Join us for this presentation as we transition from design and planning into the implementation of data pipelines and orchestration. Explore the intricacies of building and orchestrating data pipelines in this session, covering tools, coding with Python, deployments with Docker.

Agenda:

Understanding Data Pipelines: 

• Delve into the concept of data pipelines and their significance in modern data engineering.

Implementation Options: 

• Explore different approaches to implementing data pipelines, including code-centric and low-code tools.

Pipeline Orchestration: 

• Learn about the role of orchestration in managing complex data workflows and the tools available, such as Apache Airflow, Apache Spark, Prefect, and Azure Data Factory.

Cloud Resources: 

• Identify the necessary cloud resources for staging environments and data lakes to support efficient data pipeline deployment.

Implementing Flows: 

• Examine the process of building data pipelines, including defining tasks, components, and logging mechanisms.

Deployment with Docker: 

• Discover how Docker containers can be used to isolate data pipeline environments and streamline deployment processes.

Monitor and Operations: 

• Manage operational concerns related to data pipeline performance, reliability, and scalability.

Why Join This Session?

- Gain practical insights into building and managing data pipelines.

- Learn coding techniques with Python for efficient data pipeline development.

- Discover the benefits of Docker deployments for data pipeline management.

- Understand the significance of data orchestration in the data engineering process.

- Connect with industry professionals and expand your network.

- Stay updated on the latest trends and advancements in data pipeline architecture and orchestration.

Please RSVP to secure your spot for this enriching session. Looking forward to exploring the future of data engineering together!