Data Architecture
19 items tagged with "data-architecture"
Best Practices14
Data Mesh Principles
Domain-oriented, self-serve data infrastructure principles promoting product thinking for data.
CQRS (Command Query Responsibility Segregation)
An architecture pattern that separates the model that writes data (commands) from the model that reads it (queries), allowing each side to scale and evolve independently.
Event Sourcing
An architecture pattern that stores every change to application state as an immutable sequence of events, making the event log the source of truth instead of current state.
Data Governance Framework
A structured set of roles, policies, and processes that make an organization accountable for the quality, security, and proper use of its data assets.
Medallion Architecture
A layered data design that refines data through Bronze (raw), Silver (cleaned and conformed), and Gold (business-ready) tables to improve quality and reuse.
Data Lakehouse Architecture
An architecture that combines the low-cost, open storage of a data lake with the transactions, schema, and performance of a data warehouse using open table formats.
ELT vs ETL Best Practices
Guidance on when to transform data before loading (ETL) versus loading raw and transforming in the warehouse (ELT), and how to run each pattern well.
Reverse ETL
The practice of moving modeled data from the warehouse back into operational tools like CRM and marketing platforms so business teams act on it directly.
Schema Evolution and Schema Registry
Managing how data schemas change over time with compatibility rules and a central registry so producers and consumers evolve without breaking each other.
Data Catalog and Discovery
A searchable inventory of an organization's data assets with metadata, ownership, and lineage so people can find, understand, and trust the data they need.
Apache Kafka Streaming Best Practices
Design and operational guidance for building reliable, scalable event streaming on Apache Kafka, covering topics, partitions, delivery semantics, and consumers.
Vector Database Best Practices
A vector database stores embeddings and serves fast similarity search for AI features like RAG and semantic search; best practices cover indexing, metadata, and freshness.
Test Data Management
Practices for provisioning realistic, isolated, and compliant test data so tests are reliable, repeatable, and free of production data exposure.
GDPR Compliance Engineering
GDPR compliance engineering turns the EU General Data Protection Regulation's legal principles into concrete technical controls: lawful processing, data minimization, consent, and data-subject rights.