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- Memory Management in PySpark- CPU Cores, executors, executor memory
- Memory Management in PySpark- Scenario 1, 2
- Develop and maintain CI/CD pipelines using GitHub for automated deployment, version control
- Complete guide to building and managing data workflows in Azure Data Factory (ADF)
- Complete guide to architecting and implementing data governance using Unity Catalog on Databricks
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Tag: Azure Databricks
Hereβs a complete blueprint to help you develop and maintain CI/CD pipelines using GitHub for automated deployment, version control, and DevOps best practices in data engineering β particularly for Azure + Databricks + ADF projects. π PART 1: Develop & Maintain CI/CD Pipelines Using GitHub β Technologies & Tools Tool Purpose GitHub Code repo +…
Hereβs a complete guide to building and managing data workflows in Azure Data Factory (ADF) β covering pipelines, triggers, linked services, integration runtimes, and best practices for real-world deployment. ποΈ 1. What Is Azure Data Factory (ADF)? ADF is a cloud-based ETL/ELT and orchestration service that lets you: π 2. Core Components of ADF Component…
Here’s a complete guide to architecting and implementing data governance using Unity Catalog on Databricks β the unified governance layer designed to manage access, lineage, compliance, and auditing across all workspaces and data assets. β Why Unity Catalog for Governance? Unity Catalog offers: Feature Purpose Centralized metadata Unified across all workspaces Fine-grained access control Table,…
Designing and developing scalable data pipelines using Azure Databricks and the Medallion Architecture (Bronze, Silver, Gold) is a common and robust strategy for modern data engineering. Below is a complete practical guide, including: π· 1. What Is Medallion Architecture? The Medallion Architecture breaks a data pipeline into three stages: Layer Purpose Example Ops Bronze Raw…