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Databricks Streaming and Delta Live Tables

This course provides a comprehensive understanding of Spark Structured Streaming and Delta Lake, including computation models, configuration for streaming read, and maintaining data quality in a streaming environment.

Note: This course is part of the 'Advanced Data Engineering with Databricks' course series.

Skill Level
Professional
Duration
4h
Prerequisites

The content was developed for participants with these skills/knowledge/abilities:  


    • Ability to perform basic code development tasks using the Databricks Data Engineering and Data Science workspace (create clusters, run code in notebooks, use basic notebook operations, import repos from git, etc.)

    • Intermediate programming experience with PySpark

        - Extract data from a variety of file formats and data sources

        - Apply a number of common transformations to clean data

        - Reshape and manipulate complex data using advanced built-in         functions

    • Intermediate programming experience with Delta Lake (create tables, perform complete and incremental updates, compact files, restore previous versions, etc.)

    • Beginner experience configuring and scheduling data pipelines using the Delta Live Tables (DLT) UI

    • Beginner experience defining Delta Live Tables pipelines using PySpark



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Runtime

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

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Instructors

Instructor-Led

Public and private courses taught by expert instructors across half-day to two-day courses

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Learning

Blended Learning

Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase

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Scale

Skills@Scale

Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

Upcoming Public Classes

Data Engineer

Deploy Workloads with Databricks Workflows

By scheduling tasks with Databricks Jobs, applications can be run automatically to keep tables in the Lakehouse fresh. Using Databricks SQL to schedule updates to queries and dashboards allows quick insights using the newest data. In this course, students will be introduced to task orchestration using the Databricks Workflow Jobs UI. Optionally, they will configure and schedule dashboards and alerts to reflect updates to production data pipelines.

In this course, you’ll learn how to orchestrate data pipelines with Databricks Workflow Jobs and schedule dashboard updates to keep analytics up-to-date. We’ll cover topics like getting started with Databricks Workflows, how to use Databricks SQL for on-demand queries, and how to configure and schedule dashboards and alerts to reflect updates to production data pipelines.

Free
4h
Associate
Machine Learning Practitioner

Machine Learning Operations

This course will guide participants through a comprehensive exploration of machine learning model operations, focusing on MLOps and model lifecycle management. The initial segment covers essential MLOps components and best practices, providing participants with a strong foundation for effectively operationalizing machine learning models. In the latter part of the course, we will delve into the basics of the model lifecycle, demonstrating how to navigate it seamlessly using the Model Registry in conjunction with the Unity Catalog for efficient model management. By the course's conclusion, participants will have gained practical insights and a well-rounded understanding of MLOps principles, equipped with the skills needed to navigate the intricate landscape of machine learning model operations.

Free
4h
Associate
Data Engineer

Databricks Performance Optimization

In this course, you’ll learn how to optimize workloads and physical layout with Spark and Delta Lake and analyze the Spark UI to assess performance and debug applications. We’ll cover topics like streaming, liquid clustering, data skipping, caching, photons, and more.

Note: This course is part of the 'Advanced Data Engineering with Databricks' course series.

Free
4h
Professional
Career Workshop

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March 20

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If you have any questions, please refer to our Frequently Asked Questions page.
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