Spreadsheet Modelling & Analysis MGNM580
- Subject Code :
MGNM580
Session 24253 (Jan Mar)
Academic Task: 1 (Project)Nature:Individual
Course Title:Spreadsheet Modelling & AnalysisCourse Code:MGNM580
Section: Maximum Marks:30
Date of Allotment:Feb 10, 2025Date of Submission:Feb 24, 2025
The Objective of the Activity
After completing this assignment, the students will be capable of:
- Understanding the importance of the data, in data analysis and visualization.
- Clean the data
- Arrange the data
- Analyze the data
- Draw inferences from the data
- Present the data in visually appealing way
The Topic
The students are expected to make a one-page dashboard using publicly available data. They may use data of their choice from:
- Screener
- Prowess
- Kaggle
- Mavens data playground
- Any other source (complete URL must be provided from where data has been taken)
For this assignment the syllabus would be the topics covered inUnit I to Unit IV. The dashboard must not be the compilation of tables and charts. It must tell a story.
The studentsmust use a combination of tables, charts, and numbers in the dashboard. The are free to design a static dashboard or a dynamic dashboard using pivot tables and/or formulae.
The students will design the dashboard and upload it on their#linkedin accountwhile using the#LovelyProfessionalUniversity, #MSOB and #SpreadsheetModellingAssignment1. All three #tags are mandatory.
The students must also update the link of their linkedin dashboard at thisgoogleform link:
The Evaluation Parameters
The evaluation is divided in two parts:
- Linkedin shares and commenting (10 Marks)
- Technical skill assessment by the faculty (20 Marks)
Distribution of Marks: Linkedin Shares and Comments
Shares and comments >= 100 (10 marks)
Shares and comments >= 80 (08 marks)
Shares and comments >= 60 (06 marks)
Shares and comments >= 40 (04 marks)
Shares and comments >= 20 (02 marks)
Distribution of Marks: Technical Skill Assessment by Faculty
|
Parameter |
Marks |
Key Evaluation Points |
|
1. Dashboard Functionality |
4 |
- Clear business purpose & scope |
|
- Contains essential KPIs/metrics |
||
|
- Effective data aggregation |
||
|
- Mobile/desktop responsiveness |
||
|
2. Visual Design |
4 |
- Logical layout hierarchy |
|
- Appropriate chart selection |
||
|
- Color contrast & accessibility |
||
|
- Minimal chartjunk/clutter |
||
|
3. Data Integrity |
4 |
- Error-free calculations |
|
- Proper data validation |
||
|
- Efficient formula usage |
||
|
- Source data organization |
|
4. User Interaction |
4 |
- Intuitive slicers/filters |
|
- Dynamic updates |
||
|
- Navigation flow |
||
|
- Drill-down capability |
||
|
5. Documentation |
4 |
- User guide clarity |
|
- Data dictionary |
||
|
- Formula explanations |
||
|
- Version control |
Note that within the parameters each evaluation key point carries ONE MARK
Mapped Course Outcomes
CO1, CO2, CO3, CO4
Mapped Blooms Taxonomy
L4 L6