Bantuan Analisis Data Pribadi -- 2

@PINESCRIPTERR

Hi, I can turn your raw data into a clean, reproducible analysis with clear visuals and practical recommendations written in straightforward Indonesian. My preferred stack is Python with pandas for cleaning and transformation, NumPy and statistical libraries for analysis, and Matplotlib, Seaborn, or Plotly for visualisation. Power BI can also be used when an interactive business dashboard is the better final format. I would begin by profiling the dataset for duplicates, missing values, inconsistent categories, invalid dates, and unusual records. Every cleaning decision would be documented so the process can be repeated when new data arrives. The analysis can then cover trends, correlations, customer or operational segmentation, outliers, period comparisons, and the metrics most relevant to your decisions. Deliverables would include the cleaned dataset, reproducible scripts or notebook, charts or dashboard, and a concise Indonesian report explaining the methodology, findings, limitations, and recommended next actions. Correlations would be clearly distinguished from proven causal relationships. Relevant dashboard and report examples can be shared privately where client permissions allow. Question 1: What type of data, file format, date range, and approximate number of records are involved? Question 2: Which decisions or business questions should the analysis help you answer first? Regards, Houssame