What you’ll learn
After completing this course, students will be able to:
Understand Azure Databricks fundamentals
Configure and manage workspaces
Integrate with Microsoft services
Optimize compute resources
Use Unity Catalog effectively
Implement data security controls
Manage identities and credentials
Build ingestion and transformation pipelines
Apply data quality and governance
Orchestrate, deploy, and monitor pipelines
Small and Medium Business at Lumify Work
As the leading provider of information and communications technology training in Australasia, we designed and put together training programs to help small businesses keep pace with the technological changes that drive business transformation.
Who is the course for?
The target audience is data engineers who have fundamental knowledge of data analytics concepts, a basic understanding of cloud storage, and familiarity with data organization principles. They should be comfortable working with SQL and have experience using Python, including notebooks, for data engineering tasks. Learners are expected to have a good understanding of Azure Databricks workspaces and Unity Catalog, along with familiarity with data access patterns and core data engineering and data warehouse concepts. In addition, they should have foundational knowledge of Azure security, including Microsoft Entra ID, and be familiar with Git version control fundamentals.
Course subjects
Set up and configure an Azure Databricks environment
Explore Azure Databricks
Understand Azure Databricks architecture
Understand Azure Databricks Integrations
Select and Configure Compute in Azure Databricks
Create and organize objects in Unity Catalog
Secure and govern Unity Catalog objects in Azure Databricks
Prepare and process data with Azure Databricks
Design and implement data modeling with Azure Databricks
Ingest data into Unity Catalog
Cleanse, transform, and load data into Unity Catalog
Implement and manage data quality constraints with Azure Databricks
Deploy and maintain data pipelines and workloads with Azure Databricks
Design and implement data pipelines with Azure Databricks
Implement Lakeflow Jobs with Azure Databricks
Implement development lifecycle processes in Azure Databricks
Monitor, troubleshoot and optimize workloads in Azure Databricks
Prerequisites
Prerequisite certification is not required before taking this course. Successful Azure Data Fundamentals students start with some basic awareness of computing and Internet concepts, and an interest in extracting insights from data.
Specifically:
Fundamental knowledge of data analytics concepts
Basic understanding of cloud storage concepts
Familiarity with SQL and data organization principles
Good understanding of Azure Databricks workspaces and Unity Catalog concepts
Familiarity with SQL and data access patterns
Knowledge of Microsoft Entra ID and Azure security fundamentals
Familiarity with SQL and Python programming
Knowledge of fundamental data engineering and data warehouse concepts
Familiarity with data engineering concepts and SQL
Experience with Python programming and notebooks
Knowledge of Git version control fundamentals
Terms & Conditions
The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.
