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Datos y JSONs
Mindset & Code edited this page May 29, 2026
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🇬🇧 English first · 🇪🇸 Español más abajo.
Data is synthetic, generated with Python to simulate a realistic B2B SaaS business with seasonality, segmentation and coherent trends.
import pandas as pd, numpy as np
months = pd.date_range('2022-01', periods=36, freq='MS')
base_mrr, growth = 480_000, 0.07 # 7% monthly growth
mrr = [base_mrr * (1 + growth) ** i for i in range(36)]generate_data.py produces 5 CSV tables in data/; generate_executive_json.mjs (in project-sales-weather-etl) converts them to the JSONs the dashboard consumes.
| Principle | Detail |
|---|---|
| Internal coherence | MRR × 12 = ARR; LTV/CAC > 3× in good months |
| Seasonality | Stronger Q4, softer Q1 (typical B2B pattern) |
| Realistic segmentation | 60% SMB · 30% Mid-Market · 10% Enterprise |
| Coherent churn | Higher on month-to-month vs annual contracts |
| Reproducibility |
np.random.seed(42) → identical output every run |
| File | Rows | Consumed by |
|---|---|---|
executive_summary |
36 | KPI cards + trends |
revenue_by_segment |
108 | Segment donut |
revenue_by_channel |
144 | Channel bars |
marketing_funnel |
36 | Funnel |
pipeline_stages |
180 | Pipeline funnel |
Los datos son sintéticos, generados con Python para simular un negocio SaaS B2B realista con estacionalidad, segmentación y tendencias coherentes.
import pandas as pd, numpy as np
months = pd.date_range('2022-01', periods=36, freq='MS')
base_mrr, growth = 480_000, 0.07 # 7% crecimiento mensual
mrr = [base_mrr * (1 + growth) ** i for i in range(36)]generate_data.py produce 5 tablas CSV en data/; generate_executive_json.mjs (en project-sales-weather-etl) las convierte a los JSON que consume el dashboard.
| Principio | Detalle |
|---|---|
| Coherencia interna | MRR × 12 = ARR; LTV/CAC > 3× en meses buenos |
| Estacionalidad | Q4 más fuerte, Q1 más débil (patrón B2B típico) |
| Segmentación realista | 60% SMB · 30% Mid-Market · 10% Enterprise |
| Churn coherente | Mayor en mes a mes vs contratos anuales |
| Reproducibilidad |
np.random.seed(42) → salida idéntica cada vez |
| Archivo | Filas | Consumido por |
|---|---|---|
executive_summary |
36 | Tarjetas KPI + tendencias |
revenue_by_segment |
108 | Donut de segmento |
revenue_by_channel |
144 | Barras de canal |
marketing_funnel |
36 | Funnel |
pipeline_stages |
180 | Funnel de pipeline |