Business Insight Accelerators: Decision Intelligence and Predictive Analytics
Contact principal
Chronologie
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février 12, 2024Début de Expérience
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février 16, 2024Kickoff
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février 27, 2024Initial research
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mars 8, 2024Interim report/presentation
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mars 22, 2024Final model development
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mars 28, 2024Analyze and collect data
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avril 13, 2024Fin de Expérience
Chronologie
-
février 12, 2024Début de Expérience
-
février 16, 2024Kickoff
Team orientation and project briefing
-
février 27, 2024Initial research
Conduct initial research, gather relevant data, and establish project objectives. Assign roles and responsibilities within the team.
-
mars 8, 2024Interim report/presentation
Prepare an interim report or presentation. This should detail the methods used, interim results, and any challenges encountered.
-
mars 22, 2024Final model development
Finalize data analysis or model development. Ensure all objectives are met and results are validated.
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mars 28, 2024Analyze and collect data
This could involve data cleaning, preliminary analysis, or initial model building.
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mars 30, 2024Preliminary findings
Present preliminary findings and receive feedback. Refine the project scope and objectives if necessary.
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avril 1, 2024Final Report Draft
Begin drafting the final report or preparing the final presentation. This should include insights, recommendations, and practical implications of the findings.
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avril 2, 2024Final Report
Complete the final report or presentation. This should be comprehensive, including methodology, findings, implications, and recommendations.
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avril 6, 2024Advanced Data Analysis
Conduct advanced data analysis or model development. For predictive analytics projects, this would involve refining models and testing hypotheses.
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avril 9, 2024Final Presentation
Present the final report or findings to stakeholders (class, external partners, etc.). Gather feedback and discuss potential future work or implications of the project.
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avril 13, 2024Fin de Expérience
Portée de Expérience
Catégories
Apprentissage automatique Visualisation des données Analyse des données Étude de marchéCompétences
decision models inventory management business strategies predictive modeling trend analysis strategic decision making machine learning market trend strategic planning business operationsStudents in our Decision Intelligence course will gain theoretical knowledge and practical expertise, including developing visualizations and dashboards with tools like Tableau and PowerBI. They will learn to apply these visualizations, along with statistical methods and storytelling, to enhance problem-solving and support strategic decisions. These senior students will also be skilled in integrating technical BI skills with broader business strategies and goals. They will be able to apply decision-making principles, construct sophisticated decision models, and use machine learning for predictive modelling. Their proficiency in decision modelling will enable them to analyze scenarios for strategic planning and risk assessments.
Apprenant.es
Teams of 4 or 5 students will contribute deliverables that may vary by project. Projects will focus on creating actionable insights and practical tools that can be implemented within the organization or study. Example deliverables may include:
Strategic Donor Engagement: Profiling and Predictive Analysis for Non-Profit Fundraising: A comprehensive donor profile report identifying key characteristics of current and potential donors, segmented into various categories. A predictive model capable of forecasting future giving patterns.
Summer Melt Insights: Predictive Analysis of Student Attrition: An analytical report detailing the primary factors contributing to 'summer melt', supported by statistical evidence. Development of a predictive model that identifies at-risk students, accompanied by a set of recommended engagement strategies to reduce attrition.
Market Trend Analysis and Forecasting: A detailed market trend analysis report highlighting key emerging trends and their potential implications. A predictive market forecast model, providing insights for strategic market entry or product development decisions.
Supply Chain Optimization: A supply chain analysis report identifying current inefficiencies and potential improvement areas. Development of a predictive model for inventory management and demand forecasting, along with an optimization plan for supply chain processes.
Risk Assessment and Mitigation Strategies: A risk assessment report outlining potential risks in business operations or investments. Creation of a decision model for risk assessment and a set of mitigation strategies to address identified risks.
Chronologie du projet
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février 12, 2024Début de Expérience
-
février 16, 2024Kickoff
-
février 27, 2024Initial research
-
mars 8, 2024Interim report/presentation
-
mars 22, 2024Final model development
-
mars 28, 2024Analyze and collect data
-
avril 13, 2024Fin de Expérience
Chronologie
-
février 12, 2024Début de Expérience
-
février 16, 2024Kickoff
Team orientation and project briefing
-
février 27, 2024Initial research
Conduct initial research, gather relevant data, and establish project objectives. Assign roles and responsibilities within the team.
-
mars 8, 2024Interim report/presentation
Prepare an interim report or presentation. This should detail the methods used, interim results, and any challenges encountered.
-
mars 22, 2024Final model development
Finalize data analysis or model development. Ensure all objectives are met and results are validated.
-
mars 28, 2024Analyze and collect data
This could involve data cleaning, preliminary analysis, or initial model building.
-
mars 30, 2024Preliminary findings
Present preliminary findings and receive feedback. Refine the project scope and objectives if necessary.
-
avril 1, 2024Final Report Draft
Begin drafting the final report or preparing the final presentation. This should include insights, recommendations, and practical implications of the findings.
-
avril 2, 2024Final Report
Complete the final report or presentation. This should be comprehensive, including methodology, findings, implications, and recommendations.
-
avril 6, 2024Advanced Data Analysis
Conduct advanced data analysis or model development. For predictive analytics projects, this would involve refining models and testing hypotheses.
-
avril 9, 2024Final Presentation
Present the final report or findings to stakeholders (class, external partners, etc.). Gather feedback and discuss potential future work or implications of the project.
-
avril 13, 2024Fin de Expérience
Exemples de projets
Strategic Donor Engagement: Profiling and Predictive Analysis for Non-Profit Fundraising:
- Students could analyze historical donor data to develop a comprehensive understanding of current and potential donors, predict future giving patterns, and enhance fundraising strategies.
Summer Melt Insights: Predictive Analysis of Student Attrition:
- Students could analyze factors contributing to 'summer melt,' where prospective students who have been accepted fail to enrol or fail to return in their second or subsequent years.
Market Trend Analysis and Forecasting:
- Students could analyze historical sales and market data to identify emerging trends. Using predictive analytics, they can forecast future market shifts, providing strategic insights for market entry or product development.
Customer Behavior Prediction:
- A project focusing on analyzing customer data to predict purchasing behaviors. This could involve segmenting customers based on their purchasing history and predicting future buying patterns, aiding in targeted marketing strategies.
Supply Chain Optimization:
- Students can develop models to optimize supply chain processes. This could include predictive analytics for inventory management, demand forecasting, or identifying bottlenecks in the supply chain to improve efficiency and reduce costs.
Risk Assessment and Mitigation Strategies:
- A project centered on identifying potential risks in business operations or investments. Using decision intelligence, students could develop risk assessment models and propose mitigation strategies.
Contact principal
Chronologie
-
février 12, 2024Début de Expérience
-
février 16, 2024Kickoff
-
février 27, 2024Initial research
-
mars 8, 2024Interim report/presentation
-
mars 22, 2024Final model development
-
mars 28, 2024Analyze and collect data
-
avril 13, 2024Fin de Expérience
Chronologie
-
février 12, 2024Début de Expérience
-
février 16, 2024Kickoff
Team orientation and project briefing
-
février 27, 2024Initial research
Conduct initial research, gather relevant data, and establish project objectives. Assign roles and responsibilities within the team.
-
mars 8, 2024Interim report/presentation
Prepare an interim report or presentation. This should detail the methods used, interim results, and any challenges encountered.
-
mars 22, 2024Final model development
Finalize data analysis or model development. Ensure all objectives are met and results are validated.
-
mars 28, 2024Analyze and collect data
This could involve data cleaning, preliminary analysis, or initial model building.
-
mars 30, 2024Preliminary findings
Present preliminary findings and receive feedback. Refine the project scope and objectives if necessary.
-
avril 1, 2024Final Report Draft
Begin drafting the final report or preparing the final presentation. This should include insights, recommendations, and practical implications of the findings.
-
avril 2, 2024Final Report
Complete the final report or presentation. This should be comprehensive, including methodology, findings, implications, and recommendations.
-
avril 6, 2024Advanced Data Analysis
Conduct advanced data analysis or model development. For predictive analytics projects, this would involve refining models and testing hypotheses.
-
avril 9, 2024Final Presentation
Present the final report or findings to stakeholders (class, external partners, etc.). Gather feedback and discuss potential future work or implications of the project.
-
avril 13, 2024Fin de Expérience