Live Online Fivetran Course for Data Engineering

Live Course Module: Fivetran Course for Data Engineering

Total Duration: 24 Hours (6 Weeks)

Week 1: Foundations of Modern Data Integration (4 hours)

Goal: Understand the fundamentals of Fivetran and ELT concepts.

1. Introduction to the Modern Data Stack (45 mins)

   • Overview of ETL vs ELT

   • Why Data Engineers prefer ELT tools

   • Fivetran’s role in the modern analytics pipeline

2. Introduction to Fivetran (45 mins)

   • What is Fivetran and how it works

   • Fivetran architecture & key components

   • Use cases and advantages for data engineers

3. Getting Started: Account Setup & UI Overview (1 hour)

   • Setting up a free Fivetran account

   • Navigating the dashboard and console

   • Exploring connectors and destinations catalog

4. First Hands-on Project: Simple Data Sync (1.5 hours)

   • Connecting a source (e.g., MySQL or Google Sheets)

   • Setting a destination (e.g., BigQuery or Snowflake)

   • Executing and validating first data load

Week 2: Core Concepts — Connectors, Destinations & Data Flow (4 hours)

Goal: Learn to configure, monitor, and troubleshoot Fivetran connectors.

1. Understanding Fivetran Connectors (1 hour)

   • Types of connectors (Databases, SaaS apps, Files, Events)

   • Incremental syncs and change data capture (CDC)

   • Scheduling syncs and managing sync frequency

2. Destination Configuration (1 hour)

   • Supported destinations (BigQuery, Snowflake, Databricks, Redshift)

   • Authentication, roles, and permissions setup

   • Schema management best practices

3. Schema Evolution and Data Modeling (1 hour)

   • How Fivetran handles schema changes automatically

   • Naming conventions, table mapping, and primary keys

   • Handling deletions and soft deletes

4. Monitoring and Troubleshooting (1 hour)

   • Connector logs and error types

   • Sync performance analysis

   • Notification settings and alert configuration

Week 3: Transformations and dbt Integration (4 hours)

Goal: Learn to manage transformations and integrate Fivetran with dbt.

1. Transformations in Fivetran (1 hour)

   • Understanding in-warehouse transformations

   • Transformation scheduling and dependencies

   • SQL-based transformation workflow

2. dbt Integration with Fivetran (1 hour 30 mins)

   • Setting up dbt inside Fivetran

   • Creating models, tests, and documentation

   • Orchestrating ELT pipelines with Fivetran + dbt

3. Hands-on Project: Build a dbt-Enabled Fivetran Pipeline (1.5 hours)

   • Connect → Transform → Validate workflow

   • Hands-on with dbt packages and Fivetran transformations

Week 4: Security, Governance & Performance Optimization (4 hours)

Goal: Learn to secure, optimize, and govern your data pipelines.

1. Security and Compliance in Fivetran (1 hour)

   • Encryption, authentication, and access management

   • Role-based access control (RBAC)

   • Compliance standards (GDPR, HIPAA, SOC 2)

2. Audit Trails & Metadata Management (1 hour)

   • Connector logs, metadata tracking, and audit trails

   • Integration with monitoring tools (Datadog, CloudWatch)

3. Performance Optimization (1 hour 30 mins)

   • Optimizing sync performance

   • Managing large datasets efficiently

   • Cost optimization: Active row pricing model

4. Best Practices Review (30 mins)

   • Recommended naming, scheduling, and monitoring strategies

Week 5: Automation, APIs & Advanced Integrations (4 hours)

Goal: Learn to automate, extend, and customize Fivetran with APIs.

1. Automation & Scheduling (1 hour)

   • Automating pipeline execution

   • Webhooks and event-driven scheduling

   • Integration with Airflow / Prefect for orchestration

2. Fivetran REST API (1 hour 30 mins)

   • Overview of API endpoints

   • Managing connectors via API

   • API-based monitoring and automation demo

3. Advanced Integrations (1 hour 30 mins)

   • Integrating with Data Catalogs & Observability tools

   • Using Fivetran with dbt Cloud, Looker, or Power BI

   • Multi-environment pipeline setup (dev → prod)

Week 6: Enterprise Deployment & Capstone Project (4 hours)

Goal: Apply all learned skills to build a real-world enterprise-grade pipeline.

1. Enterprise-Scale Deployment (1 hour)

   • Multi-region setup and scaling

   • CI/CD with Fivetran + GitHub Actions

   • Managing multiple teams and environments

2. Capstone Project (2 hours)

   • End-to-End Pipeline Build:

     • Source: PostgreSQL / Salesforce

     • Destination: Snowflake / BigQuery

     • Transformations: dbt integration

     • Automation: Fivetran API or Airflow orchestration

   • Test, monitor, and document your pipeline

3. Final Review, Q&A, and Certification (1 hour)

   • Summary of core-to-advanced features

   • Common interview questions & industry use cases

   • Certification assessment & feedback

🧩 Optional Add-ons

• Fivetran API Lab: Extended practice on automation and scaling.

• Advanced Data Observability Module: Integration with tools like Monte Carlo, Soda, or Metaplane.

🧰 Tools & Technologies

• Fivetran (Web UI & REST API)

• Cloud Data Warehouse: Snowflake / BigQuery / Redshift / Databricks

• dbt Core / dbt Cloud

• Airflow / Prefect (for orchestration)

• GitHub / GitLab (for CI/CD)

• Visualization Tool: Looker / Metabase / Tableau

🎯 Learning Outcomes

By the end of this course, learners will:
✅ Build, schedule, and monitor automated ELT pipelines using Fivetran
✅ Integrate Fivetran with dbt for data transformations
✅ Manage schema evolution, transformations, and governance
✅ Utilize APIs for automation and enterprise-grade deployment
✅ Design optimized, secure, and production-ready data pipelines