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36 resultsIntroduction to Data Pipelines
What a data pipeline is, the core stages, and when to build vs buy.
Database Schema Migration Strategies
Expand-contract pattern, zero-downtime migrations, and tooling.
Data Warehouse Modelling — Star Schema and Dimensional Design
Facts, dimensions, slowly changing dimensions, and why modelling choices matter for query performance.
CI/CD Pipeline Design — From Commit to Production
Stages, gates, deployment strategies, and keeping pipelines fast.
Privacy-First Data Design — PII Handling Patterns
Tokenisation, pseudonymisation, encryption at rest, and right-to-deletion workflows.
Progressive Delivery — Feature Flags, Canary, and Dark Launching
Techniques for releasing software confidently at any scale.
Apache Iceberg — The Open Table Format Explained
Snapshots, schema evolution, partition evolution, time travel, and compaction.
REST API design principles we follow
Versioning, error formats, pagination, and auth patterns used across all Intersysop-built APIs.
Multi-Tenancy Patterns — Database-per-Tenant, Schema-per-Tenant, and Row-Level
Tradeoffs for SaaS data isolation, compliance, and operational complexity.
Getting Started with dbt (data build tool)
Models, tests, documentation, and the dbt workflow for transforming warehouse data.
Delta Lake — ACID Transactions for Your Data Lake
Transaction log, upserts, schema enforcement, and time travel on S3.
Event Sourcing and CQRS — Practical Implementation
Event store design, projection rebuilding, and operational realities.
CDN and Edge Caching Strategy
Origin offload, cache key design, purging, and choosing a CDN.
Schema Registry and Avro for Kafka Data Contracts
Why schema management matters for streaming pipelines and how to implement it.
gRPC Service Design — Protocol Buffers and Production Patterns
Proto file design, streaming, deadlines, interceptors, and error handling.
Designing a Data Lake on AWS S3
Folder structure, naming conventions, lifecycle policies, and access patterns.
Data Lake vs Data Warehouse vs Lakehouse
Practical comparison of the three architectures and how to choose.
Data Observability — Detecting Silent Pipeline Failures
Freshness, volume, distribution, schema, and lineage monitoring for data reliability.
Airflow Best Practices for Production Pipelines
Idempotency, backfilling, SLA misses, and common pitfalls to avoid.
HTTP Caching Strategies for APIs and Web Applications
Cache-Control headers, ETags, CDN caching, and cache invalidation.
MongoDB Schema Design Patterns
Embedding vs referencing, the subset pattern, and indexing strategy.
Time-Series Databases — InfluxDB vs TimescaleDB vs ClickHouse
Comparing purpose-built and general-purpose solutions for time-series data.
Migrating from MySQL to PostgreSQL
Schema translation, data migration, and common incompatibilities to address.
GraphQL vs REST — When to Use Each
Comparing query flexibility, over-fetching, tooling, and operational complexity.
Implementing Data Lineage Tracking
Column-level lineage, tools, and why it is critical for debugging and compliance.
API Error Handling — Consistent Error Responses
Error format standards, HTTP status code usage, and client-friendly error design.
Designing a Reliable Webhook System
Delivery guarantees, signature verification, retry logic, and consumer best practices.
Background Job Queue Design
Idempotency, retries, dead letter queues, and job observability.
Idiomatic REST API Design Patterns
Naming conventions, filtering, sorting, sparse fieldsets, and HATEOAS considerations.
Designing and Publishing API Client SDKs
Auto-generation vs handwritten, retry logic, versioning, and developer experience.
Data & Platform — Service Overview
Pipelines, vector stores, governance, and privacy-first data design.
Testing Strategy for Data Pipelines
Unit tests, integration tests, data contract tests, and regression testing for pipelines.
Parquet vs CSV — Why Columnar Storage Matters
How Parquet's columnar format reduces storage costs and speeds up analytical queries.
API Pagination — Cursor, Offset, and Keyset Patterns
When each method works, performance tradeoffs, and implementation details.
OpenAPI Spec-First API Development
Write the contract before writing code — benefits, tooling, and workflow.
Data Contracts — Formalising Agreements Between Producers and Consumers
Schema, SLAs, semantics, and how to enforce data contracts in practice.