BSc Business Information Systems

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BCO5010: Business Intelligence Technologies (Assignment 1)CARDIFF SCHOOL OF MANAGEMENT: ASSIGNMENT FEEDBACK PROFORMASTUDENT NAME:PROGRAMME: BSc Business InformationSystems/BSc Software Development/ BScComputingSTUDENT NUMBER:YEAR: 1GROUP:Module Number: BCO5010Term: 1Module Title: Business IntelligenceTechnologiesTutor Responsible For Marking This Assignment: Imtiaz KhanModule Leader: Imtiaz KhanAssignment Due Date: 18 Dec 2016 (viaMoodle)Hand In Date:ASSIGNMENT TITLE: Analysis of locational social media data (Assignment 1)42.5% of totalmarksSECTION A: SELF ASSESSMENT (TO BE COMPLETED BY THE STUDENT)In relation to each of the set assessment criteria, please identify the areas in which you feel youhave strengths and those in which you need to improve. Provide evidence to support your self-assessment with reference to the content of your assignment.STRENGTHSAREAS FOR IMPROVEMENTI certify that this assignment is a result of my own work and that all sources have beenacknowledged:Signed:______________________________________________Date___________________________SECTION B: TUTOR FEEDBACK(based on assignment criteria, key skills and where appropriate, reference to professionalstandards)STRENGTHSAREAS FOR IMPROVEMENT AND TARGETSFOR FUTURE ASSIGNMENTSMARK/GRADE AWARDEDDATE:SIGNEDASSIGNMENT MODERATED BY:DATE
BCO5010: Business Intelligence Technologies (Assignment 1)MODERATOR’S COMMENTS:1. Learning outcomesBy completing this assignment the student will learn aboutSocial media data analysis with Excel and creating dashboard for reporting.Apply OLAP approach in conjunction with database for reporting.Design, program and link social media data with geospatial data.Critical analysis and evaluation of results.2. Assignment outline and guidance notesAnalysis of locational social media dataCase study: Monmouthshire County CouncilOutline:Monmouthshire County Council (MCC) would like to increase their organisational understanding andpotential impact of existing and potential online networks. They are pioneering a more relaxed andinformal approach to talking with residents and developing relationships with other stakeholders. Aspart of its programme of culture change (outlined here: the council isempowering staff and residents toinnovate and find new ways of co-creating a better place to live.MCC have now conducted a pilot study to find out the opinions of council residents and havegathered a large dataset of social media data. They asked residents to describe how they thoughtMCC could best improve their services. MCC were not only interested in the topics broached, butalso the style of the respondents’ narrative. They developed some calculated fields, and now theyhave asked you to finish off the analysis of their data and report on your analysis.A detailed summary of the data can be found in Appendix A, however in summary it contains thefollowing:
BCO5010: Business Intelligence Technologies (Assignment 1)FieldsExplanationidUnique ID for residentformality, flesch, fog, kincaid,percentComplexWords,syllablesPerWords, wordsPerSentence,wordcountA series of fields all related to the structure and style of theresidents responsesexSex of the residentextraversion, emotional stability,agreeableness, conscientiousness,openness to experienceA series of fields corresponding to the“Big 5” personalitytraitslongitude/latitudeGeographical location of residenteducation, jobs and employment,recycling and waste, buses and publictransport, planning and housing, care andsupport, activities and leisureThe topics the resident mentioned.You have been provided an Excel spreadsheet with several thousand rows of data (each row is aunique resident), in the above format. Additionally you have access to KML files for Gwent boundaryand neighbourhoods.2.1 Assignment tasks:Statistical analysis [20%]Using the Excel spreadsheet:Create a dashboard to view a selection of the data in a more synthetic and operationallyuseful way.A table showing the mean and standard deviation for each featureAny appropriate functions in Excel (e.g. frequency distributions and polygons, overlaying‘curves of best fit’ etc) to explore:oM1 versus literacy fieldsoM1 versus M2 and/or M3oAny significant relationships between M4, M5, M6 and M7OLAP [20%]Import the data from the spreadsheet into an Access database.Create two appropriate queries and supporting reports.Using PowerPivot1(or any other tool suitable for the version of Microsoft Office) create anyappropriate OLAP cubes2in Excel using the Access database as the data source1
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