INFO 4311 Data Warehousing Alternative Assessment Semester 1, 2025/26 | IIUM
Assignment Type
Individual Assignment
Subject
INFO 4311 Data Warehousing
Uploaded by Malaysia Assignment Help
Date
01/16/2026
INFO 4311 ALTERNATIVE ASSESSMENT
KULLIYYAH OF INFORMATION AND COMMUNICATION TECHNOLOGY
| Programme | Â BIT | Level of Study | Undergraduate |
| Time | Â Class time, 13 Jan 2026 until 10:00 am, 16 Jan 2026 | Date | 13-16 Jan 2026 |
| Duration | Â 3 Days | ||
| Course Code | Â INFO 4311 | Section(s) | All |
| Course Title | Â DATA WAREHOUSING |
INSTRUCTION S TO CANDIDATES
Please refrain from opening the question paper until instructed to do so.
This question paper consists of 5 pages, excluding the cover page.
WARNNG
Cheating is strictly prohibited and will be subject to disciplinary action, including dismissal, as outlines in the Student Academic Performance Evaluation Regulations (SAPER).
Answer all parts and submit in ITa’leem.
FINAL ASSESSMENT BRIEF: DATA WAREHOUSE AND DASHBOARD DEVELOPMENT (100 MARKS = 40%)
ISSUE DATE : 13 JAN 2026 (TUESDAY) 10:00 A.M. DUE DATE : 16 JAN 2026 (FRIDAY) 12:00 NOON
You are given the following:
- Data Warehouse (Data Mart) Star Schema as in Figure 1.
- SQL script file (Bikesales_DW.sq/) to create the BikesaIes_DW Data Mart.
- Three (3) cleaned Excel spreadsheet datasets — Bikestores 2016.xlsx, Bikestores 2017.xlsx and Bikestores 2018.x/sx— as Data Sources to your Data Mart.
Figure 1: BikesaIes_DW Data Mart Star Schema
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ANSWER ALL QUESTIONS BELOW.
Question 1
Using Microsoft SQL Server, execute the SQL script file provided to create the Bikesales DW Data Mart following the schema in Figure 1. For such Data Mart, complete the Bus Matrix (Table 1).
Table 1: Bus Matrix
| Business processes [2 marks] | Fact Table
[2 marks] |
Granularity of
Fact Table [2 marks] |
Fact
[2 marks] |
Dimension
[2 marks] |
Deliverable:
BikeSales DW Bus Matrix
[Total: 10 marks]
Question 2
Using Microsoft SQL Server Integration Services (SSIS), populate Bikesales_DW Data Mart created in question 1 with data from the 3 Excel spreadsheet datasets provided.
Source: Excel    Destination: SQL Server Data Mart
Use SSIS transformation features — Lookup, Sort, Union All and Data Conversion — in the
Extract, Transform and Load (ET L) process, You may use other relevant features if necessary.
Capture screenshots of the Control Flow, Data Flow, Execution Flow and Output of all packages you built (see examples below), compile in the document and briefly describe the ET L implementation of the Bikesales_DW.
Control Flow:
Package,dtsx {Design] X
Oath                                                          m fåent HendlK:i Package Explorer O Progress
SQL – Truncate DimProducts Table
DF Extract From Source to Dimproducts
DESKTOP-TIJBPUF.Northwind               DESKTOP-TIJBPüF.NorthwindDW
Data Flow:
Package.dtsx (Design! Â Â Â Â Â X
Control How      Data               Parameters El Event Handlers        package Explorer O Execution Results
Data Flow Task:         DF Extract .frorp         _tp QImProgucts
OLE DB Source Products
You may have other transformations from your ET L rules, so you may add more in between source and destination
OLE DB Destination DimProducts
Execution Flow:
| Luvr.up tn
Oeöved Calumn C2kuiaLe                                                                                                            Maximize |
|
| Output
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|
VarSQbEes           List Output
Maximisation of the Execution Flow:
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| the q.öt:he | |||||
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| . | at Bata Flow Task                                          source, Lockup Payron.PateKQY |          LGQkuæy –                                             has cached 266 r0NK._ | |||
| In tornarlan: | cource , Lookup |                                                                              hafi cache._i                          of 366 ras•;. | |||
| Informaticn, | at Daca_ | fron “th_irce. |            The                      of unique                  added                                      is 2-66, | ||
| • | Data | from source, Lbr;kup fQsheets | Lookup | rows | cache. The |
| at Data |                                         -Fron                      IkiurhyRatR | Lppkup Houriydate | Ad | ||
|                       VactEnp10yeeIftE2shcet5                                         Lockup          “nuriyRate | added | cache | |||
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the .1dta |
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phase |
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source, finished; Drs:                                (ftXØ). |
|||
Result Output — The Data:
Run a query for each dimension table and fact table in Microsoft SQL Server to check whether all tables have been populated with data. Capture full screenshots of result data populated in dimension tables and fact tables (see example below). A sample of data visible in the screenshot to show successful loading of data for each table is enough.
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|||||||||||||||||||||||||
PM
Deliverable:
Bikesales DW Control Flow, Data Flow, Execution Flow and Output of all ET L packages.
[Total: 60 marks]
Question 3
Using Microsoft PowerBl, create a dashboard with at least TWO (2) visuals that analyse the facts and data from BikesaIes_DW Data Mart. Clearly specify the query associated with each visual, describe the visual and give insight.
Deliverable:
Bikesales DW Dashboard
SUBMISSION GUIDELINES
- Format: Compile deliverables of Question 1, 2 and 3 in one file (Word or PDF). If you have more than one file, submit a zip file.
- Filename: Name your file MatricnoDW.doc or MatricnoDW.pdf.
Submission Platform: iTa’leem
Notes
- Use the provided datasets only
- Clearly state any assumptions made.
- Cite all references or sources used.
- Refer to Assessment Rubric in the Appendix.
[Total: 30 marks]
END OF QUESTION PAPER
APPENDIX Assessment Rubric
Total = 100 marks / 40%
This rubric is divided into three main parts as specified in the final assessment brief.
| Criteria | Excellent (Full Marks) | Good (Partial Marks) | Needs
Improvement (Minimal Marks) |
Max
Marks |
|
| Question 1: 10 marks | |||||
| Business Process | 2 | ||||
| Fact Table | 2 | ||||
| Granularity | 2 | ||||
| Fact | 2 | ||||
| Dimensison | 2 | ||||
| Question 2: 60 marks | |||||
| ETL         Package Control  Flow
(SSIS) |
Control Flow is well-structured, logical,             and complete (5) | Mostly structured and functional (3-4) | Disorganized or incomplete (1—2) | 5 | |
| ETL Data Flow and transformations | All                  necessary
transformations applied correctly for all tables (20-30) |
Most transformations correct with minor errors for all/some tables (10-19) | Major       issues       in
transformations incomplete for all/some tables (1— 9) |
30 | |
| Execution             Flow and             successful data loading, and well-documented | Fully successful execution for all tables with clear documentation (5) | Execution mostly successful with minor issues for all/some tables (34) | Unsuccessful for all/some tables or poorly documented (1-2) | 5 | |
| Screenshots and result output
from                    data warehouse |
Complete, screenshots components 20) | clear of all (16- | Mostly complete; some screenshots missing (8-15) | Incomplete         or unclear (1—7) | 20 |
| Question 3: 30 marks | |||||
| Dashboard Design
& Visual Quality |
Dashboard is designed, visually
Visuals appropriate labelled (8-10) |
welL and clear. are and correctly. | Dashboard includes relevant visuals but layout may lack clarity or visual appeal. Minor inconsistencies in labeling, scaling, or formatting. (5-7) | Dashboard cluttered, unclear, or               poorly
formatted. Visual choices are inappropriate or difficult               to interpret. (1-4) |
10 |
| Queries | Queries are clearly stated, correct, and efficiently retrieve data from the | Queries are mostly correct but may include minor | Queries missing, incorrect, or unclear. (1-2) | ||
| Bikesales DW Data Mart. (5) | syntax or logical issues. (3-4) | |||
| Description Insights | Each visual is clearly described                with meaningful. Strong connection between data and conclusion. | Description is understandable but insights are superficial or general. Some connection to decision-making is present but not fully developed. (610) | Descriptions               are vague or missing. Insights               are incorrect, unsupported,       or unrelated              to visuals. (1-5) | 15 |
| TOTAL | 100 |
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INFO 4311 Data Warehousing alternative assessments require students to demonstrate strong ETL design, SQL accuracy, SSIS implementation, and meaningful dashboard insights. IIUM assessors closely evaluate data modelling, transformation logic, screenshots, and business interpretation, not just technical execution. When managing data marts, SSIS packages, and Power BI dashboards becomes challenging, Data Warehousing Assignment Help Malaysia provides structured academic support. At Malaysia Assignment Help we deliver AI-free, plagiarism-free, human-written assignments aligned with assessment rubrics. You can also review our human-written assignment samples to see the quality delivered by our IIUM Assignment Help experts.
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