Data Arena
High-performance browser sandbox for Apache Spark & distributed SQL. Write, execute, and validate real data engineering transformations with zero cloud configuration.
Apache PySpark
Python DataFrame APISolve real-world enterprise data engineering challenges. Master DataFrame transformations, schema construction, multi-stage revenue aggregation, deduplication, and relational joins in an interactive Databricks-style environment with automated semantic validation.
Spark SQL
Declarative AnalyticsFully integrated ANSI SQL queries, CTEs, and window analytics interoperable with PySpark DataFrames.
Launch SQL Mode →Scala Arena
Distributed SparkType-safe distributed pipelines with typed Datasets, case classes, and functional Spark combinators.
R / SparkR
Statistical PipelinesStatistical machine learning and data frames powered by SparkR and sparklyr backends.
Search All 121 Engineering Challenges
Filter by problem ID, topic, concept, difficulty tier, or SQL/PySpark patterns.
Load Employee Master Dataset
📚 DataFrame Fundamentals
Inspect DataFrame Schema
📚 DataFrame Fundamentals
Count Master Records
📚 DataFrame Fundamentals
Display Sample Records
📚 DataFrame Fundamentals
Verify Lazy Evaluation
📚 DataFrame Fundamentals
Ingest Delimited CSV Dataset
📚 Multi-Format File Ingestion
Ingest Semi-Structured JSON
📚 Multi-Format File Ingestion
Ingest Columnar Parquet Storage
📚 Multi-Format File Ingestion
Ingest Delimited File with Custom Options
📚 Multi-Format File Ingestion
Create Temporary View for SQL Access
📚 Multi-Format File Ingestion
Select Required Employee Columns
📚 Column Selection & Aliasing
Project Columns Using col() Function
📚 Column Selection & Aliasing
Column Access with DataFrame Attribute Notation
📚 Column Selection & Aliasing
Column Access with Bracket Indexing Notation
📚 Column Selection & Aliasing
Rename Projected Column with alias()
📚 Column Selection & Aliasing
Project Computed SQL Expressions with selectExpr
📚 Column Selection & Aliasing
PySpark & SQL Fundamentals
Master PySpark and SQL fundamentals through 50 hands-on coding challenges. Learn real-world DataFrame operations, multi-format file ingestion, predicates, deduplication, transformations, and aggregations with interactive Databricks-style notebooks and automated test validation.
8 Core Curriculum Modules (PY-001 to PY-050)
Load the existing employees table from the Spark catalog into a PySpark DataFrame named df....
Read data/employees.csv into a DataFrame named df using spark.read.csv with header=True and inferSchema=True....
Project employee_id, employee_name, and department columns from the employees table into DataFrame df....
Filter records from the employees table where department is exactly equal to 'IT' into DataFrame df....
A customer outreach campaign requires identifying accounts that cannot receive digital communications due to u...
The e-commerce storefront is optimizing its discovery experience for budget-conscious shoppers. Review the pro...
Enterprise financial planning systems evaluate monthly recurring customer contracts to establish forward-looki...
Anti-money laundering and compliance operations require transactions to be categorized into operational risk q...
Production Data Engineering
Level up to production data engineering across 50 challenges. Master analytical window functions (dense_rank, lag, lead), schema validation assertions, multi-table join pipelines, SCD Type 1 & 2 dimensions, CDC reconciliation, and enterprise data quality.
33 Core Curriculum Modules (PY-051 to PY-100)
In e-commerce fulfillment, transaction logs track item quantities and unit pricing. Examine the orders dataset...
Customer relationship management platforms categorize customers based on historical spend to allocate service ...
Data captured across external customer registration portals often exhibits formatting discrepancies that hinde...
Logistics tracking systems capture dispatch and arrival milestones across shipping routes. Examine the shipmen...
Financial risk surveillance systems monitor transaction streams to identify critical anomalies requiring prior...
Customer journey tracking platforms capture varied user behavioral events across digital channels. Examine the...
Customer onboarding verification pipelines screen new user account profiles to ensure mandatory identity crede...
Executive commercial analytics requires an authoritative summary of fulfilled commercial transactions to evalu...
In distributed cloud infrastructure, workloads are deployed across multiple regional datacenters with varying ...
Supply chain operations regularly audits carrier performance across national shipping lanes to identify qualif...
Executive merchandising analytics evaluates commercial sales performance across retail merchandise departments...
Hospital administration requires a consolidated inpatient census report. Using the provided patient directory ...
The billing finance team requires an account-level revenue reconciliation summary. Integrate the subscriber re...
Logistics dispatchers require a consolidated order fulfillment manifest. Combine order records, customer accou...
Financial compliance officers require an investigation queue for completed transactions associated with height...
Join 'employees' and 'departments' on 'department', selecting 'employee_name', 'department', 'division', 'sala...
Add column 'tenure_days' using datediff(lit('2025-01-01'), col('joining_date'))....
In an enterprise customer platform, an operational master table stores customer profile details. A periodic in...
In retail platforms and pricing analytics systems, tracking product price revisions over time is crucial for c...
In modern event-driven enterprise architectures, operational databases stream mutation events—such as record c...
Digital streaming platforms analyze subscriber navigation logs to understand engagement patterns. In continuou...
E-commerce and media streaming services map user interaction trajectories to evaluate campaign efficacy and pr...
Digital marketplaces analyze browsing sessions to measure conversion velocity and user engagement efficiency. ...
Reconcile customer records across three source tables (customer_source_primary_091, customer_source_secondary_...
Build an automated quality enforcement pipeline that processes raw_orders_092 to produce a trusted dataset con...
Reconcile the existing baseline snapshot (order_snapshot_093) with the daily update stream (order_incremental_...
Reconcile daily financial revenue figures (finance_daily_revenue_094) against detailed operational transaction...
Construct an end-to-end Customer 360 pipeline integrating customer_profiles_095, customer_accounts_095, custom...
Digital analytics platforms monitor high-frequency browsing interactions across customer accounts. Analyze the...
Customer relationship data warehouses periodically refresh baseline customer dimensions using delta updates. E...
Master customer repositories process continuous mutation streams containing inserts, updates, and deletions al...
Financial data engineering pipelines audit daily settlement feeds against authorized corporate general ledgers...
Enterprise data architectures unite multiple domain feeds into a comprehensive analytical warehouse. Combine c...
Expert Production Architectures
Master production data engineering patterns including multi-source feed consolidation, temporal validity window analytics, multi-stage revenue pipelines, CDC stream merging, IoT anomaly detection, and entity deduplication.
19 Core Curriculum Modules (PY-101 to PY-125)
In high-throughput event processing pipelines, unpartitioned aggregations across skewed customer keys cause st...
In distributed analytics platforms, heavy hitters create unbalanced partitions where individual tasks process ...
Transactional streaming and ingestion pipelines frequently process high-velocity transaction streams that must...
In enterprise financial systems, daily ledger settlement pipelines ingest raw delimited files originating from...
Modern web platforms record user events in semi-structured JSON log stores. Downstream marketing automation an...
High-volume media streaming platforms rely on columnar storage formats like Parquet to store telemetry and pla...
Financial analytics engines periodically compile active customer account snapshots to assess portfolio balance...
Supply chain fulfillment centers monitor warehouse stock valuation across product catalogs to optimize repleni...
E-commerce merchant intelligence systems process transaction ledgers to identify top-performing accounts and c...
Mobile and web telemetry streams continuously emit user engagement events to operational ingestion endpoints. ...
Supply chain fulfillment coordinators oversee continuous merchandise restock priority across regional distribu...
Enterprise payment networks receive transactional ledger lines from independent regional processing clusters. ...
Payment infrastructure platforms process millions of financial ledger events daily. Merchant risk officers and...
Enterprise payment networks stream financial transaction batches that contain merchant references but lack ful...
Omnichannel fulfillment centers maintain dynamic pricing schedules that vary based on product stock and region...
Financial institutions conduct daily regulatory reconciliations between master client portfolios and periodic ...
Process the records from customer_purchases_119 to identify the top 2 purchases for each market segment: - Eva...
Process the records from customer_revenue_trend_120: - Exclude any transaction where transaction_status is not...
Analyze chronological account milestones in customer_behavior_121: - For each customer, sequence milestones ch...
Enterprise Platform Capstone
Enterprise capstones currently in development. Target curriculum spans 10 challenges (PY-126 through PY-135) assessing end-to-end data platform architectures, multi-feed CDC reconciliation, and lakehouse pipeline engineering.