| Category | Assignment | Subject | Computer Science |
|---|---|---|---|
| University | Northeastern University | Module Title | LCSCI7231 Data-Driven Transformation |
| Assessment Type | Practical Task 1 |
|---|---|
| Assessment Title | Practical Task 1 |
| Academic Year | 2024-25 |
| Deadline | 10th July 2025 |
| Level | 7 |
Students must perform the following practical tasks to address the case study and associated data.
1. Market Analysis for Competitive Intelligence [K2d(ii), S1d, S3d, T2d, T3d(i),T3d(ii)]
2. Using Business Intelligence to inform the creation of a high-level technology roadmap for the case study. [ K4d, T1d, T2d, T3d(ii)] (25 Marks)
Using the analytics result from (1) create a documentation of the details of the technology roadmap. Your report should help to make data-driven decisions for the case study. This should be in the direction of the goal stated in (1). Also, in addition, you may or may not need to create more visualisations in addition to what you have in (1), to improve your choice of visuals to include in the technology road map.
The Technology road map should include details such as
3. Data requirements for digital transformation for the case study [T2d, T3d(ii)] (10 Marks)
Give a detailed description of the datasets used in questions 1 &2 above, stating the following for each:
4. The report will the evaluated for English proficiency (10Marks)
You are to upload at least 2 files on Canvas (you could zip the files together and upload as a single file, or you could upload them individually)
Climate change is the long-term shift in weather patterns and temperature. The Earth is now 1.1°C higher in temperature than it was in the 1800s. The consequence of this rise in climate temperature is water scarcity, melting of polar ice caps and flooding (as well as many other consequences).
This increase in climate temperature has huge implications for the Earth and society at large, and we need to address it. Although many societal shifts need to be made, technological development can help address some environmental issues.
Digital transformation could help tackle climate change, for example, using sensors that can monitor performance, software that can connect operations with IT systems, automation and analytics that will equip organisations and individuals alike with the ability to better manage and optimise their environment, whether at work or home. An example of this is the EcoDataCenter in Sweden [1].
As the world continues to seek solutions to climate change issues, it's important to consider the role data-driven digital transformation could play in making this a reality. This assignment aims to explore how digital transformation can help tackle climate change challenges.
Assuming you are in charge of a digital transformation project targeted at solving climate change problems, as it affects an organisation that you have chosen. (You are free to select any of the climate change problems you like, and the technology approach to address it). The aim of this assignment is for you to provide a data-driven business strategy and offer recommendations that can contribute to solving a selected climate change problem in the UK.
Here are some examples of useful data sources for this assignment (Note: You are not required to use the data sources provided. Feel free to add other data sources (open and free) that could help support your submission).
Climate Change
Climate Change: Earth Surface Temperature Data
Potential Impacts of Climate Change on World Food Supply
Measuring UK greenhouse gas emissions
ESA Climate Office
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No part of this assignment is to be done using AI tools.
This assignment is 50% of the overall mark for the course.
This assignment requires that you submit both a PDF document (that attends to the solutions to the questions and all necessary visualizations) and a Tableau workbook (make sure to upload your data to the workbook). Not submitting the Tableau workbook (or submitting a wrong file format) or the PDF report will mean that no marks will be allocated to the questions that require these submissions.
The goal of this practical task is to gain hands-on experience in using data to make informed business decisions.
Given a context case, the students will work individually, explore large datasets, analyse the data and use the result from the analysis to inform the creation of a technology roadmap. The students are expected to build mastery in the use of Tableau software. The student should also be able to deliver written work that shows English language competency, coherence, conciseness, and clarity.
Students will be supported throughout the period of the assessment during office hours and lab sessions.
You have three submission attempts, but only the last submission will be graded. If your last submission attempt is late, you will receive the late penalty even if you have a previous submission that was on time. Please make sure to avoid multiple submissions for assessments with multiple components, as only the last attempt will be graded. Upload several files in one submission attempt instead.
If your assessment requires anonymous submission (see the assessment details table at the top of your assessment brief), please be sure you have left your name off of your submission and out of the submission file name, as failing to do so may result in a 0% mark on the assessment.
Refer to the assessment details table in your assignment brief for acceptable file formats. Avoid submitting zip files (unless explicitly required by the assessment brief); use the 'add files' function to submit multiple files instead. If you are submitting a physical artefact, you must also provide clear and thorough documentation (such as in the form of photographs or a video) of your submission by the deadline; see the bottom of this section for guidance on submitting video files.
Please ensure that you tick the agreement box at the very bottom of your Canvas submission page (scroll down if you don't see it). This will enable you to select 'Submit Assessment.' Please review the submitted file to ensure that everything is in order.
If you encounter any issues with submission, email a copy of your assignment before the deadline to student.assessments@nulondon.ac.uk along with screenshots of the problem on Canvas, showing a timestamp.
To turn on notifications for submission confirmation emails in your Canvas settings: Account > Notifications > Turn on the bell for 'All submissions.' In the app, this is via Settings > Email Notifications > All submissions.
To submit a video recording: Select the 'Panopto video' icon in the text entry box in your submission portal. You can upload a video file of any format from your media library by selecting 'upload,' choosing 'my folder' in the drop-down menu, and clicking 'insert.' You should be able to play the video back once it processes. See further explanation, including guidance on recording videos using Panopto, in this support article: 'How to Submit a Video Assignment in Canvas.'
The University uses two categorical assessment marking schemes -one for undergraduate and one for postgraduate -to mark all taught programmes leading to an award from the University.
More detailed information on the categorical assessment marking scheme and the criteria can be found in the Course Syllabus, available on the University's VLE.
This assessment will enable students to demonstrate in full or in part the learning outcomes identified in the Course Descriptor.
On successful completion of this assessment, students should be able to:
K2d(i) Comprehensively understand the underpinning principles of data-driven transformation.
K2d(ii) Systematically understand how to monitor market trends and collect competitive intelligence.
K4d Comprehensively understand the strategic importance of data-driven business strategy and technology roadmap.
S1d Use theory, tools and frameworks to critically evaluate the business intelligence and develop transformation strategies to improve business performance.
S2d Critically evaluate business literature to compare and critique different approaches to data-driven business strategy.
S3d Critically evaluate and create effective communication plans based on rigorous data analysis.
T1d Evaluate and develop effective data-driven communication strategies.
T2d Consistently display an excellent level of technical proficiency in written English and command of scholarly terminology, so as to be able to deal with complex issues in a sophisticated and systematic way.
T3d(i) Use self-direction and originality in problem solving.
T3d(ii) Identify, critique and synthesise complex information from a range of sources.
Students can expect to receive feedback on all summative coursework within 28 calendar days of the submission deadline or, if applicable, the last oral assessment date, whichever later. The 28 calendar day deadline does not apply to work submitted late. Feedback can be accessed through the assessment link on the Canvas course page.
Please ensure that you submit your assignment well before the deadline to avoid any late penalties, as a submission made exactly on the deadline will be considered late. Please keep in mind that there may be differences between your computer's clock and the server time, which can cause discrepancies, and that Canvas may take some time to process your submission.
Your Canvas submission portal displays two due dates: one is the deadline for your assignment, and the second is the latest possible date by which your assignment can be submitted late. Please make sure you submit by the assessment deadline in order to avoid late penalties.
If assessments are submitted late without approved Extenuating Circumstances, there are penalties:
For assessment elements submitted up to one day late, any passing mark will receive 10 marks deducted or a threshold pass (40% for undergraduate students, 50% for postgraduate students), whichever is higher. Any mark below 40% for undergraduate students and below 50% for postgraduate students will stand.
Students who do not submit their assessment within one day of the deadline, and have no approved Extenuating Circumstances, are deemed not to have submitted and to have failed that assessment element. The mark recorded will be 0%.
For assessment subelements, late submission will result in non-submission penalties deducted according to the marking criteria above.
For further information, please refer to AQF7 Part C in the Academic Handbook.
The University's Extenuating Circumstances (ECs) procedure is in place if there are genuine circumstances that may prevent a student from submitting an assessment. If the EC application is successful, there will be no academic penalty for missing the published submission deadline.
Students are normally expected to apply for ECs in advance of the assessment deadline. Students may apply for consideration of ECs retrospectively if they can provide evidence that they could not have done so in advance of the deadline. All applications for ECs must be supported by independent evidence.
Successful EC applications for live oral assessments, including vivas, will result in a deferral of the oral to be organised by faculty, students, and Timetabling for a date as close as possible to the original presentation date. The deadline for supplementary materials, if assigned, will be carried forward by the length of the oral assessment extension.
Missing an oral assessment, including a compulsory viva, without an approved EC will result in a non-submission for the entire assessment and, accordingly, a recorded mark of 0%.
Students are reminded that the ECs procedure covers only short-term issues (within 21 days leading to the submission deadline) and that if they experience longer-term matters that impact learning, then they must contact Student Support and Development for advice.
Under the Extenuating Circumstances Policy, students may defer an assessed element on only one occasion and may request an extension on a maximum of two occasions.
For further information, please refer to the Extenuating Circumstances Policy in the Academic Handbook.
Any submission must be a student's work and, where facts or ideas have been used from other sources, these sources must be appropriately referenced. The University reserves the right to hold a viva if there are concerns about the authenticity of a student's or learner's work. The Academic Misconduct Policy includes the definitions of all practices that will be deemed to constitute academic misconduct. This includes the use of artificial intelligence (AI) where not expressly permitted within the assessment brief or in a manner other than specified. Students should check this policy before submitting their work. Students suspected of committing Academic Misconduct will face action under the Policy. Where students are found to have committed an offence, they will be subject to a sanction, which may include failing an assessment, failing a course or being dismissed from the University depending upon the severity of the offence committed. For further information, please refer to the Academic Misconduct Policy in the Academic Handbook.
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