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Documentation And Examples

Learn Documentation And Examples for free with explanations, exercises, and a quick test (for Data Platform Engineer).

Published: January 11, 2026 | Updated: January 11, 2026

Table of Contents

Why this matters

As a Data Platform Engineer, you build tools others must trust quickly: ingestion SDKs, pipelines, dbt models, governance workflows. Clear documentation and runnable examples reduce onboarding time, prevent support tickets, and keep teams unblocked during incidents.

  • Onboarding: New teams can ship their first pipeline the same day.
  • Reliability: Runbooks turn pager events into quick, correct actions.
  • Adoption: Good examples demonstrate value and best practices.

Who this is for

  • Data Platform Engineers building internal data products and tooling.
  • Analytics Engineers documenting dbt models and datasets.
  • ML/Data Engineers publishing SDKs, connectors, or Airflow/Flow jobs.

Prerequisites

  • Basic Git workflow (branch, commit, PR).
  • Comfort with SQL and either Python or your platform’s SDK.
  • Understanding of your platform’s deployment and monitoring basics.

Concept explained simply

Documentation answers: What is this? Why use it? How do I start? How do I debug? Reference tells every option. Examples show working patterns to copy.

Mental model

  • Layers of docs (think onion):
    • Overview: purpose, benefits, scope.
    • Quickstart: 5–10 minute path to first success.
    • How-to guides: step-by-step for common tasks.
    • Reference: exhaustive API/config options.
    • Runbook/Troubleshooting: detect, diagnose, resolve.
  • Examples are tests you run by hand: self-contained, copy-pastable, with expected output.
  • Docs are a product: versioned, reviewed, and owned.

Reusable templates

DocSpec mini-template (fill this for any tool)
  • Purpose: what problem it solves, who benefits.
  • Prerequisites: accounts, roles, access, versions.
  • Quickstart: minimal steps to first success.
  • How-to: common tasks (one goal per guide).
  • Reference: API/configs/CLI flags with defaults.
  • Operations: runbook, SLOs, alerts, dashboards.
  • Versioning: current version, breaking changes, migration.
  • Ownership: team, contact, review cadence.
ExampleSpec checklist (for runnable examples)
  • Single goal, small scope.
  • Setup steps with exact commands.
  • Copy-paste code plus inline comments.
  • Expected output or validation query.
  • Cleanup steps to avoid costs/state pollution.
  • Runtime note: estimated time and resource needs.

Worked examples

1) Quickstart for an ingestion SDK

Goal: Ingest a CSV into the bronze layer.

  1. Install: pip install acme-data-ingest (requires Python 3.10+)
  2. Auth: Set ACME_TOKEN env var.
  3. Run:
# ingest_csv.py
from acme_ingest import Client
c = Client()
c.ingest_csv(
    dataset="sales_bronze",
    path="./samples/sales.csv",
    delimiter=",",
    header=True
)
print("Rows loaded: ", c.last_result.rows)

Expected: console shows row count; table bronze.sales updated.

Cleanup: delete local sample file if created.

2) Minimal pipeline runbook

Scope: Airflow DAG daily_customer_dim

  • Normal runtime: 8–12 minutes; SLO: succeeds by 02:00 UTC.
  • Critical alerts: task build_dim fails or SLA miss.
Diagnose
  • Check last run logs for HTTP 429 (source throttling).
  • Run validation query: select count(*) from dim_customer where load_date = current_date; expect > 0.
Resolve
  • If 429: rerun with backfill window of 1 day; increase backoff to 5s.
  • If schema drift: apply data contract patch (add nullable column), then rerun.

Owner: Data Platform Team; Review quarterly.

3) Dataset README (copy-ready)

Dataset: analytics.orders_daily

  • Business purpose: Orders with daily grain for dashboards.
  • Freshness: by 03:00 UTC (90th percentile), alert at 04:00.
  • Schema (excerpt): order_id (PK), customer_id, order_ts, status, total_usd.
  • Quality checks: not-null order_id, valid status in {new, paid, shipped, canceled}.
  • Backfill policy: up to 30 days.
  • Owner: Analytics Engineering.

Example query:

select date(order_ts) as d, sum(total_usd) as revenue
from analytics.orders_daily
where d >= current_date - interval '7 day'
group by 1
order by 1;

Exercises

Do these to lock in the skill. A short checklist is included. Solutions are available, but try first.

Exercise 1: Rewrite a bad doc into a great Quickstart

See Exercises list below (ex1). Aim for a 5–10 minute path to first success.

Exercise 2: Build a runnable example with validation

See Exercises list below (ex2). Include setup, run, expected output, and cleanup.

Self-check checklist
  • Purpose is clear in the first 2 sentences.
  • Prerequisites are explicit (versions, roles, access).
  • Copy-paste commands actually work together in order.
  • There is a visible success signal and a way to verify it (query, log line).
  • Rollback/cleanup steps are present.

Common mistakes and how to self-check

  • Mixing how-to and reference in one page: Separate tasks from exhaustive lists. Self-check: does the page ask the reader to decide among 20 options before starting? If yes, split it.
  • No first-run success path: Add a Quickstart that produces a clear visible result. Self-check: can a new user succeed in under 10 minutes?
  • Hidden prerequisites: Always list roles, network allowlists, tokens, and versions. Self-check: can you run it fresh in a clean environment?
  • Examples that don’t match production constraints: Mirror auth, naming, and resource limits. Self-check: does your sample exceed quotas or skip governance steps?
  • Stale docs: Add ownership and review cadence. Self-check: does the page show last reviewed date?

Practical projects

  • Create a Quickstart and a runbook for one existing pipeline. Ask a teammate to follow it; capture time-to-first-success.
  • Publish two runnable examples: one ingestion, one transformation. Add validation queries and cleanup steps.
  • Convert one large doc into four layers: Overview, Quickstart, How-to, Reference.

Learning path

  1. Draft a DocSpec for one platform component you own.
  2. Write a Quickstart that runs end-to-end locally or in dev.
  3. Add two how-to guides for top support tickets.
  4. Fill in reference options from code/config with defaults.
  5. Write a runbook with detect-diagnose-resolve and SLOs.
  6. Publish two runnable examples with validation and cleanup.

Quick test

Everyone can take this quick test; sign in to save your progress.

Next steps

  • Adopt the DocSpec and ExampleSpec templates for all new components.
  • Set review cadences for critical docs (quarterly at minimum).
  • Collect feedback: add a short issue template for doc gaps.

Mini challenge

Pick a confusing internal tool and ship a 1-page Quickstart plus a runnable example that proves a real result (row count, dashboard refresh, or alert cleared). Measure time-to-first-success before and after.

Practice Exercises

2 exercises to complete

Instructions

You are given a poor doc snippet:

Use the loader to send files. It supports different types. Configure it the usual way. You might need a token. Then run it and check if it worked. If there are errors, fix them.

Task: Rewrite into a Quickstart that delivers a visible success in under 10 minutes. Include:

  • Purpose and prerequisites.
  • Exact install/auth steps.
  • Copy-paste command or code.
  • Expected output or validation query.
  • Cleanup.
Expected Output
A short, ordered Quickstart with precise steps and a concrete success signal (e.g., row count, table exists).

Documentation And Examples — Quick Test

Test your knowledge with 8 questions. Pass with 70% or higher.

8 questions70% to pass
Standard Libraries And SDKsPlatform Support And Enablement

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