LMastering Lakehouse Architecture: Best Practices for Data Engineersakehouse Architecture Best Practices.pdf
- 1. LAKEHOUSE ARCHITECTURE BEST PRACTICES THE MODERN DATA PLATFORM DEMYSTIFIED FOR DATA ENGINEERS contact@accentfuture.com +91-96400 01789
- 2. WHAT IS LAKEHOUSE ARCHITECTURE? • Combines features of Data Lakes and Data Warehouses. • Supports both structured and semi-structured data. • Built for scalability, reliability, and performance. • Supports ACID transactions (with Delta Lake, Apache Hudi, Iceberg). • Enables machine learning, BI, streaming, and batch workloads. • Stores data once and uses it for multiple purposes. • Built on open standards (e.g., Parquet, Delta, Spark). • Unified governance, schema enforcement, and time- travel. • Enables real-time and historical data analytics. • Foundation for modern data engineering workflows. contact@accentfuture.com +91-96400 01789
- 3. KEY COMPONENTS OF A LAKEHOUSE • Storage Layer: Cost-effective, scalable object storage (S3, ADLS, GCS). • Table Format: Delta Lake, Apache Hudi, or Iceberg for ACID transactions. • Query Engine: Apache Spark, Trino, Presto, Databricks SQL. • Metadata Layer: Unity Catalog, Hive Metastore, AWS Glue Catalog. • Data Ingestion: Batch & Streaming tools like Kafka, Flink, Airbyte. • Governance & Security: Role-based access, lineage, audits. • ML & BI Integration: Native support for MLlib, DBT, Tableau, Power BI. • Orchestration: Airflow, Dagster, Azure Data Factory. • Monitoring: Lakehouse-native tools + Prometheus/Grafana integration. • Data Observability: Tools like Monte Carlo, Great Expectations. contact@accentfuture.com +91-96400 01789
- 4. WHY LAKEHOUSE OVER TRADITIONAL ARCHITECTURES? • Reduces data duplication and cost. • Offers flexibility across analytics and ML workloads. • Simplifies ETL/ELT and data governance. • Combines best of data lakes (scale) and warehouses (structure). • Real-time and batch data in one place. • Ensures strong data consistency with schema enforcement. • Improved performance with indexing, caching, Z- Ordering. • Version control and time-travel support. • Encourages agile development and faster insights. • Highly interoperable with open formats and engines. contact@accentfuture.com +91-96400 01789
- 5. LAKEHOUSE DESIGN PRINCIPLES • Modularity: Decouple compute, storage, catalog, and ingestion. • Data As Code: Versioning, CI/CD for data pipelines. • Schema Enforcement: Catch issues at write time. • Data Lineage: Track origins for governance and debugging. • Partitioning Strategy: Design for query performance. • Metadata First: Optimize with statistics and Z-Order. • Open Table Formats: Use Delta, Hudi, or Iceberg for portability. • Immutable Writes: Enable audit trails and rollback. • Security-First: Encrypt at rest/in-transit + RBAC. • Cost Optimization: Auto-compaction, file sizing, tiered storage. contact@accentfuture.com +91-96400 01789
- 6. BEST PRACTICES FOR DATA INGESTION • Use streaming for real-time data (Kafka, Flink). • Leverage CDC tools (Debezium, Fivetran) for change tracking. • Validate schema before ingestion to avoid corrupting tables. • Automate data quality checks with Great Expectations or Deequ. • Store raw data in a Bronze layer (immutable). • Maintain idempotency in ingestion jobs to avoid duplication. • Use append-only patterns to simplify merge conflict handling. • Automate schema evolution with metadata tracking. • Include data source watermark for time-based ingestion tracking. • Monitor ingestion lag and backfill on failures. contact@accentfuture.com +91-96400 01789
- 7. BEST PRACTICES FOR GOVERNANCE & SECURITY • Integrate Unity Catalog or AWS Lake Formation for RBAC. • Audit every read/write via logs. • Encrypt data at rest with KMS keys. • Implement masking for sensitive columns (PII). • Tag datasets by classification (public, internal, confidential). • Apply policies using tools like Immuta, Privacera. • Use token-based access for automation. • Avoid hardcoded credentials; use secret managers. • Monitor access patterns for anomalies. • Ensure compliance with HIPAA, GDPR, ISO standards. contact@accentfuture.com +91-96400 01789
- 8. BEST PRACTICES FOR RELIABILITY & SCALABILITY • Separate environments for dev, test, prod with data isolation. • Use autoscaling clusters with job queues. • Apply retry logic for flaky jobs. • Snapshot tables daily for rollback. • Use data validation tests in CI pipelines. • Ensure schema compatibility across services. • Automate alerting for failed pipelines. • Keep bronze → silver → gold layer separation clean. • Use scalable orchestration (Airflow, Prefect). • Monitor job duration, throughput, failures. contact@accentfuture.com +91-96400 01789
- 9. INTERVIEW QUESTIONS FOR DATA ENGINEERS • What is a Lakehouse? • A data platform combining benefits of Data Lake and Warehouse with ACID, reliability, and openness. • Name key components of a Lakehouse. • Object Storage, Table Format (Delta/Hudi), Query Engine, Metadata Catalog. • How is schema enforcement handled in Lakehouse? • By using Delta/Hudi which reject mismatched schemas at write time. • Explain Bronze, Silver, Gold layers. • Bronze: Raw data; Silver: Cleaned data; Gold: Aggregated for consumption. • What’s Z-Ordering? • Technique to colocate related data for efficient filtering. • Why use Delta Lake over traditional Parquet? • Delta supports ACID transactions, time travel, and scalable metadata. • How do you manage data versioning? • Delta and Iceberg allow snapshot-based versioning and rollback. • What tools are used for governance? • Unity Catalog, Lake Formation, Immuta. contact@accentfuture.com +91-96400 01789
- 10. HOW ACCENTFUTURE HELPS YOU LEARN LAKEHOUSE • Hands-on Delta Lake, Spark, Airflow labs. • Real-time project on building Lakehouse pipeline. • Live mentorship with working engineers. • Guidance on tools like Databricks, Snowflake, Kafka. • Mock interviews focused on Lakehouse architecture. • Access to notebooks, datasets, and templates. • Recorded sessions + lifetime access. • Certification + project support. • Resume and job portal help. • Community support and updates. contact@accentfuture.com +91-96400 01789
- 11. READY TO GET STARTED? • Visit: www.accentfuture.com • - Enroll: Azure + Databricks Data Engineering Course • Mode: 100% Online with Live Projects • Timings: Weekday & Weekend Batches • Includes Certification + Placement Assistance • Enroll now: https://www.accentfuture.com/enquiry- form/ • Call: +91 9640001789 • Become a Certified Cloud Data Engineer Today!