Final
Individual Assessment
Unit Details |
Name |
Business Analytics Fundamentals |
Code |
HI6037 |
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Year, Trimester |
Trimester 2, 2024 |
Assessment Details |
Name |
Final Individual Assessment |
Due Date & Time |
10 October, 2024 10.59 pm – Gold Coast students 11.59 pm – Melbourne & Sydney students |
Student Details |
Student Number |
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First Name |
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Family Name |
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Submission Declaration |
Integrity Declaration |
I have read and understand academic integrity policies and practices and my assessment does not violate these. |
Full Name |
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Submission Date |
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ALL SUBMISSIONS MUST INCLUDE YOUR STUDENT DETAILS AND SUBMISSION DECLARATION.
IF THESE DETAILS ARE NOT COMPLETED YOU RISK BEING PENALISED
Instructions
Academic Integrity Information |
Holmes Institute is committed to ensuring and upholding academic integrity. All assessment must comply with academic integrity guidelines. Important academic integrity breaches include plagiarism, collusion, copying, impersonation, contract cheating, data fabrication and falsification. Please learn about academic integrity and consult your teachers with any questions. Violating academic integrity is serious and punishable by penalties that range from deduction of marks, failure of the assessment task or unit involved, suspension of course enrolment, or cancellation of course enrolment.
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Format & submission instructions |
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Penalties |
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All responses must be entered in the answer boxes at the end of each question
For Questions 1, 2, and 3, you must take screenshots of the results from Power BI and paste them into the corresponding answer boxes.
Question 1 (10 marks)
Create a report page in Power BI Desktop that includes a slicer to filter episodes by the Director. When a Director is selected, the report should update to show only the episodes directed by that individual.
The report should be presented in a table format containing the following columns: Season, No. overall, No. in season, Title, Year, Sum of U.S. viewers (millions), and Written by. Explain the process of setting up this slicer and how to configure the table to display the specified columns.
Datasets Used:
Episodes.xlsx
(Overview of this dataset: The Episodes.xlsx dataset provides a comprehensive overview of a television series through two interconnected tables: Series and Episodes. The Series table offers a summary of each season, detailing the season number, total episodes, and the airing dates of the first and last episodes, giving a snapshot of the series' progression. The Episodes table dives into the specifics of each episode, including the season number, overall and in-season episode numbers, title, director, writers, original air date, and U.S. viewership in millions. The Season column links the two tables, allowing for a cohesive analysis that connects season-level summaries with detailed episode information, providing a complete view of the series' structure and evolution.)
ANSWER (box will enlarge as you enter your response)
A Power BI report should be developed such that episodes can be filtered based on director The Episodes.xlsx file should be loaded into Power BI Desktop. Make sure that along with Episodes, there is information in the Series table for further analysis. Then, create the connection between these tables as one table has a Season field, and binding both tables together helps with data integration and analysis. To increase the navigator’s interactivity, it is recommended to include a Slicer for the Director. Right-click in the Details column and select New Slicer, then drag the Director column into the new slicer that appeared in the upper panel of the report navigation. This feature will enable a user to choose a particular director and the report will refresh to display only episodes of that director.
Then, add an executive summary of a Table visualization to the report. Populate the table with the following columns: Season, No. Overall, No. in season, Title, Year, and Sum of US viewers per million Written by. For clarity, users can sort the table and filter them to their specific design depending on their requirements. Taking screenshots of the entire process at proper intervals is crucial; depicting the slicer setup, table options, and visual design selected. It does not only provide detailed information about the data but also engages the user to explore the dataset about contributions made by directors.
Question 2 (10 marks)
Using the Episodes dataset, analyse the trend in viewership across all episodes. Create a report that visualizes this trend and identifies any significant changes in viewership. Discuss the insights gained from this analysis.
Datasets Used:
Episodes.xlsx
ANSWER
The line graph It created exhibits how viewership changed with every aired episode. The No. Overall, episode number is on the x-axis and U.S. visitors (in millions) are on the y-axis with a trendline. The early episodes, though, come in much later when viewership numbers are concerned, and hover around 2.2 million views, but as more episodes are released, its viewership numbers start to climb. By episode 30 viewership hits 6 million and the trend holds up throughout a few small up and downs until the end. The largest drop is when viewership drops to about 5.4 million around episode 50 before bouncing back later on. It ends with the final episode at 12.1 million visitors, the highest point on the graph. This peak means the series became extremely popular as it drew to a close. It’s clear too, that the upward change It sees on the dotted trendline indicates a steady uptake in audience engagement over time, even though certain episodes seemed to garner less than the average amount of viewing attention.
Question 3 (10 marks)
Using the Episodes dataset, design a bar chart that highlights the 10 most popular episodes based on U.S. viewership.
Datasets Used:
Episodes.xlsx
ANSWER:
To assess the top 10 most popular episodes in terms of the number of viewers in the United States by using Power BI, we have first to get the Episodes.xlsx dataset into the program and check if all the information in the tables is relevant and correct. The first step you need to take is to click on a Bar Chart from the Visualizations section. To see the episode titles laid alongside the corresponding viewership, move the ‘Title’ to the X-axis and ‘U.S. viewers (millions)’ to the Y-axis. Third, sorting can be used to make the episodes sorted by the viewership in decreasing order. In the Visualizations pane, apply the Top N filter to the Title field as the Episodes with most views card should only show 10 episodes. This enables the chart to concentrate on hits such as “The Dragon and the Wolf” with 12.1m viewers, and “Eastwatch”, which attracted 10.7m viewers respectively. As an element of making the report more engaging and interactive, including the Slicer which filters based on the season. This slicer allows the end user to further analyze viewership by season and make any necessary further analysis. Use the bar chart properly with proper labels for identification and apply conditional formatting for episodes that attract very many viewers. (Thomas 2020).
Question 4 (10 marks)
What factors should be considered when determining the functionality of a report?
ANSWER:
There are several identifying factors to analyze for the PowerBI report to be functional and to measure up to several stakeholders' requirements. The usability of the report is the first. A report should be easy to read, with obvious labels, an easy-to-use laItt, and engagement tools like slicers or filters. That way, users can quickly pick up what relevant insights they can pull from the report without the need for effective training to use the report. One other thing that It needs to consider is data accuracy. Before building the visualizations ensure that the dataset is clean and error-free. Misleading insights made from inaccurate data will ruin the report’s credibility. Consequently, it is important to do data validation and that all of the calculated measures (for eg., average viewership) are accurate. Also, It needs to optimize the report for performance. Especially if the dataset is large and slow and BI reports that take a long time to load or refresh can be frustrating to users. By reducing the number of visuals in the ITR report and the amount of complex calculations that must constantly be refreshed. Finally, be thinking about audience engagement. A visual design that is engaging and not overwhelming should be the purpose. Color code and other formatting options should be used to call attention to the outliers when it comes to key data points, like which episodes achieve particularly large viewership. Take, for instance, listing episodes that pulled in more than 10 million visitors can lead users to check out the hottest parts of the series.
Question 5 (10 marks)
Why is it crucial to implement a standardised approach to reporting within a company?
ANSWER:
Keeping consistency across reports is based on a standardized reporting approach that makes it possible for users to understand data the same way irrespective of the dataset. News published according to a certain standard allows users to easily find some specific insights, which reduces the process. This makes it easier for new datasets to be analyzed more quickly because they won’t have to reinvent the reporting structure like they might otherwise have to. This provides support as members of the same team can work on the same reporting framework and avoid confusion and misinterpretation. In addition, it adds accuracy because standard operating procedures include built validation steps whereby errors in calculation or interpretation are minimized. Finally, standardized reports are necessary so that they make it easy to compare different periods, different products, or different market conditions.
References
Thomas, S 2020, ‘Power BI: An analytical view’, Journal of Accountancy, 9 October, viewed 9 October 2024, <https://www.journalofaccountancy.com/issues/2020/mar/microsoft-power-bi-data-excel/>.
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END OF FINAL INDIVIDUAL ASSESSMENT
HI6037 FIA T2 2024
