Search results
16 resultsApplied AI & ML — Service Overview
Everything included in our Applied AI engagements: RAG, agents, fine-tuning, evals, and guardrails.
Building a Data Quality Framework
Dimensions of data quality, validation layers, and monitoring in production pipelines.
Apache Kafka — Core Concepts and When to Use It
Topics, partitions, consumer groups, and the use cases where Kafka excels.
Introduction to Data Pipelines
What a data pipeline is, the core stages, and when to build vs buy.
CI/CD Pipeline Design — From Commit to Production
Stages, gates, deployment strategies, and keeping pipelines fast.
Product Engineering — Service Overview
APIs, dashboards, and services delivered with tests, CI/CD, and observability from day one.
Airflow Best Practices for Production Pipelines
Idempotency, backfilling, SLA misses, and common pitfalls to avoid.
Batch vs Streaming Pipelines — Choosing the Right Pattern
Lambda architecture, Kappa architecture, and practical guidance for choosing.
Monitoring and Alerting for Data Pipelines
What to monitor, SLIs/SLOs for data, and building effective alerting.
Schema Registry and Avro for Kafka Data Contracts
Why schema management matters for streaming pipelines and how to implement it.
Container Registry Management and Image Lifecycle
Tagging conventions, vulnerability scanning, retention policies, and registry options.
Stream Processing with Apache Flink
Event time vs processing time, windows, stateful operators, and production deployment.
Orchestrating Pipelines with Apache Airflow
DAGs, operators, scheduling, and production best practices for Airflow.
Data & Platform — Service Overview
Pipelines, vector stores, governance, and privacy-first data design.
Feature Stores — Bridging Data Engineering and ML
What a feature store is, online vs offline stores, and when to build vs buy.
Testing Strategy for Data Pipelines
Unit tests, integration tests, data contract tests, and regression testing for pipelines.