• Project overview: Provide background and contextual information. Define the analysis problem. Clearly identify project goals and deliverables. State the value this analysis will bring to your organization. Note that the analysis problem must be stated in terms of a product or result that can be accomplished using some form of descriptive, predictive, or prescriptive analytics, by the size a team of learners in the required number of weeks.

• Data Description: Provide information on the data you will share, including variables, type, granularity, time-period, number of records, and approximate total size in bytes. Provide information on how you will share this data, including mode of access, platforms, frequency, and format. Confirm that you will be able to provide access to this data by the required date.

• Technology Description: Provide information on any specific platforms and tools that you might require the learners to use for data analysis, and if so, confirm that you will be able to provide access to these by the start date of the project. Provide information on any specific methods or techniques you might require the learners to use for data analysis.

• Collect data from multiple sources, clean the data, removing duplicates, missing values and resolving inconsistencies
• Perform in-depth data analysis using spreadsheets to uncover patterns, trends, and insights within the data
• Utilise formulas, functions, and pivot tables to calculate metrics such as revenue, customer segmentation, and / or  product performance
• Perform descriptive and diagnostic analysis using SQL to gain insights  
• Apply statistical modelling techniques, such as regression and classification, to identify factors influencing sales and customer behaviour
• Perform exploratory data analysis (EDA) to uncover correlations and relationships between variables using statistical methods and visualisations 
• Create interactive dashboards to visually represent the data

The final report may vary depending on preferred methods and technology.

Learners will connect directly with the employer for mentorship and supervision throughout the project.

• Access to Resources: Provide learners with access to relevant data, documentation, and tools necessary.
• Subject Matter Expertise: Assign experienced data professionals as mentors to guide learners in understanding our support environment, identifying pain points, and developing effective solutions.
• Collaboration Opportunities: Facilitate collaboration between learners and team members to gather insights, validate recommendations, and ensure alignment with organizational goals and standards.
• Technical Guidance: Offer technical assistance and guidance to learners during the implementation phase, helping them overcome challenges, troubleshoot issues, and ensure successful deployment of new solutions.
• Feedback and Review: Regularly review project progress, provide constructive feedback on proposed recommendations and implementation efforts, and offer insights for continuous improvement.