Google Cloud training

Data Engineering Solutions Lab (DSL)

The Data Engineering Solutions Lab (DSL) is a 10-Day, focused, immersive learning experience that rapidly upskills your team on Google Cloud data engineering principles and best practices. The program combines five days of expert-led training sessions on key data engineering concepts (e.g., data warehousing, pipelines, data quality) with hands-on labs and a five-day collaborative capstone project. The capstone challenges participants to address a real-world use case using Google Cloud tools.

  • Duration: 10 days
  • Languages: English, German
  • Level: Advanced
  • Group size: Up to 16

What you'll learn

  • Accelerate data engineering adoption: Master essential skills and best practices quickly, enabling faster implementation and value realization.
  • Boost data-driven decision making: Equip your team to confidently leverage Google Cloud's powerful data tools and services for deeper insights and informed actions.
  • Shorten the path to ML success: Build a strong data engineering foundation to prepare your organization for successful machine learning implementation.

Prerequisites

  • Modernizing Data Lakes and Data Warehouses with Google Cloud.
  • Building Batch Data Pipelines on Google Cloud.
  • Building Resilient Streaming Analytics Systems on Google Cloud.

Course outline

1
  • Accelerate data engineering adoption: Master essential skills and best practices quickly, enabling faster implementation and value realization.
  • Boost data-driven decision making: Equip your team to confidently leverage Google Cloud's powerful data tools and services for deeper insights and informed actions.
  • Shorten the path to ML success: Build a strong data engineering foundation to prepare your organization for successful machine learning implementation.
Delivery/Modality
  • DSL will use an immersive blended learning approach, combining expert-led instructor sessions with self-paced, hands-on lab activities.
  • Participants will interact in real-time through a virtual classroom environment.

Related courses

Looker Developer Deep Dive

LookML serves as the foundation for visualization assets in Looker and is capable of dynamic aggregations, incrementally refreshed persistent derived tables, and more. In this course, you will practice the skills to be an advanced Looker Developer through guided lectures and independent exercises using sample data.

  • Duration: 2 days
  • Languages: English, German
  • Level: Advanced

Serverless Data Processing with Dataflow

This training is intended for big data practitioners who want to further their understanding of Dataflow in order to advance their data processing applications. Beginning with foundations, this training explains how Apache Beam and Dataflow work together to meet your data processing needs without the risk of vendor lock-in. The section on developing pipelines covers how you convert your business logic into data processing applications that can run on Dataflow. This training culminates with a focus on operations, which reviews the most important lessons for operating a data application on Dataflow, including monitoring, troubleshooting, testing, and reliability.

  • Duration: 3 days
  • Languages: English, German
  • Level: Advanced

AlloyDB Essentials

This course explores the benefits of AlloyDB, especially compared to PostgreSQL on Cloud SQL. It will walk you through AlloyDB’s unique architecture, and explain how to configure deployments on Google Cloud.The course is divided into two parts: AlloyDB Administration Essentials (architecture and configuration) and AlloyDB Optimization Essentials (performance tuning).

  • Duration: 3 hours
  • Languages: English, German
  • Level: Intermediate

Not sure which course fits?

Book a 30-minute call. We'll look at where your team is, what they need to be able to do, and put together either a specific course date or a tailored learning plan.