Data Management and Governance with Unity Catalog

Provides an introduction to the Databricks Data Intelligence Platform from a Data Engineer perspective.

In this course, you will learn about data governance and management using Databricks Unity Catalog. It begins with foundational concepts of data governance, highlighting the complexities and challenges in managing data lakes and the key functionalities of the Unity Catalog. The course then delves into Unity Catalog's architecture, emphasizing key concepts such as metastores, schemas, tables, and external storage access. Security and administration are thoroughly covered, detailing Databricks roles, identity management, and the security model. Advanced topics include fine-grained access control and privilege management, equipping learners with the skills to implement robust data governance and security measures in the Unity Catalog. The course includes practical demos and labs to reinforce theoretical knowledge.

Skill Level

Associate

Duration

Prerequisites

Beginner familiarity with cloud computing concepts (virtual machines, object storage, etc.)
Intermediate experience with basic SQL concepts such as SQL commands, aggregate functions, filters and sorting, indexes, tables, and views.
Basic knowledge of Python programming, jupyter notebook interface, and PySpark fundamentals.

Outline

- Data Governance Overview
- Demo: Populating the Metastore
- Lab: Navigating the Metastore
- Organization and Access Patterns
- Demo: Upgrading Tables to Unity Catalog
- Security and Administration in Unity Catalog
- Databricks Marketplace Overview
- Privileges in Unity Catalog
- Demo: Controlling Access to Data
- Fine-grained Access Control
- Lab: Securing Data in Unity Catalog
- Lakehouse Monitoring
- Demo: Lakehouse Monitoring

Upcoming Public Classes

Date	Time	Language	Price
Date	Time	Language	Price	Apr 02	09 AM - 01 PM (America/New_York)	Spanish	$750.00
Apr 07	09 AM - 01 PM (Europe/London)	English	$750.00
Apr 10	09 AM - 01 PM (Asia/Kolkata)	English	$750.00
Apr 11	09 AM - 01 PM (America/New_York)	English	$750.00
May 05	09 AM - 01 PM (Asia/Kolkata)	English	$750.00
May 07	01 PM - 05 PM (Europe/London)	English	$750.00
May 09	09 AM - 01 PM (America/New_York)	English	$750.00
Jun 09	09 AM - 01 PM (Europe/London)	English	$750.00
Jun 11	01 PM - 05 PM (Asia/Kolkata)	English	$750.00
Jun 12	01 PM - 05 PM (America/New_York)	English	$750.00
Jul 08	01 PM - 05 PM (Europe/London)	English	$750.00
Jul 10	09 AM - 01 PM (Asia/Kolkata)	English	$750.00
Jul 11	09 AM - 01 PM (America/New_York)	English	$750.00

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Upcoming Public Classes

Data Engineer

Automated Deployment with Databricks Asset Bundles

This course provides a comprehensive review of DevOps principles and their application to Databricks projects. It begins with an overview of core DevOps, DataOps, continuous integration (CI), continuous deployment (CD), and testing, and explores how these principles can be applied to data engineering pipelines.

The course then focuses on continuous deployment within the CI/CD process, examining tools like the Databricks REST API, SDK, and CLI for project deployment. You will learn about Databricks Asset Bundles (DABs) and how they fit into the CI/CD process. You’ll dive into their key components, folder structure, and how they streamline deployment across various target environments in Databricks. You will also learn how to add variables, modify, validate, deploy, and execute Databricks Asset Bundles for multiple environments with different configurations using the Databricks CLI.

Finally, the course introduces Visual Studio Code as an Interactive Development Environment (IDE) for building, testing, and deploying Databricks Asset Bundles locally, optimizing your development process. The course concludes with an introduction to automating deployment pipelines using GitHub Actions to enhance the CI/CD workflow with Databricks Asset Bundles.

By the end of this course, you will be equipped to automate Databricks project deployments with Databricks Asset Bundles, improving efficiency through DevOps practices.

AI/BI for Data Analysts

In this course, you’ll learn how to use the features Databricks provides for business intelligence needs: AI/BI Dashboards and AI/BI Genie. As a Databricks Data Analyst, you will be tasked with creating AI/BI Dashboards and AI/BI Genie Spaces within the platform, managing the access to these assets by stakeholders and necessary parties, and maintaining these assets as they are edited, refreshed, or decommissioned over the course of their lifespan. This course intends to instruct participants on how to design dashboards for business insights, share those with collaborators and stakeholders, and maintain those assets within the platform. Participants will also learn how to utilize AI/BI Genie Spaces to support self-service analytics through the creation and maintenance of these environments powered by the Databricks Data Intelligence Engine.

Build Data Pipelines with Delta Live Tables

In this course, you’ll learn how to define and schedule data pipelines that incrementally ingest and process data through multiple tables in the lakehouse using Delta Live Tables (DLT) in Spark SQL and Python. The course covers how to get started with DLT, how DLT tracks data dependencies in data pipelines, how to configure and run data pipelines using the Delta Live Tables UI, how to use Python or Spark SQL to define data pipelines that ingest and process data through multiple tables in the lakehouse using Auto Loader and DLT, how to use APPLY CHANGES INTO syntax to process Change Data Capture feeds, and how to review event logs and data artifacts created by pipelines and troubleshoot DLT syntax.

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