Tutorials

Step-by-step learning paths for Spindle. Each tutorial explains concepts, walks through code, and links to runnable notebooks and example scripts.

Choose Your Track

graph LR
    A[New to Spindle?] --> B[Beginner Track]
    B --> C[Intermediate Track]
    C --> D[Fabric Track]
    C --> E[Advanced Track]

    F[Building Fabric pipelines?] --> D
    G[Automating with CI/CD?] --> E

Beginner Track

Zero to generating data. No prior Spindle experience required.

#	Tutorial	What you'll learn	Time
01	Hello Spindle	Install, generate your first dataset, verify FK integrity	10 min
02	Explore All Domains	Survey all 13 domains, compare schemas and table counts	15 min
03	Custom Schemas	Build a .spindle.json schema from scratch	20 min
04	Output Formats	Export to CSV, Parquet, SQL INSERT, Excel, CDM	15 min

Prerequisites: Python 3.10+, basic pandas familiarity

Intermediate Track

Real-world data engineering patterns. Requires completing the Beginner track (or equivalent experience).

#	Tutorial	What you'll learn	Time
05	Star Schema	Transform 3NF to dimensional model with surrogate keys	20 min
06	Streaming	Emit events with rate limiting, anomalies, and burst windows	20 min
07	Chaos Engineering	Inject realistic data quality issues to test pipeline resilience	20 min
08	Validation Gates	Run quality checks and quarantine bad records	15 min
09	Composite Domains	Generate multi-domain datasets with cross-domain FK relationships	20 min
18	Fidelity Reporting	Profile real data, infer a schema, generate synthetic, and measure statistical fidelity	20 min

Prerequisites: Beginner track, familiarity with data pipelines

Fabric Track

Microsoft Fabric workflows. Write to Lakehouse, Warehouse, SQL Database, and Eventstream.

#	Tutorial	What you'll learn	Time
10	Fabric Lakehouse	Write Delta tables to Lakehouse, query with Spark SQL	20 min
11	Fabric Warehouse	Generate DDL and load a Fabric Data Warehouse	15 min
12	Fabric Streaming	Stream events to Fabric Eventstream with anomaly injection	20 min
13	Medallion Architecture	Build a Bronze/Silver/Gold pipeline with chaos and validation	25 min
14	Lakehouse Profiling	Profile Fabric Delta tables, infer schema, generate synthetic, measure fidelity	25 min

Prerequisites: Intermediate track, Fabric workspace with a Lakehouse

Advanced Track

Automation, declarative pipelines, and Day 2 operations.

#	Tutorial	What you'll learn	Time
15	Scenario Packs	Run pre-built YAML scenario packs for end-to-end workflows	20 min
16	GSL Specs	Write declarative YAML specs that orchestrate generation, chaos, and validation	15 min
17	Day 2 Operations	Incremental generation, time-travel snapshots, PII masking	25 min
18	CI Integration	Automate data generation in CI/CD pipelines	15 min

Prerequisites: Intermediate track, CI/CD experience (for tutorial 18)

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How Tutorials, Guides, and Examples Relate

Content type	Purpose	Where
Tutorials (you're here)	Learn concepts step by step	docs/tutorials/
Guides	Reference for a specific feature	docs/guides/
Example scripts	Runnable Python code	examples/scenarios/
Notebooks	Interactive Jupyter notebooks	examples/notebooks/

Tutorials reference guides for deep dives and link to notebooks/scripts for hands-on practice.