Databricks has published a comprehensive guide on data pipeline best practices, covering architecture, modern pipeline design, and deployment strategies. The guide emphasizes the importance of deliberate architectural choices for reliability and cost-efficiency, including selecting between batch and streaming modes and optimizing storage. It also highlights the necessity of robust operational practices such as version control, CI/CD, and comprehensive monitoring for production readiness. AI
IMPACT Provides guidance on building and managing data infrastructure essential for AI/ML workloads.
RANK_REASON Blog post detailing best practices for data pipeline architecture and deployment.
- Ci Cd
- Databricks
- Data contracts
- data lake
- data warehouse
- infrastructure as code
- Kappa Architecture
- Lakehouse
- Lambda architecture
- Modern Data Stack
- Zero-ETL
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