Prediction intelligence workbench

Data Lake Command Center

Data Slash

A sharp analytical system for cutting through raw data, building lakehouse features, and reporting prediction uncertainty with discipline.

Ink Cyan Signal Caveat Model
Bronze 35,937

Raw and source-shaped rows across lottery, macro, calendar, geography, and weather.

Silver 3,017

Validated Mega-Sena features with cadence, calendar, distribution, and draw metadata.

Gold 3,017

Model-ready rows joined to weather, holidays, and macroeconomic context.

Catalog 7

DuckDB views mapped onto Parquet tables for instant local analytical SQL.

Lineage

From raw source to model input

  1. Caixa3017 contests
  2. Bronzemegasena_draws.parquet
  3. Silverfeature synthesis
  4. Goldmodel_input.parquet
  5. DuckDBgold_megasena_model_input

Baseline backtest

Frequency plus recency

Weak signal
0 hits24
1 hit1526
2 hits1263
3 hits146
4 hits7
5 hits1

Average best hits: 1.5244 over 2,967 evaluated draws. This is an honesty anchor, not a promise of predictability.

Collectors

Context lake

Candidate tickets

Current baseline output

Lottery outcomes are random by design. These candidates are analysis output, not betting advice.