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Build and expand your data skills by attending this class and asking questions to our Databricks experts, taking place between 21 and 23 March.

Onboarding Advanced course consists of 3-day sessions: 1) Streaming with Delta Live Tables; 2) Data Analysis with Databricks SQL; 3) Implementing MLOps in Databricks Lakehouse. Upon completion of course (attend at least 1 of 3 sessions), survey, and accreditation, you will receive a 75% certification voucher to take on a Databricks certification exam for the course.

Activate Training Series - Onboarding Advanced

Tuesday 21 March - Thursday 23 March
9:30 AM-10:30 AM IST

12:00 PM-1:00 PM SGT

3:00 PM-4:00 PM AEDT

Day 1: Streaming with Delta Live Tables

During this 1-hour session, you will learn about how to do streaming on Databricks using Delta Live Tables. With a hands-on example, you will learn about how Delta Live Tables simplifies the orchestration and accelerates the development of streaming pipelines. We will also cover how to monitor data quality.

Topics covered:

• Delta Live Tables
• Autoloader
• Data quality monitoring  

Day 2: Data Analysis with Databricks SQL

During this 1-hour session, you will learn about Data Analysis and Visualization using Databricks SQL. Topics covered during this session will help you to run SQL queries and create dashboards on data stored in your data lake.

Topics covered:

• Introduction to Databricks SQL
     - Queries
     - Visualizations
     - Dashboards and alerts
• SQL endpoints
     - Creating and managing endpoints
     - Endpoint sizing
     - Photon
• Query Performance
     - Query profile
     - Query caching
• Remote query execution & BI-partner connect

Day 3: Implementing MLOps in Databricks Lakehouse

During this 1-hour session, you will learn about how to implement MLOps (DataOps + DevOps + ModelOps) in Databricks Lakehouse. Topics covered during this session will help you to build efficient, reliable, reproducible, and well-documented ML pipelines. 

Topics covered: 

• MLflow
     - MlFlow recap
     - MLflow auto-auto logging demo
• Feature Store
     - Role of Feature Store in MLOps
     - Feature Store UI demo
     - Upstream Lineage, Downstream Lineage, Feature Discoverability
• AutoML
     - Glassbox” approach for AutoML
     - AutoML Demo
• Models registry
• Models deployment