I have a sizeable dataset that first needs to be cleaned and standardised, then explored for meaningful insights. Your task is two-fold: 1) remove duplicates, fix inconsistencies, handle missing values and generally get the raw data into analysis-ready shape; 2) dig into the cleaned set to surface actionable findings—summary statistics, trends and any patterns you spot, with clear explanations and visuals where helpful. You are free to use the tools you are most comfortable with—Excel, Python (pandas, NumPy, SciPy), SQL, R, Power BI, Tableau or similar—as long as the final work is reproducible and can be handed over without licence restrictions. Deliverables • A clean, well-documented data file in the same original format • An insights report (PDF or slide deck) that explains methods, key findings and recommended next steps • Any scripts or notebooks used, fully commented so I can rerun the process Please outline your approach, the tools you plan to use and a rough timeline in your proposal so I can get a feel for fit and turnaround.