Yearly Sales Trend Analysis
Budget: ₹1,500 – ₹12,500 INR
I have a complete set of yearly sales figures that I need explored in depth. My main objective is to surface clear trends hidden in the numbers—patterns in revenue growth or decline, seasonal shifts, product or regional out-performance, and any anomalies that merit a second look.
All raw data are already cleaned and stored in spreadsheets; if you prefer working in Python (Pandas, NumPy, Matplotlib/Seaborn) or an R environment, that’s fine—just let me know your choice so I can grant access to the files in the right format. Please feel free to bring your own BI tool for supplementary dashboards if it speeds up iteration.
Deliverables I expect
• A concise written report outlining the key trends you discover, backed by summary statistics.
• Clear visualizations (charts or dashboards) that illustrate those findings so I can present them internally without additional tweaking.
• A brief explanation of the methodology you used—enough that another analyst could reproduce the results.
Accuracy and clarity are more important to me than flashy design; every chart should directly support the narrative in the report. If anything in the dataset looks inconsistent, flag it and we can discuss before proceeding.
All raw data are already cleaned and stored in spreadsheets; if you prefer working in Python (Pandas, NumPy, Matplotlib/Seaborn) or an R environment, that’s fine—just let me know your choice so I can grant access to the files in the right format. Please feel free to bring your own BI tool for supplementary dashboards if it speeds up iteration.
Deliverables I expect
• A concise written report outlining the key trends you discover, backed by summary statistics.
• Clear visualizations (charts or dashboards) that illustrate those findings so I can present them internally without additional tweaking.
• A brief explanation of the methodology you used—enough that another analyst could reproduce the results.
Accuracy and clarity are more important to me than flashy design; every chart should directly support the narrative in the report. If anything in the dataset looks inconsistent, flag it and we can discuss before proceeding.
Related categories:
Python
Statistics
Statistical Analysis
SPSS Statistics
NumPy
Data Visualization
Data Analysis
Pandas