articulation Speakers tone, volume, and manner of expression consistently reflect content of presentation.Speakers tone, volume, and manner of expression frequently reflects content of presentation.Speakers tone, volume, and manner of expression sometimes reflects content of presentation.Speakers tone, volume, and manner of expression rarely reflects content of presentation.Pronunciation Speaker pronounces all relevant words correctly.Speaker pronounces most relevant words correctly.Speaker pronounces some relevant words correctly.Speaker pronounces few relevant words correctly.Vocabulary Speaker consistently chooses words that reflect knowledge of subject and uses them appropriately.Speaker frequently chooses words that reflect knowledge of subject and uses them appropriately.Speaker sometimes chooses words that reflect knowledge of subject and uses them appropriately.Speaker seldom chooses words that reflect knowledge of subject and uses them appropriately./16/16/16/16 Non-VerbalAdvanced 4 Proficient 3Basic 2 Novice 1 Total1234Eye Contact Speaker consistently looks at audience.Speaker frequently looks at audience.Speaker sometimes looks at audience.Speaker hardly ever looks at audience.Body Language Gestures and stance of speaker consistently reflects content of presentation.Gestures and stance of speaker frequently reflects content of presentation.Gestures and stance of speaker sometimes reflects content of presentation.Gestures and stance of speaker rarely reflects content of presentation.Posture Speaker appears confident and dignified throughout entire presentation.Speaker appears confident and dignified throughout most of the presentation.Speaker appears confident and dignified throughout some of the presentation.Speaker seldom appears confident and dignified throughout presentation.Appearance Apparel enhances presentation. Apparel is appropriate for presentation. Apparel somewhat detracts from presentation.Apparel detracts from presentation./16/16/16/16ContentAdvanced 4 Proficient 3Basic 2 Novice 1 Total1234Knowledge of Content Speaker consistently demonstrates a depth of understanding of the content.Speaker frequently demonstrates a depth of understanding of the content.Speaker sometimes demonstrates a depth of understanding of the content.Speaker rarely demonstrates a depth of understanding of the content.Organization Speaker presents all content in a logical sequence.Speaker presents most content and mostly in a logical sequence.Speaker presents some of the content some of it in a logical sequence. Speaker presents limited content and in an illogical sequence.Supporting Detail Speaker consistently uses relevant and thorough supporting detail.Speaker frequently uses relevant and thorough supporting detail.Speaker sometimes uses relevant and thorough supporting detail. Speaker seldom uses relevant and thorough supporting detail.Making Connections Speaker consistently links material to curriculum and/or life experiences.Speaker frequently links material to curriculum and/or life experiences.Speaker sometimes links material to curriculum and/or life experiences.Speaker hardly links material to curriculum and/or life experiences./16/16/16/16 EffectivenessAdvanced 4 Proficient 3Basic 2 Novice 1 Total1234Timing/Pacing Speaker consistently regulates the speed of delivery.Speaker mostly regulates the speed of delivery.Speaker sometimes regulates the speed of delivery.Speaker did not regulate the speed of delivery.Introduction Presentation contains an effective and noticeable introduction.Presentation contains a noticeable introduction.Introduction is fair.Introduction is weak.Significance Presentation contains an effective and noticeable statement. Presentation contains a noticeable statement. Significance is fair.Significance is weak.Q and A Speaker always fields questions and comments accurately. Speaker frequently fields questions and comments accurately.Speaker sometimes fields questions and comments accurately. Speaker did not field questions and comments accurately./16/16/16/16VisualsAdvanced 4 Proficient 3Basic 2 Novice 1 Total1234Choice of visual type Speaker consistently choose best visual to use for display (e.g. graph, text, clip art).Speaker frequently choose best visual to use for display (e.g. graph, text, and clip art).Speaker sometimes choose best visual to use for display (e.g. graph, text, and clip art).Speaker do not choose best visual to use for display (e.g. graph, text, and clip art).Choice of color/font/ backgroundSpeaker consistently choose best color/font size/background.Speaker frequently choose best color/font size/background.Speaker sometimes choose best color/font size/ background.Speaker do not choose best color/font size/ background.Amount of text informationSpeaker consistently used key words, bullet points, numberingSpeaker frequently used key words, bullet points, numberingSpeaker sometimes used key words, bullet points, numberingSpeaker do not used key words, bullet points, numberingUse of graphs/tables Speaker consistently labeled information and presented the right amount of data.Speaker frequently labeled information and presented the right amount of data.Speaker sometimes labeled information and presented the right amount of data.Speaker do not labeled information and do not presented the right amount of data./16/16/16/16 STUDENTS12345Report Marks /85/85/85/85/85Equivalent 10Presentation Marks /80/80/80/80/80Equivalent 5Total Assignment Marks (15)/15/15/15/15/15 CSC 1215 BASIC COMPUTING Group Assignment Form a team (a group of 4-5 members) and conduct a research on the following topics. Each group will be assigned one (1) research topic and each group member is required to present in the presentation. The research presentation, will be structured as a formal knowledge sharing session. New and Emerging Technology Emerging technology is a new technology that is currently being developed, or will be developed within the next several years. Following are several key emerging technology topics Internet of Things (IoT) Artificial Intelligence (AI) Immersive Experiences Big Data Chatbots Blockchain Cloud Computing Data Analytics Deep Learning (Neural Network) Cognitive Computing Your task is to conduct a research on a selected topic and develop an understanding of the underlying technology what it is, how does it work, what existing technologies does it replace and how it differs, and what are the set of components / elements establish the emerging technology Who are the inventor(s) or originator(s) of the emerging technology and / or related sub-technologies What are the advantages and likely disadvantages of this new technology for the businesses, organizations and communities alike How will it change business practice or user activity – and in what areas or industries As a guideline, your research report and presentation should cover The description and definition of the emerging technology topic The overview discussion of the emerging technology topic The current / latest development of the emerging technology topic The future outlook of the emerging technology topic The overall impact of the emerging technology topic Marking Scheme This assignment carries 15 of the overall coursework. Your assignment must include the following Assignment Cover Page Assignment Marking Scheme Assignment Question Acknowledgement Table of Content List of Figures List of Table Conclusion List of References Appendices Presentation slides Requirements This is a Group Assignment 4 to 5 students per group. Font size 12. Font Style Times New Roman. All paragraphs must be fully Justified (CTRL J) with 1.5 Line Spacing. Main Title Case Times New Roman, size 16. All heading should have the Title Case, BOLD and Left-Alignment, Times New Roman, size 14, and must use PROPER NUMBERING Do not ITALIC. Your report must be printed in A4 Size, only WHITE PAPER accepted. Minimum pages are 20 pages not including the Table of Content, List of Tables, List of Figures, References and Appendices. Between Main Title Case and Title Case No NEED ENTER key. Between Paragraphs ENTER key 2X. Between Title Case and Table or Figure ENTER key 2X. Between Table or Figure and Paragraph ENTER key 2X. Remember to spell check your report. All FIGURES must with same HEIGHT 6 cm and WIDTH 17.25 cm. All FIGURES, FIGURE NAME and FIGURE NUMBERING must be placed in the CENTER. All FIGURES must contain NAME and NUMBER – Times New Roman, size 10, and must use PROPER NUMBERING. All TABLES, TABLE NAME AND TABLE NUMBERING must be placed in the CENTER. All TABLES must contain NAME and NUMBER. Please use the report TEMPLATE / SAMPLE provided in the next pages. Cover page must be TYPED (NAME, MATRICULATION NUMBER and RESEARCH REPORT TITLE). Report must be properly BINDING. Please follow the Harvard referencing style for your references. Citations must be included wherever necessary. You must upload the softcopy of your FIRST DRAFT report on Blackboard Safe Assign software for plagiarism checking. The acceptable percentage for the similarity report is NOT MORE THAN 20. Subsequently when accepted, you will need to upload the FINAL DRAFT of your report for record purposes. Your slides should be INFORMATIVE for the audience. Printing format of presentation slides handouts 6 SLIDES PER PAGE PURE BLACK WHITE. attach together with your report in the Appendices section Due date Week 6 6TH July 2018 (FRIDAY) before 5.00 PM to Faculty of Business, Communications and Law (FOBCAL) (Any late assignment will not be tolerated). Presentation Week 7. Note Any information from Wikipedia and Ask.com is not allowed. ACKNOWLEDGEMENT Table of Contents TOC o 1-3 h z u HYPERLINK l _Toc517969754 1. Introduction PAGEREF _Toc517969754 h 1 HYPERLINK l _Toc517969755 1.1. Definition of Big Data PAGEREF _Toc517969755 h 1 HYPERLINK l _Toc517969756 1.1.1. History of Big Data PAGEREF _Toc517969756 h 2 HYPERLINK l _Toc517969757 1.1.2. Categories of Big Data PAGEREF _Toc517969757 h 2 HYPERLINK l _Toc517969758 1.1.3. Structured Data PAGEREF _Toc517969758 h 2 HYPERLINK l _Toc517969759 1.1.4. Semi-Structured Data PAGEREF _Toc517969759 h 2 HYPERLINK l _Toc517969760 1.1.5. Unstructured Data PAGEREF _Toc517969760 h 3 HYPERLINK l _Toc517969761 1.1.6. Volume in Big Data PAGEREF _Toc517969761 h 3 HYPERLINK l _Toc517969762 1.1.7. Velocity in Big Data PAGEREF _Toc517969762 h 4 HYPERLINK l _Toc517969763 1.1.8. Variety in Big Data PAGEREF _Toc517969763 h 4 HYPERLINK l _Toc517969764 1.2. PAGEREF _Toc517969764 h 4 HYPERLINK l _Toc517969765 1.2.1. PAGEREF _Toc517969765 h 4 HYPERLINK l _Toc517969766 1.2.2. PAGEREF _Toc517969766 h 4 HYPERLINK l _Toc517969767 1.2.3. PAGEREF _Toc517969767 h 4 HYPERLINK l _Toc517969768 1.2.4. PAGEREF _Toc517969768 h 5 HYPERLINK l _Toc517969769 1.2.5. PAGEREF _Toc517969769 h 5 HYPERLINK l _Toc517969770 2. Big Data PAGEREF _Toc517969770 h 6 HYPERLINK l _Toc517969771 2.1. How Big Data Works PAGEREF _Toc517969771 h 6 HYPERLINK l _Toc517969772 2.2. Elements Implemented in Big Data PAGEREF _Toc517969772 h 6 HYPERLINK l _Toc517969773 2.3. Source of Big Data PAGEREF _Toc517969773 h 6 HYPERLINK l _Toc517969774 2.4. The Importance of Big Data PAGEREF _Toc517969774 h 6 HYPERLINK l _Toc517969775 2.5. Applications of Big Data in Various Industries PAGEREF _Toc517969775 h 7 HYPERLINK l _Toc517969776 2.5.1. Banking and Finance Firm PAGEREF _Toc517969776 h 7 HYPERLINK l _Toc517969777 2.5.2. Health Industry PAGEREF _Toc517969777 h 8 HYPERLINK l _Toc517969778 2.5.3. Retail Industry PAGEREF _Toc517969778 h 8 HYPERLINK l _Toc517969779 2.5.4. Manufacturing Industry PAGEREF _Toc517969779 h 8 HYPERLINK l _Toc517969780 2.5.5. Entertainment Industry PAGEREF _Toc517969780 h 8 HYPERLINK l _Toc517969781 2.5.6. Political Industry PAGEREF _Toc517969781 h 8 HYPERLINK l _Toc517969782 2.5.7. Weather Industry PAGEREF _Toc517969782 h 8 HYPERLINK l _Toc517969783 2.5.8. Advertising PAGEREF _Toc517969783 h 8 HYPERLINK l _Toc517969784 2.6. Disadvantages of Big Data PAGEREF _Toc517969784 h 8 HYPERLINK l _Toc517969785 3. Future Scope for Big Data PAGEREF _Toc517969785 h 9 HYPERLINK l _Toc517969786 3.1. Challenges in Implementation of Big Data PAGEREF _Toc517969786 h 9 HYPERLINK l _Toc517969787 3.2. PAGEREF _Toc517969787 h 9 HYPERLINK l _Toc517969788 3.2.1. PAGEREF _Toc517969788 h 9 HYPERLINK l _Toc517969789 3.2.2. System Packages PAGEREF _Toc517969789 h 9 HYPERLINK l _Toc517969790 3.3. PAGEREF _Toc517969790 h 9 HYPERLINK l _Toc517969791 3.3.1. PAGEREF _Toc517969791 h 9 HYPERLINK l _Toc517969792 3.3.2. PAGEREF _Toc517969792 h 9 HYPERLINK l _Toc517969793 3.4. PAGEREF _Toc517969793 h 10 HYPERLINK l _Toc517969794 3.4.1. PAGEREF _Toc517969794 h 10 HYPERLINK l _Toc517969795 3.4.2. PAGEREF _Toc517969795 h 10 HYPERLINK l _Toc517969796 3.4.3. PAGEREF _Toc517969796 h 10 HYPERLINK l _Toc517969797 3.4.4. PAGEREF _Toc517969797 h 10 HYPERLINK l _Toc517969798 3.4.5. PAGEREF _Toc517969798 h 10 HYPERLINK l _Toc517969799 3.5. PAGEREF _Toc517969799 h 10 HYPERLINK l _Toc517969800 3.5.1. PAGEREF _Toc517969800 h 10 HYPERLINK l _Toc517969801 3.5.2. PAGEREF _Toc517969801 h 10 HYPERLINK l _Toc517969802 3.5.3. PAGEREF _Toc517969802 h 10 HYPERLINK l _Toc517969803 3.5.4. PAGEREF _Toc517969803 h 10 HYPERLINK l _Toc517969804 3.5.5. PAGEREF _Toc517969804 h 10 HYPERLINK l _Toc517969805 4. References PAGEREF _Toc517969805 h 11 HYPERLINK l _Toc517969806 4.1. Websites PAGEREF _Toc517969806 h 11 HYPERLINK l _Toc517969807 4.2. Books PAGEREF _Toc517969807 h 11 HYPERLINK l _Toc517969808 5. Appendices PAGEREF _Toc517969808 h 12 List of Figures TOC h z c Figure HYPERLINK l _Toc463118317 Figure 1.1 Complete System Module Breakdown PAGEREF _Toc463118317 h 1 HYPERLINK l _Toc463118318 Figure 1.2 Rapid Prototyping Lifecycle with Software Versioning PAGEREF _Toc463118318 h 1 HYPERLINK l _Toc463118319 Figure 2.1 EXAMPLE Top Level System Diagram PAGEREF _Toc463118319 h 3 HYPERLINK l _Toc463118320 Figure 3.1 System Level Class Digram PAGEREF _Toc463118320 h 6 HYPERLINK l _Toc463118321 Figure 3.2 System Level Package Diagram PAGEREF _Toc463118321 h 6 List of Tables TOC h z c Table HYPERLINK l _Toc463118322 Table 1.1 Module Development Responsibilities PAGEREF _Toc463118322 h 2 HYPERLINK l _Toc463118323 Table 2.1 System Sizing Limitations PAGEREF _Toc463118323 h 5 HYPERLINK l _Toc463118324 Table 2.2 System Timing Targets PAGEREF _Toc463118324 h 5 Introduction Definition of Big Data Commonly, the first thing that surfaces to mind whenever we hear, Big Data is size. Although size is a characteristic to take note of, our progressing technology has raised diverse views on what big data is. From the standpoint of the industrial section, Gartner describes the term as being a high volume/high velocity and/or high variety information assets that demand cost-effective, innovative forms of information processing that enables enhanced insight, decision making and process automation (Gartner, n.d.). Similarly, International Data Corporation (IDC) defines big data as a new generation of technologies and architectures, designed to economically extract value from very large volumes of a wide variety of data, by enabling high velocity capture, discovery, and/or analysis. (Reinsel, 2012) In addition to that, the largest computer company in the world, International Business Machines (IBM), has proposed that big data is a term applied to data sets whose size or type is beyond the capacity of traditional relational databases to capture and process data with low latency. IBM has prescribed three attributes that characterize big data. (Analytics, n.d.) The three points are as follows Volume Velocity Variety These characteristics are globally recognized as the Vs of big data. The concept has been introduced by none other than Gartner analyst, Doug Laney. These Vs will be further elaborated in Section 1.3. History of Big Data Big data emerge in the IT world in the first decade of the 21st century. Organizations such as Google, Facebook, E-Bay as well as other online startup firm where the first group to embrace big data. They are said to build mainly around big data from the beginning. Big data emerge in the IT world in the first decade of the 21st century. Organization such as Google, Facebook, E-Bay as well as other online startup firm where the first group to embrace big data. They are said to build mainly around big data from the beginning. Big data refers to the massive, more complex data sets. These data sets are so voluminous which typically consisting up to billions and trillion of records that traditional data processing software are not able to manage them. Every excess of application in our smartphone is a complex operation. Every excess of WhatsApp, Facebook, Amazon or any other social media site automatically produces data and leaves train of information behind. Every data coming are in rapid rate, all from different resources and coming in real time. This is big data. Types of Big Data In order to understand how big data works and the concept of said technology, we must first educate ourselves on the various forms of big data there are. As of today, we have three types of big data which include structured data, semi-structured data and also unstructured data. These three types of data will be further discussed in the next section. Structured Data In simple words, structured data refers to any form of data that is capable of being stored, accessed and processed in an orderly manner. There are two origins of this particular data which are from humans and machines. Machine generated data include GPS data Medical data Financial programs Human generated data is technically data a user inputs into a computer. The most common examples would be personal details and passwords. Data is generated through clicks and movement in games. All this data produced is used by organizations to make modifications for customer satisfaction (Editor, 2016). Semi-Structured Data Semi-structured data is basically a combination of both structured and unstructured data. (Editor, 2016) Unstructured Data Unstructured data is basically the opposite of structured data. Unlike structured data, unstructured data is not processed nor accessed in an orderly manner. Unstructured data is the most common data we will all encounter. It is mainly used to store and analyze manually. Unstructured data is also categorized based on its source. Machine-generated data includes satellite images, scientific data from a variety of experiments and radar data obtained by various facets of technology. Human-generated data can be found abundantly across the web. This is due to the fact that it consists of social media data, mobile data and internet data/content. since it includes social media data, mobile data and website content. This means that the photos we upload or store in Facebook and the videos we click on YouTube all the time contributes to the massive collection of unstructured data. Hence, a type of big data (Editor, 2016). Characteristics of Big Data Volume in Big Data Volume refers to the magnitude of data generated and stored. Big data sizes range from a petabyte to a zettabyte. Despite the massive range, the volume of big data remains a subjective topic. What may appear as big data today may not be deemed the same subsequently. This is because our technology is constantly expanding. With our technology advancing daily, storage capacities would boost too. This enables us to collect larger datasets. Furthermore, the dimension of volume in big data cannot be determined quantitively. Basically, the volume of data relies on the industry and its applications (Amir Gandomi, 2015). This is why we have no specific definition when it comes to characterizing big data it is very subjective. Velocity in Big Data Velocity is a measure of data rate and flow. Data rate refers to the number of digital bits per second that are recorded or retrieved from a data storage device during the transfer of a large data block whereas data flow in terms of computing is the transfer of data from an external storage device, through the processing unit and memory, and out to an external storage device. (Hill, 2003) The velocity dimension also refers to the capability of understanding and responding to events as they occur. This enables us to gain knowledge of both past happenings and also real-time happenings in the blink of an eye (Sonka, 2016). A perfect example would be Waze, an application one can get on Google Store in smartphones. With the help of big data and its analytics, Waze is able to provide real-time traffic status. It also analyzes real-time traffic flow and provides alternative routes if traffic is too heavy. Hence, allowing us to reach our destination smoothly in due time. All this is possible because of big data. Variety in Big Data Lastly, variety refers to the numerous types of data we can now utilize. In the older days, structured data is the general trend when it comes to forms of data. This is due to its convenience in keying in data neatly into tables and relational databases. For example, keying in financial data. Due to the vast enhancement of technology, 80 of the worlds data is unstructured and unlike before, cannot be easily modified or inserted into tables. With big data technology, we are able to harness different types of data and compile them together with more advanced, traditional data regardless of it being structured or not. This includes messages, social media conversations, sensor data or voice notes (Amir Gandomi, 2015). Big Data How Big Data Works Elements Implemented in Big Data Source of Big Data The Importance of Big Data Big data plays a vital role in various industries all over the world. Due to its sophisticated analytics, this data comes in handy when it comes down to decision making. This is because big data enables one to gain eloquent value by making information precise and usable at better prevalence. Furthermore, accurate and detailed results can be obtained easily as organizations generate and store more transactional data. The following figure shows the usage of big data in various industries. Applications of big data in the industries below shall be further discussed in the next section. Figure SEQ Figure ARABIC 1.0 Big Data in Various Industries Applications of Big Data in Various Industries Previously, we have seen some of the reasons that make big data a relevant factor in organizations. In this section, we shall be taking an in depth look at how big data is implemented/applied in different industries worldwide. Banking and Finance Firm One of the most important uses of big data in the banking and finance industry is fraud detection. The imposition of big data analytics in banking and finance firms allows us to define usual activity based on a customers history and segregate it from unethical behavior which commonly signifies deception. With this data administered in the industry, fraudulent interactions can be easily subjugated. Hence, improving profitability (Advisor, n.d.). Other than fraud detection, this firm also uses big data for customer segmentation. According to the Business Dictionary on Google, customer segmentation refers to the act of dividing customers into groups that share similar interests and characteristics from a marketing or demographic perspective. Understanding these groups is essential in order to form a solid base for sales and marketing. With the aid of big data, sharper segments are able to be created in due time. These segments are specified by datasets which include customers demographics, daily transactions, communication with customer service systems and also home value. Based on the data accumulated, profitable groups can then be targeted to customers to raise the bar of contentment (Advisor, n.d.) Healthcare and Medicine Commonly, the first thing that comes to mind at the mention of health industry would be medicine. It is vital to prescribe the right medicine according to a patients needs or the outcomes would be disastrous. This is where big data comes into the picture. The methodical collection and analysis of genetic data in combination with various infections, remedies and after effects allows us to select the best treatments without causing harm to patients. (Subgroup, 2016) Government Sector Big data is one of the tools this particular sector makes practical use of with the aim to combat terrorist acts. In 2012, the government launched Neptune and Cerberus. According to Ingram Micro Advisor, Neptune is a data lake of unclassified statistics labelled with data tags to maintain access and safeguard personal privacy. On the other hand, Cerberus refers to a data lake of classified information consisting of more rigid safety regulations. By combining these two, the Department of Homeland Security is able to conduct analytics to pinpoint acts that pose as a threat and predict sources that are most likely to contribute to domestic terrorism. (Advisor, n.d.) Furthermore, the government sector uses big data in enforcing the law. By assessing relationships between people, locations and other influences, a shocking 50 reduction in crime rate was recorded in Durham, North California in a two-square-mile area. To make the police department more productive, tallying census data and community records is strongly encouraged. For instance, it would be more convenient to acquire manpower requirements and patrol routes if we cross-reference zoning applications for liquor licenses, new construction site sites prone to thefts, and the launching of new retail centers. (Advisor, n.d.) Manufacturing Industry The manufacturing industry was one of the earlier sectors to utilize big data for the sake of efficiency, embracing information technology and automation to blueprint, build, and hand out products since the early ages of the computer era. In the 1990s, manufacturing companies bagged up outstanding profit with the assistance of big data. Media and Entertainment The media and entertainment industry has been favored by many people worldwide. Till this day, this sector stands as one of the most successful. A popular entertainment site on the web these days would be Netflix. It is a site where users can stream videos and movies. Netflix has become one of the largest streaming sites globally after making practical use of big data. Basically, Netflix gathers data such as ratings, reviews and clicks before processing them altogether. A system in Netflix called the Video-Video Similarity Algorithm estimates and gives out recommendations on what a user may like based on the history or stated preferences of his/her watched videos. (Team, 2018) Political Sector Weather Industry Advertising Disadvantages of Big Data Future Scope for Big Data Challenges in Implementation of Big Data System Packages References Websites Books Appendices CSC1215 / MAY 2018 PAGE MERGEFORMAT xii CSC1215 / MAY 2018 m)[email protected]_Kme23f6dws_5g6mCjn3oEoky5bb8kL(K0/w)7iu.pn9x 6tjf/vaiW AUWOyeGMKOWGX08Oi_zN 5/7bpcHkijDYrDj zJixU4jfd6Sr7AnRrkfVxW5X3zSxd.DD8b,/fvP Tv5e– kEFObp75KCfN([email protected] MYyerj6crunTi 0szA_p.7qA
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