Data Engineering Zoomcamp
- Register in DataTalks.Club's Slack
- Join the
#course-data-engineering
channel - Join the course Telegram channel with announcements
- The videos are published on DataTalks.Club's YouTube channel in the course playlist
- Frequently asked technical questions
Syllabus
- Week 1: Introduction & Prerequisites
- Week 2: Workflow Orchestration
- Week 3: Data Warehouse
- Week 4: Analytics Engineering
- Week 5: Batch processing
- Week 6: Streaming
- Week 7, 8 & 9: Project
Taking the course
2024 Cohort
- Start: 15 January 2024 (Monday) at 17:00 CET
- Registration link: https://airtable.com/shr6oVXeQvSI5HuWD
- Subscribe to our public Google Calendar (it works from Desktop only)
- Cohort folder with homeworks and deadlines
Self-paced mode
All the materials of the course are freely available, so that you can take the course at your own pace
- Follow the suggested syllabus (see below) week by week
- You don't need to fill in the registration form. Just start watching the videos and join Slack
- Check FAQ if you have problems
- If you can't find a solution to your problem in FAQ, ask for help in Slack
Syllabus
Note: NYC TLC changed the format of the data we use to parquet. But you can still access the csv files here.
Week 1: Introduction & Prerequisites
- Course overview
- Introduction to GCP
- Docker and docker-compose
- Running Postgres locally with Docker
- Setting up infrastructure on GCP with Terraform
- Preparing the environment for the course
- Homework
Week 2: Workflow Orchestration
- Data Lake
- Workflow orchestration
- Workflow orchestration with Mage
- Homework
Week 3: Data Warehouse
- Data Warehouse
- BigQuery
- Partitioning and clustering
- BigQuery best practices
- Internals of BigQuery
- Integrating BigQuery with Airflow
- BigQuery Machine Learning
Week 4: Analytics engineering
- Basics of analytics engineering
- dbt (data build tool)
- BigQuery and dbt
- Postgres and dbt
- dbt models
- Testing and documenting
- Deployment to the cloud and locally
- Visualizing the data with google data studio and metabase
Week 5: Batch processing
- Batch processing
- What is Spark
- Spark Dataframes
- Spark SQL
- Internals: GroupBy and joins
Week 6: Streaming
- Introduction to Kafka
- Schemas (avro)
- Kafka Streams
- Kafka Connect and KSQL
Week 7, 8 & 9: Project
Putting everything we learned to practice
- Week 7 and 8: working on your project
- Week 9: reviewing your peers
Course UI
Alternatively, you can access this course using the provided UI app, the app provides a user-friendly interface for navigating through the course material.
- Visit the following link: DE Zoomcamp UI
Asking for help in Slack
The best way to get support is to use DataTalks.Club's Slack. Join the #course-data-engineering
channel.
To make discussions in Slack more organized:
- Follow these recommendations when asking for help
- Read the DataTalks.Club community guidelines
Overview
Architecture diagram
Technologies
- Google Cloud Platform (GCP): Cloud-based auto-scaling platform by Google
- Google Cloud Storage (GCS): Data Lake
- BigQuery: Data Warehouse
- Terraform: Infrastructure-as-Code (IaC)
- Docker: Containerization
- SQL: Data Analysis & Exploration
- Mage: Workflow Orchestration
- dbt: Data Transformation
- Spark: Distributed Processing
- Kafka: Streaming
Prerequisites
To get the most out of this course, you should feel comfortable with coding and command line and know the basics of SQL. Prior experience with Python will be helpful, but you can pick Python relatively fast if you have experience with other programming languages.
Prior experience with data engineering is not required.
Instructors
Tools
For this course, you'll need to have the following software installed on your computer:
- Docker and Docker-Compose
- Python 3 (e.g. via Anaconda)
- Google Cloud SDK
- Terraform
See Week 1 for more details about installing these tools
Supporters and partners
Thanks to the course sponsors for making it possible to run this course
Do you want to support our course and our community? Please reach out to alexey@datatalks.club