Everything your team needs to master Databricks - from first steps to fine-tuning.
Choose the right starting point based on your team’s experience. Each course builds toward deeper knowledge, better performance, and smarter workflows.
This course introduces core Databricks concepts, the Lakehouse architecture, and essential Spark and Delta Lake skills needed to read, transform, and write data. It provides the foundational understanding of compute, Unity Catalog, and basic data engineering tasks that all later courses assume.
This course expands on the fundamentals by introducing more complex transformations, Delta Live Tables, orchestration, metadata‑driven design, and governance through Unity Catalog. It focuses on practical engineering patterns - streaming, automation, CI/CD, cluster management, and parameterised pipelines - to build robust, maintainable workflows.
This course dives into advanced engineering and architectural topics, including deep Delta Lake mechanics, enterprise‑grade security, schema governance, and large‑scale deployment patterns (Terraform, DABs, REST API). It emphasises building production‑ready frameworks, monitoring, observability, performance tuning, and handling complex batch‑streaming scenarios.
This course specialises in understanding Spark’s execution model and teaching engineers how to diagnose and optimise performance across compute, shuffle, partitioning, Delta Lake operations, SQL, UDFs, and streaming. It develops the skills needed to interpret the Spark UI, resolve bottlenecks, and design cost‑efficient, high‑performing pipelines.
Explore our services and discover how we can help you turn data into your most valuable asset.
