Modules Hub · The Deck

Pick your lane.

Five practice lanes — model data, build pipelines, write SQL and Python, and run real Spark — each with interview-style tasks and a clear verdict on what you built. New to a topic? Start in the knowledge library and learn the concepts first.

Module library

5 lanes

Practice schema thinking

Data Modeling

Entities, keys, and defensible relationships.

SkillEntity design, grain, constraints, cardinality, and tradeoff explanation.

TaskVisual canvas with entity structure, relationships, and validation cues.

RangeConcepts to real design tradeoffs

Practice system flow

Pipeline Builder

Orchestration, failure handling, dependency flow.

SkillDependency ordering, retries, quality checks, and execution reasoning.

TaskNode-based visual builder with validation and simulation-oriented feedback.

RangeConceptual to orchestration-heavy

Practice query reasoning

SQL

Schema-aware problems that reward clarity.

SkillQuery reasoning, joins, windows, debugging, and result validation.

TaskEditor-based exercises with schema context and structured feedback.

RangeFoundations to advanced analytics

Practice transform logic

Python

Transform-heavy tasks under edge-case pressure.

SkillData cleaning, parsing, transformation, validation, and test-driven thinking.

TaskCode workspace with examples, expected outputs, and review-first results.

RangeFoundations to production-style tasks

Practice execution reasoning

Spark Playground

Real PySpark, read through the DAG and plan Spark ran.

SkillLazy evaluation, shuffles, join strategies, AQE, skew, and reading physical plans.

TaskReal PySpark notebook beside the job DAG, SQL plan, stages and tasks Spark produced.

RangeFoundations to tuning decisions

Before the workspace

learn first

Knowledge Corner

Deepen the fundamentals before you build.

Short, concept-first reads that make each practice lane click. Skim one, then step straight into the workspace.

Open Knowledge Corner

Python for data mungingCleaning inputs, reshaping rows, and writing transformations that stay readable.Foundations SQL basicsCore querying patterns, joins, filters, grouping, and result-shaping habits.Foundations SQL advancedWindow functions, layered CTEs, debugging strategies, and analytical tradeoffs.Intermediate Data modeling pre-requisitesGrain, keys, cardinality, and the mental model behind durable entity design.Foundations Pipeline builder foundationsDependency order, quality gates, retries, alert paths, and orchestration tradeoffs.Foundations