Data Operations — Automation, Monitoring & Reliability

Learn how to automate, monitor, and optimize modern data pipelines with best practices in reliability, observability, and governance. Build resilient systems using Airflow, dbt, and CI/CD pipelines to ensure trust and uptime in enterprise data environments.

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Duration: 8 weeks · Self-paced or cohort-based · 300+ lessons and real-world case studies

Program Snapshot

  • • Data pipeline orchestration (Airflow, Prefect)
  • • dbt transformations and version control
  • • Observability, lineage, and monitoring with OpenLineage & Prometheus
  • • Incident management, SLAs, and cost optimization
  • • DataOps CI/CD automation & deployment strategies
Starting at Contact · Includes labs and certification badge

Why Data Operations?

DataOps is the next evolution of DevOps for data teams — combining automation, observability, and governance to deliver high-quality, reliable data at scale. This course helps you operationalize trust in your data ecosystem through automated workflows, lineage tracking, and real-time monitoring.

Reliability Engineering

Design data pipelines that recover gracefully, self-heal, and meet SLAs through proactive monitoring and alerting.

Automation & CI/CD

Automate code deployments, testing, and rollback strategies with GitHub Actions, Jenkins, or GitLab CI.

Observability & Lineage

Track dependencies, data lineage, and performance metrics using OpenLineage, Great Expectations, and Grafana dashboards.

Core Modules

Module 1 — Foundations of DataOps

  • Principles of DataOps & comparison with DevOps
  • DataOps lifecycle and stakeholder roles
  • Version control for data & configuration management

Module 2 — Pipeline Automation

  • Airflow, Prefect & Dagster workflows
  • Scheduling, task retries, and dependency management
  • Dynamic pipelines and modular DAG design

Module 3 — Testing & Validation

  • Data testing strategies (unit, regression, validation)
  • Great Expectations, dbt tests, and data SLAs
  • Automated anomaly detection pipelines

Module 4 — Observability & Monitoring

  • Lineage tracking with OpenLineage & Marquez
  • Dashboards: Prometheus, Grafana, and ELK stack
  • Alerting frameworks & on-call processes

Module 5 — Incident Response & Reliability

  • Incident management playbooks & escalation
  • Post-mortems, RCA templates, and SLOs
  • Chaos testing and recovery drills

Module 6 — Governance & Cost Ops

  • DataOps governance & approval flows
  • FinOps practices for data cost optimization
  • Security, privacy, and audit logging

Hands-on Labs

CI/CD for Data Pipelines

Implement Git-based CI/CD with Airflow + dbt using GitHub Actions or Jenkins.

Pipeline Observability

Integrate OpenLineage & Prometheus to visualize pipeline health and latency metrics.

Incident Simulation

Simulate data pipeline failure scenarios and execute automated recovery with alerts.

Pricing & Certification

Self-paced

Contact

All modules, labs, and certification quizzes. Access for 1 year.

Cohort (Instructor-led)

Contact

8-week live cohort, mentorship sessions, and career project feedback.

Enterprise Track

Custom Pricing

For teams. Private labs, integration with internal tools, and optional certification exam.

Graduates earn a Yukti Certified DataOps Practitioner badge and access alumni community.

Get Started

Join Yukti’s Data Operations Certification Program — learn to build reliable, automated, and observable data systems.