foundations

DE//AGENT currently lists 5 resources under foundations: 3 tutorials, 2 references. Everything below is derived from the live registry — counts, capabilities, verification state and security posture come from the curated records, never from marketing copy.

Documented learning objectives across these resources:

• Say why analytics engines read columnar files — columnar files scan less data — via Hold the row-versus-column mental model
• Place file-format decisions on the storage stage of the data engineering lifecycle — via Hold the row-versus-column mental model
• Point at the sources that make columnar claims exact — layout, statistics, memory — via Hold the row-versus-column mental model
• Name the twelve-factor principles that map onto pipeline jobs — via The twelve-factor vocabulary for pipeline jobs
• Treat config, backing services, logs, and disposability as shared vocabulary — via The twelve-factor vocabulary for pipeline jobs
• Connect the methodology to the data engineering lifecycle — via The twelve-factor vocabulary for pipeline jobs
• Run a design review using the six sources' own claims — via Capstone — the foundations checklist
• Assign each format its lane and each job its twelve-factor vocabulary — via Capstone — the foundations checklist

1 more objectives live on the individual resource pages.

These resources map to stage: Foundations (5). Follow the four-phase roadmap to place this topic inside a progression instead of learning it in isolation.

Every entry, its shape and its trust state — sorted by the registry's composite score. This table is the honest version of a marketing comparison: no sponsored placements, no unverifiable claims.

How scores are computed: source quality score.

Highest composite score first:

1. Hold the row-versus-column mental model score 34.15 — beginner
2. The twelve-factor vocabulary for pipeline jobs score 34.15 — beginner
3. Capstone — the foundations checklist score 34.15 — intermediate

Scores rank provenance, completeness and trust — read how verification works before adopting anything.

Start here if you're new: Hold the row-versus-column mental model, The twelve-factor vocabulary for pipeline jobs.

• Hold the row-versus-column mental model — Before you pick a file format, understand why analytics engines read columnar files at all: row groups carrying min/max statistics let a reader prune most of the file before decodi… details
• The twelve-factor vocabulary for pipeline jobs — Data pipelines run as jobs on shared infrastructure, so the twelve-factor principles apply to them — config in the environment, backing services as attached resources, logs as even… details
• Capstone — the foundations checklist — Ten lessons compress into one checklist — place every decision on the lifecycle, lay out analytics files with row groups and statistics, expect Arrow at the boundaries, evolve even… details
• The Twelve-Factor App — The classic twelve principles for building services that run portably: config in the environment, backing services as attached resources, logs as event streams, disposability and d… details

Adjacent topics: tutorial (3 shared), config (2 shared), logging (2 shared).

Study path: the roadmap places this topic in a progression · the scoring model explains the numbers · the trust rule catalog shows every security check these entries passed through.