IS6140 Business Intelligence and Analytics 1Python

Java Python IS6140 Business Intelligence and Analytics

Assignment 1: Individual Report (65 marks)

The IS6140 assignment is divided into two parts:

1.   Report including Tableau Dashboard: 2,000 words

. Marks: 45

2.   Recorded Video Presentation (max 10 slides): 10 mins

. Marks: 20

(1) Report Description

“Salt Productions” is the largest television production company in the Northern Hemisphere. This is primarily due to their recent acquisition of HBO, Netflix, Comedy Central and other major television producers. As a result of such heavy investment, the  Stakeholders are anxious to identify  new opportunities for future projects. They also need to integrate their data across all new acquisitions and require a data analytics strategy to create a roadmap for future insights. They have hired you, as apart of a team from BIA Consultants, to draft a detailed report (MAX 2000 words) to stakeholders with the following requirements and guidelines.

1.   Propose an analytics strategy for Salt Productions.

a.   You will need to define Business Intelligence and outline the key elements of BI using relevant academic and practitioner material.

b.   You will need to conduct a preliminary investigation into the streaming platform. industry and identify current trends for getting business insights. Present potential challenges relevant to the context of the case.

c.   Identify appropriate tools and techniques that can be used in future analyses with a “wish list” of data that would help us understand the business case further. What are the data requirements for Salt Productions? How would you advise Salt Productions in terms of further developing their Business Intelligence and Analytics strategy? Please provide a comprehensive justification for your recommendations.

2.   As apart of your report, you must conduct an analysis on Dataset 1: dai 写IS6140 Business Intelligence and Analytics Assignment 1Python Streaming Platforms” to portray our current understanding of movie/TV streaming and to inform your analytic strategy and recommendations to stakeholders.

a.   Using an appropriate BI tool (e.g. Tableau, MS Excel) create a dashboard and visualize the streaming platforms dataset. This tabular dataset consists of listings of    all the movies and tv shows available on four streaming platforms (Disney+, Netflix,  Hulu, and Amazon Prime), along with details such as - cast, directors, ratings, release year, duration, etc.

b.   Select appropriate data points for comparison and visualize the salient information for discussion in your report. Document any assumptions you make and justify the approach you have taken.

c.   Based on your analysis of the data, present your key findings, and give recommendations to the stakeholders as apart of your proposed analytics strategy.

(2) Presentation Description

Prepare a PowerPoint Presentation (.ppt) and voice over (10 slides excluding a title slide and slide for your references). Your presentation should be no more than 10 minutes and should highlight the key information from your report.

Please include the following in your presentation:

•    Title, name, student number

•    Your proposed analytics strategy (include a screenshot of your Dashboard and any relevant visualizations of Dataset 1)

•    Discussion

•    Conclusion

•    References

Submission Procedure:

Submission to Canvas by 23:59, Tuesday March 19th, 2024

Please ensure you submit all project files, including:

•    Dashboard and analysis file(s).

•    Report in a single document saved as a pdf.

•    Recorded presentation file.

•    Ensure you have submitted the Assignment Submission form.

Penalties (for late submission of Course/Project Work etc.): Where work is submitted up to and including 7 days late, 10% of the total marks available shall be deducted from the mark achieved. Where work is submitted up to and including 14 days late, 20% of the total marks available shall be deducted from the mark achieved. Work submitted 15 days late or more shall not be accepted         

内容概要:本文介绍了一个基于MATLAB实现的无人机三维路径规划项目,采用蚁群算法(ACO)与多层感知机(MLP)相结合的混合模型(ACO-MLP)。该模型通过三维环境离散化建模,利用ACO进行全局路径搜索,并引入MLP对环境特征进行自适应学习与启发因子优化,实现路径的动态调整与多目标优化。项目解决了高维空间建模、动态障碍规避、局部最优陷阱、算法实时性及多目标权衡等关键技术难题,结合并行计算与参数自适应机制,提升了路径规划的智能性、安全性和工程适用性。文中提供了详细的模型架构、核心算法流程及MATLAB代码示例,涵盖空间建模、信息素更新、MLP训练与融合优化等关键步骤。; 适合人群:具备一定MATLAB编程基础,熟悉智能优化算法与神经网络的高校学生、科研人员及从事无人机路径规划相关工作的工程师;适合从事智能无人系统、自动驾驶、机器人导航等领域的研究人员; 使用场景及目标:①应用于复杂三维环境下的无人机路径规划,如城市物流、灾害救援、军事侦察等场景;②实现飞行安全、能耗优化、路径平滑与实时避障等多目标协同优化;③为智能无人系统的自主决策与环境适应能力提供算法支持; 阅读建议:此资源结合理论模型与MATLAB实践,建议读者在理解ACO与MLP基本原理的基础上,结合代码示例进行仿真调试,重点关注ACO-MLP融合机制、多目标优化函数设计及参数自适应策略的实现,以深入掌握混合智能算法在工程中的应用方法。
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