{"id":30939,"date":"2026-05-03T17:59:15","date_gmt":"2026-05-03T17:59:15","guid":{"rendered":"https:\/\/academicwritersbay.com\/solutions\/job-description-you-might-maybe-almost-definitely-almost-definitely-also-very-well-be-a-knowledge-engineer-tasked-with-designing-and-enforcing-a-proof-of-thought-enormous-knowledge-analytics-solutio\/"},"modified":"2026-05-03T17:59:15","modified_gmt":"2026-05-03T17:59:15","slug":"job-description-you-might-maybe-almost-definitely-almost-definitely-also-very-well-be-a-knowledge-engineer-tasked-with-designing-and-enforcing-a-proof-of-thought-enormous-knowledge-analytics-solutio","status":"publish","type":"post","link":"https:\/\/academicwritersbay.com\/solutions\/job-description-you-might-maybe-almost-definitely-almost-definitely-also-very-well-be-a-knowledge-engineer-tasked-with-designing-and-enforcing-a-proof-of-thought-enormous-knowledge-analytics-solutio\/","title":{"rendered":"Job Description: You might maybe almost definitely almost definitely also very well be a Knowledge Engineer tasked with designing and enforcing a proof- of thought Enormous Knowledge analytics solution for a metropolis's transport authority. Scenario: The metropolis council needs to analyse urban mobility patterns the utilize of"},"content":{"rendered":"

DEGREE: BSc Laptop Science and Digitisation<\/strong><\/p>\n

Module: Enormous Knowledge Analytics the utilize of AI<\/strong><\/p>\n

Assignment Title: SmartCity Metropolis Mobility Analysis the utilize of Hadoop and<\/strong><\/p>\n

Predictive AI<\/strong><\/p>\n

Assignment Form: <\/strong>Document<\/p>\n

Word Restrict: 3000 phrases (+\/- 300)<\/strong><\/p>\n

Weighting: 100%<\/strong><\/p>\n

Project Date: 4\/9\/2025<\/strong><\/p>\n

Submission Date: 30\/9\/2025<\/strong><\/p>\n

Feedback Date: 21\/10\/2025<\/strong><\/p>\n

<\/figure>\n

Plagiarism:<\/strong><\/p>\n

When submitting work for overview, students needs to be responsive to the<\/p>\n

InterActive\/Canvas guidance and regulations in referring to plagiarism. All submissions needs to be your individual, normal work. Please enlighten that it’s top to no longer put up the identical project for two various modules within your route.<\/p>\n

It be important to put up an electronic copy of your work. Your submission shall be electronically checked.<\/strong><\/p>\n

<\/figure>\n

Harvard Referencing:<\/strong><\/p>\n

The Harvard Referencing Machine also can neutral quiet be historical. The Wikipedia, UKEssays.com or identical net sites must no longer <\/strong>be historical or referenced to your work.<\/p>\n

Introduction<\/strong><\/p>\n<\/p>\n

The aim of this project is to offer you with arms-on skills in designing and enforcing a Enormous Knowledge analytics solution that contains a predictive AI component. You might maybe cope with a hypothetical trim metropolis order by the utilize of the Hadoop ecosystem to route of mountainous-scale recordsdata and gain actionable insights for urban planning. This project requires you to invent an answer the utilize of Hadoop, HDFS, YARN, and MapReduce<\/strong> to analyse transportation recordsdata. The final step entails the utilize of the processed recordsdata to prepare a easy predictive model, thereby connecting Enormous Knowledge processing with AI functions. This enable you to know the finish-to-finish pipeline from raw recordsdata to industry intelligence in a up-to-the-minute context.<\/p>\n

Scenario:<\/strong> The metropolis council needs to analyse urban mobility patterns the utilize of recordsdata from twin carriageway sensors, taxi journeys, or public transit data. The neutral is to title congestion hotspots, perceive their causes, and predict future web page visitors patterns to enable proactive web page visitors administration and better infrastructure planning.<\/p>\n

Phase 1: Conceptual Assemble & Architecture (LO 1, LO 2) – 20% of Total Grade<\/strong><\/p>\n

1.\u00a0 Exchange Context and Order Assertion (5%)<\/strong><\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Picture the trim metropolis subject, focusing on the challenges of urban mobility.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Clarify a transparent subject assertion. As an instance: “To analyse historical web page visitors recordsdata to predict the probability of web page visitors congestion at key intersections in retaining with time of day and day of the week”.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Show how solving this subject presents tangible cost to the metropolis (e.g., reduced commute instances, lower air pollution, improved public security).<\/p>\n

2.\u00a0 Hadoop Ecosystem and Architecture (15%)<\/strong><\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Show why a Enormous Knowledge manner is excessive for this subject.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Name the roles of HDFS, YARN, and MapReduce to your proposed solution.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Define your need of those substances for the defined subject.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Build a transparent architectural scheme illustrating how recordsdata flows from offer to HDFS, is processed by MapReduce managed by YARN, and is then historical for prognosis.<\/p>\n

Phase 2: Implementation & Analysis (LO 3) – 50% of Total Grade<\/strong><\/p>\n<\/p>\n

1.\u00a0 Knowledge<\/strong> Acquisition & Preparation (5%)<\/strong><\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Pick out a appropriate public dataset representing urban mobility (e.g., taxi day out data, web page visitors sensor recordsdata). Platforms love Kaggle or metropolis-philosophize open recordsdata portals are correct sources.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Picture the dataset’s constructing, size, and key attributes connected to your subject assertion.<\/p>\n

2.\u00a0 Hadoop Atmosphere and Knowledge Ingestion (10%)<\/strong><\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Region up an arena single-node Hadoop cluster (e.g., the utilize of the official Apache Hadoop binaries or a Docker image).<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Doc the important steps of your setup route of.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Load your chosen dataset into HDFS. Provide the instructions and screenshots showing the options successfully saved in HDFS.<\/p>\n

3.\u00a0 Knowledge Processing with MapReduce (20%)<\/strong><\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Write a MapReduce program in Java or Python to route of the options. Your programmust form recordsdata cleansing and feature engineering to situation up it for the predictive model.<\/p>\n

Instance tasks: calculate common day out length per route, count automobile waft per\u2022 <\/sub>hour, or title various connected beneficial properties from the raw recordsdata.<\/p>\n

\u2022Show the common sense of your Mapper and Reducer classes and consist of the well- commented offer code to your document’s appendix.<\/p>\n

4.\u00a0 Predictive Analysis and Visualization (15%)<\/strong><\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Export the processed recordsdata from HDFS.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Utilize the processed recordsdata to prepare a easy predictive model. You might maybe almost definitely almost definitely also utilize a library love Scikit-learn in Python to produce a classification or regression model that addresses your subject assertion.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Analyze and interpret the output of your MapReduce job and your predictive model.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Build meaningful visualizations (e.g., graphs showing congestion by time of day, a confusion matrix for your model) to original your findings.<\/p>\n

Phase 3: Reflection and Documentation (LO 1, LO 2, LO 3) – 30% of Total Grade<\/strong><\/p>\n

1.\u00a0 Serious Reflection (10%)<\/strong><\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Reflect on the important challenges you encountered all the intention thru implementation (e.g., recordsdata cleansing, debugging MapReduce, model accuracy) and how you addressed them.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Seriously discuss the performance and scalability of your MapReduce solution.<\/p>\n

Could well well it be optimized (e.g., by the utilize of a Combiner)?<\/p>\n

2.\u00a0 Closing Document Documentation (20%)<\/strong><\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Assemble an intensive, reliable document of no bigger than 3000 phrases documenting the total challenge.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 The document also can neutral quiet be well-structured with certain headings, honest grammar, and academic language.<\/p>\n

\u2022 <\/p>\n

Be sure that all phases (Conceptual Assemble, Implementation, Reflection) are thoroughly coated, including diagrams, code snippets, instructions, and visualizations to beef up your work.<\/p>\n

\u2022\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Encompass a bibliography the utilize of the Harvard referencing model.<\/p>\n

<\/strong><\/p>\n

Submission Pointers:<\/strong><\/p>\n

\u2022 Doc Format:<\/strong> Put up your project as a single doc following theBSBI project template equipped in Canvas.<\/p>\n

\u2022 Writing Quality:<\/strong> Be sure that certain and concise writing with honest grammar and spelling. Utilize headings and subheadings to prepare your work logically in accordance with the tasks outlined above.<\/p>\n

\u2022 Visuals<\/strong>: Encompass visuals love diagrams (route of waft, conceptual model sketches), tables (recordsdata assumptions, outcomes), and graphs (simulation output) where acceptable to enhance determining.<\/p>\n

\u2022 Job Protection:<\/strong> Take care of every segment thoroughly, demonstrating your determining of Enormous Knowledge ideas and their utility to the industry subject.<\/p>\n

\u2022 Implementation Famous beneficial properties:<\/strong> Provide connected examples and annoying beneficial properties of your model implementation, including code snippets, instructions, and calculations.<\/p>\n

\u2022 Referencing Fashion:<\/strong> Utilize Harvard referencing model for your bibliography.<\/p>\n

\u2022 Discussion:<\/strong> Speak about your findings, insights, and the implications of your options. Reflect on the challenges confronted and how you overcame them.<\/p>\n

\u2022 Submission:<\/strong> Put up your project electronically (Canvas) by the specified deadline.<\/p>\n

GUIDANCE ON ASSESSMENT<\/strong><\/p>\n

All supplies also can neutral quiet be successfully referenced under Harvard conventions. The length required is 3000 phrases with tasks equally weighted. The writing model needs to be formal academic \/ document writing model with in-text referencing to beef up your feedback and observations. Originality, quality of argument and proper constructing are required. The document also can neutral quiet demonstrate sound determining and skill to prepare knowledge and belief of Simulation Systems. Extra marks being awarded for juxtaposition and perception of components.<\/p>\n

Grading Criteria<\/strong><\/p>\n

Generic Criteria \u00a0\u00a0\u00a0\u00a0\u00a0 90 – 100<\/strong><\/p>\n

<\/figure>\n

Knowledge of contexts, ideas, applied sciences and <\/strong>Distinctive breadth and<\/p>\n

processes <\/strong>depth of recordsdata of<\/p>\n

The extent to which: \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 contextual and theoretical<\/p>\n

components, some of that are connected contextual or theoretical <\/em>on the forefront of the components are identified, defined and <\/em>discipline, and their described<\/em><\/p>\n

relationship to heaps of<\/p>\n

historical or up-to-the-minute <\/em>historical and practices are identified, defined <\/em>up-to-the-minute practices and described<\/em><\/p>\n

acceptable applied sciences,<\/em><\/p>\n

methods and processes are <\/em>Distinctive knowledge of identified defined and described<\/em> heaps of connected specialist ways and processes<\/p>\n

Figuring out thru <\/strong>Distinctive utility of utility of recordsdata <\/strong>heaps of research The level to which research \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 methodologies to tasks methods are demonstrated: \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 and problems and hypotheses, with evidence connected knowledge and <\/em>of highly targeted recordsdata is in comparison, <\/em>neutral conception and contrasted, manipulated, <\/em>some original insights into translated and interpreted <\/em>the subject knowledge and data is<\/em><\/p>\n

chosen, analysed, synthesized and evaluated in teach to <\/em>Distinctive capacity to<\/p>\n

generate inventive options, practices, <\/em>place heaps of<\/p>\n

alternatives, arguments or <\/em>inventive practices and to hypotheses <\/em>critically evaluate them in<\/p>\n

a wider context, generating sustainable arguments and highly efficient and individual outcomes<\/p>\n

80 – 89<\/strong><\/p>\n

Excellent breadth and depth of recordsdata of contextual and theoretical components, some of that are on the forefront of the discipline, and their relationship to heaps of historical and up-to-the-minute practices<\/p>\n

Intensive knowledge of heaps of connected specialist ways and processes<\/p>\n

Systematic and thorough utility of heaps of research methodologies<\/p>\n

to tasks and problems and hypotheses, with evidence of highly targeted neutral conception and a few original insights into the subject<\/p>\n

Excellent capacity to place heaps of inventive practices and to critically evaluate them in a wider context , generating sustainable arguments and highly efficient and normal outcomes<\/p>\n

70 – seventy nine<\/strong><\/p>\n

A breadth and depth of recordsdata of contextual and theoretical components, some of that are on the forefront of the discipline, and their relationship to heaps of historical and up-to-the-minute practices<\/p>\n

Famous knowledge of heaps of connected specialist ways and processes<\/p>\n

Rigorous utility of heaps of research methodologies to tasks , problems and hypotheses with evidence of highly targeted neutral conception and<\/p>\n

excessive prognosis<\/p>\n

Sturdy capacity to place heaps of inventive practices and to critically evaluate them in a wider context, generating sustainable arguments and highly<\/p>\n

efficient outcomes<\/p>\n

60 – 69<\/strong><\/p>\n

Confident knowledge of heaps of contextual and theoretical components, some of that are on the forefront of the discipline, and their relationship to heaps of historical and up-to-the-minute practices<\/p>\n

Confident knowledge of heaps of connected specialist ways and processes<\/p>\n

Confident capacity to prepare heaps of research methodologies to tasks, problems and hypotheses with certain evidence of neutral conception and excessive prognosis<\/p>\n

Sturdy capacity to place heaps of inventive practices and to judge them in a wider context , generating efficient outcomes<\/p>\n

50 – 59<\/strong><\/p>\n

Conversant in heaps of contextual and theoretical components, on the very least some of that are on the forefront of the discipline, and their relationship to heaps of historical and up-to-the-minute practices<\/p>\n

Sound knowledge of heaps of connected specialist ways and processes<\/p>\n

Sound capacity to prepare a range \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 of \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 research methodologies to tasks, problems and hypotheses and \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 to demonstrate neutral \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 conception<\/p>\n

and excessive prognosis<\/p>\n

Sound capacity to place arange of inventive practices and to judge them in a wider context, generating efficient outcomes<\/p>\n

40 – 49<\/strong><\/p>\n

Conversant in heaps of contextual and theoretical components and their relationship to a<\/p>\n

vary of historical and<\/p>\n

up-to-the-minute practices<\/p>\n

Adequate knowledge of heaps of connected specialist ways and processes<\/p>\n

Competent capacity to prepare heaps of research methodologies to tasks, problems and hypotheses with some component of neutral conception and excessive prognosis<\/p>\n

Competent capacity to place heaps of inventive practices and evaluate them in a wider context to generate efficient outcomes<\/p>\n

30 – 39<\/strong><\/p>\n

Some knowledge of heaps of contextual and theoretical components and their relationship to arange of historical and up-to-the-minute practices<\/p>\n

Tiny knowledge of a range ofrelevant specialist ways and processes<\/p>\n

Ability to prepare a restricted vary of research methodologies to tasks, problems and hypotheses with minute evidence of neutral conception or excessive prognosis<\/p>\n

Tiny capacity to place heaps of inventive practices and to judge them in a wider context to generate efficient outcomes<\/p>\n

0-29<\/strong><\/p>\n

Tiny knowledge of contextual and theoretical components and their relationship to heaps of historical and up-to-the-minute practices<\/p>\n

No \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 vital knowledge of heaps of connected specialist ways \u00a0\u00a0 or processes No vital capacity to prepare research methodologies to tasks, problems and hypotheses, and no evidence of<\/p>\n

neutral<\/p>\n

conception or excessive prognosis<\/p>\n

No vital capacity to place heaps of inventive practices or to judge them in a wider context to generate efficient outcomes<\/p>\n

5<\/p>\n

Application of technical and reliable skills <\/strong>The level to which:<\/p>\n

<\/figure>\n

acceptable supplies and media are chosen, examined and utilised to clutch and original options and alternatives acceptable applied sciences, methods and processes are demonstrated<\/em><\/p>\n

transferable, reliable skills are successfully demonstrated self administration and neutral studying are demonstrated <\/em>Distinctive,individual andfluentapplication ofa vary of specialist<\/p>\n

life like and technical skills<\/p>\n

Excellent accomplishment of heaps of improved transferable and reliable skills applied to advanced eventualities and problems<\/p>\n

Distinctive capacity to administer non-public studying in a sustained manner and to critically evaluate non-public growth, making utilize of a huge series of options sources Executed,normal andfluentapplication ofa vary of specialist<\/p>\n

life like and technical skills<\/p>\n

Excellent accomplishment of heaps of improved transferable and reliable skills applied to advanced eventualities and problems<\/p>\n

Excellent capacity to administer non-public studying in a sustained manner and to critically evaluate non-public growth, making utilize of a huge series of options sources<\/p>\n

Executed and normal applicationof heaps of specialist life like and technical skills<\/p>\n

Executed utility of improved transferable and reliable skills to advanced eventualities and problems<\/p>\n

Very excessive capacity to administer non-public studying in a sustained manner and critically evaluate non-public growth making efficient utilize of options<\/p>\n<\/p>\n

Confident and imaginative utility of heaps of specialist life like and technical skills<\/p>\n

Confident utility of improved transferable and reliable skills to hard eventualities and problems<\/p>\n

Sturdy capacity to administer non-public studying in a sustained manner and to critically evaluate non-public growth making efficient utilize of options<\/p>\n

Sound utility ofa vary of specialist life like and technical skills<\/p>\n

Sound utility of improved transferable and reliable skills<\/p>\n

Sound capacity to administer non-public studying in a sustained manner and critically evaluate non-public growth making efficient utilize of options Competent utility ofa vary of specialist life like and technical skills<\/p>\n

Competent utility of improved transferable reliable skills<\/p>\n

Competent capacity to administer non-public studying in a sustained manner and place efficient utilize of options<\/p>\n

Classic utility of heaps of specialist life like and technical skills<\/p>\n

Tiny utility of improved transferable and reliable skills<\/p>\n

Classic capacity to administer non-public studying in a sustained manner and place utilize of options Rudimentary utility of heaps of specialist life like and technical skills<\/p>\n

Ineffective utility of improved transferable and reliable skills<\/p>\n

Proof of a total capacity to administer non-public studying<\/p>\n

6<\/p>\n","protected":false},"excerpt":{"rendered":"

DEGREE: BSc Laptop Science and Digitisation Module: Enormous Knowledge Analytics the utilize of AI Assignment Title: SmartCity Metropolis Mobility Analysis the utilize of Hadoop and Predictive AI Assignment Form: Document Word Restrict: 3000 phrases (+\/- 300) Weighting: 100% Project Date: 4\/9\/2025 Submission Date: 30\/9\/2025 Feedback Date: 21\/10\/2025 Plagiarism: When submitting work for overview, students needs […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-30939","post","type-post","status-publish","format-standard","hentry","category-solutions"],"_links":{"self":[{"href":"https:\/\/academicwritersbay.com\/solutions\/wp-json\/wp\/v2\/posts\/30939","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/academicwritersbay.com\/solutions\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/academicwritersbay.com\/solutions\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/academicwritersbay.com\/solutions\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/academicwritersbay.com\/solutions\/wp-json\/wp\/v2\/comments?post=30939"}],"version-history":[{"count":0,"href":"https:\/\/academicwritersbay.com\/solutions\/wp-json\/wp\/v2\/posts\/30939\/revisions"}],"wp:attachment":[{"href":"https:\/\/academicwritersbay.com\/solutions\/wp-json\/wp\/v2\/media?parent=30939"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/academicwritersbay.com\/solutions\/wp-json\/wp\/v2\/categories?post=30939"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/academicwritersbay.com\/solutions\/wp-json\/wp\/v2\/tags?post=30939"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}