Databricks Training

Live Online & Classroom Enterprise Training

Databricks is a cloud-based data platform for big data processing, analytics, and machine learning. It provides a unified environment built on Apache Spark for collaborative data engineering and AI workflows.

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What is Databricks Training about?

The Databricks course provides a comprehensive understanding of the Databricks Lakehouse Platform and its capabilities for data engineering, analytics, and machine learning. Participants will explore how Databricks unifies data warehouses and AI workloads, simplifies collaboration using notebooks, and integrates seamlessly with Azure, AWS, and Google Cloud. Through hands-on labs and use cases, learners will acquire practical experience in building data pipelines, performing analytics with SQL, and deploying ML models at scale.

What are the objectives of Databricks Training ?

Understand the core architecture and components of the Databricks Lakehouse Platform.
Build and manage scalable data pipelines using Databricks.
Perform data analytics and visualization using Databricks SQL and notebooks.
Implement and deploy machine learning workflows using MLflow.
Collaborate effectively using Databricks Workspaces and Repos.

Who is Databricks Training for?

Business Intelligence (BI) Developers and Analysts.
Data Engineers and Data Scientists.
Data Analysts and BI Professionals.
Machine Learning Engineers.
Cloud Architects and Developers.
Professionals interested in modern data platform technologies.

What are the prerequisites for Databricks Training?

Prerequisites:

Basic understanding of data analytics and cloud computing.
Familiarity with Python, SQL, or Scala (recommended).
Awareness of big data concepts (Spark, Hadoop).
Knowledge of data processing and ETL fundamentals
Experience with any cloud platform (Azure, AWS, or GCP).

Learning Path:

Introduction to Databricks and the Lakehouse Platform
Data Engineering with Databricks
Performing Analytics using Databricks SQL
Machine Learning and AI with Databricks MLflow
Managing, Securing, and Monitoring Databricks Workspaces

Related Courses:

Azure Databricks Fundamentals
Apache Spark for Data Engineers
Data Engineering on Microsoft Azure (DP-203)
Machine Learning with Databricks

Available Training Modes

Live Online Training

1 Days

Course Outline Expand All

Expand All

Module 1: Introduction to Databricks

Overview of Databricks and its Ecosystem

Understanding the Lakehouse Architecture

Key Components: Workspace, Clusters, and Notebooks

Databricks User Interface and Navigation

Working with Data in Databricks

Collaboration and Version Control in Databricks

Module 2: Data Intelligence Platform Fundamentals

Overview of the Databricks Data Intelligence Platform

Data Management and Governance in Databricks

Unity Catalog: Data Lineage, Access Control, and Compliance

Delta Lake Fundamentals and Data Versioning

Integrating Databricks with Cloud Data Sources (AWS, Azure, GCP)

Performance Optimization and Cost Management

Module 3: Introduction to SQL in Databricks

Basics of SQL in the Databricks Environment

Creating and Managing Tables and Views

Writing Queries with Databricks SQL

Using Joins, Aggregations, and Window Functions

Query Optimization and Caching Techniques

Visualizing Query Results with Databricks SQL Dashboards

Who is the instructor for this training?

The trainer for this Databricks Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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