Carlos D. Prado S.
Selected work

MSc capstone · Data visualization

Energy transition analytics

A global energy-data project combining relational modelling, Tableau storytelling, and Python forecasting to examine supply, demand, and renewable potential.

Role
Data sourcing, database design, analysis, forecasting, and dashboard design
Period
2022
Status
Academic capstone
Tableau dashboard showing a European energy-consumption map and a linear projection to 2050
A 2050 consumption scenario from the capstone dashboard series.
12dashboard chapters
2forecast approaches
57report pages
01

Challenge

What the work needed to resolve.

Unify heterogeneous global energy, population, development, and weather sources into a navigable story about the transition to 2050.

02

Approach

A system designed for scrutiny.

  1. 01

    Built master tables and a relational model from international energy and development sources.

  2. 02

    Designed Tableau dashboards for energy mix, renewable potential, investment context, and dependence risks.

  3. 03

    Compared linear-regression and LSTM projection workflows in Python notebooks.

SourcesMaster tablesRelational modelDashboardsProjection
03

Inside

What the system actually produces.

The figures below are rebuilt in the portfolio from synthetic series, so they show the shape of each output without carrying any real data out of the project.

Generation mix over timeSynthetic data
2000202520500%50%100%RenewableNuclearGasCoal

The transition question is a composition question: what share each source holds, and how fast the shares move.

Projection with its uncertaintySynthetic data
100150200observedprojected200020252050Index, 2000 = 100 — illustrative scenario

A projection is only honest with its band attached. The further past the observed window, the wider the interval it has to carry.

Outcome

A complete analytical narrative spanning data preparation, modelling, interactive dashboards, and documented methodology.

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