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The Data Architect's Guide to Databricks

Modern data platforms live or die by the architectural decisions made in their first few weeks - decisions that quietly shape everything the platform can and can't do for years afterward. The Data Architect's Guide to Databricks is a comprehensive, practitioner-focused roadmap for designing, governing, and scaling a production-grade lakehouse on Databricks.

Starting with the lakehouse paradigm itself, this book walks architects and senior engineers through the full stack of the Databricks platform: the control plane and data plane split that determines where your data lives and who can reach it; Delta Lake's transaction log, which turns plain files into governed, ACID-compliant tables; and Unity Catalog, the account-level governance layer that unifies access, lineage, and audit across every workspace.

From there, the book moves into the engineering decisions that separate a working prototype from a resilient production system - medallion architecture as a set of real engineering contracts, ingestion patterns from Auto Loader to Lakeflow Declarative Pipelines, and a decision framework for matching compute (clusters, Photon, SQL Warehouses, serverless) to workload instead of defaulting to habit. Later chapters tackle orchestration with Jobs and Asset Bundles, data modeling for a streaming-first world, and Lakebase for operational workloads that don't fit a traditional warehouse.

No architecture is complete without operating it well, so the book dedicates full sections to performance tuning and cost as a single FinOps discipline, security and compliance mapped to SOC 2, HIPAA, GDPR, and FedRAMP, and MLOps with MLflow and model serving. A dedicated chapter on Generative AI and Mosaic AI shows how RAG, fine-tuning, and agents extend the same governed platform rather than requiring a separate stack.

The book closes by zooming out: multi-cloud and multi-workspace architecture, disaster recovery, CI/CD for data platforms, five industry-grounded reference architectures, and a forward-looking chapter on where lakehouse architecture is headed next.

Whether you're designing your first Databricks deployment or hardening one that's already in production, this book gives you the frameworks, trade-offs, and hard-won lessons to make architectural decisions with confidence.

What you'll learn:

• How Delta Lake, Unity Catalog, and the medallion architecture fit together as a coherent governance and engineering model
• How to choose the right ingestion, compute, and orchestration patterns for your workload
• How to operationalize ML and GenAI on governed lakehouse data
• How to design for cost, security, compliance, and disaster recovery at enterprise scale
• Real reference architectures and the mistakes that recur across industries

Parametry knihy

• Plný název: The Data Architect's Guide to Databricks
• Podnázev: A Complete Guide to Designing, Securing, and Scaling the Lakehouse Platform
• Autor: Khokan Sarkar
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 298
• EAN: 9798190484823
• ID: 53440192
• Nakladatelství: Independently published
• Hmotnost: 596 g
• Rozměry: 254 × 203 × 16 mm
• Datum vydání: 03. August 2026

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