Drive Team Excellence with Databricks Corporate Training

Empower your teams with expert-led on-site/in-house or virtual/online Databricks Training through Edstellar, a premier Databricks training company for organizations globally. Our customized training program equips your employees with the skills, knowledge, and cutting-edge tools needed for success. Designed to meet your specific training needs, this Databricks group training program ensures your team is primed to drive your business goals. Transform your workforce into a beacon of productivity and efficiency.

Databricks provides an interactive and collaborative environment for data engineers, data scientists, and analysts to work together on big data projects. This virtual and onsite Databricks training combines data engineering, data science, and business analytics into a single unified workflow, enabling employees to derive valuable insights from the data efficiently.

Edstellar’s Databricks instructor-led training course focuses on enhancing data-related skills within organizations. The training course is designed to cater to professionals at all levels of expertise, from beginners to experienced data analysts and scientists.

Key Skills Employees Gain from Databricks Training

Databricks skills corporate training will enable teams to effectively apply their learnings at work.

  • Machine Learning Modeling
  • Data Validation
  • Data Manipulation
  • Data Integration
  • Advanced Analytics
  • Data Governance

Key Learning Outcomes of Databricks Training Workshop

Edstellar’s Databricks group training will not only help your teams to acquire fundamental skills but also attain invaluable learning outcomes, enhancing their proficiency and enabling application of knowledge in a professional environment. By completing our Databricks workshop, teams will to master essential Databricks and also focus on introducing key concepts and principles related to Databricks at work.


Employees who complete Databricks training will be able to:

  • Create and implement machine learning models using Databricks' ML libraries to solve business problems and predict future outcomes
  • Evaluate the quality and reliability of data by applying data validation and cleansing techniques, ensuring accurate and trustworthy data analysis results
  • Apply data manipulation techniques using Databricks' DataFrame API and SQL queries to cleanse, transform, and manipulate large datasets effectively
  • Integrate data from various sources and formats into Databricks, allowing employees to work with diverse data sets and leverage the full potential of the platform
  • Analyze complex data sets using advanced analytics tools and techniques in Databricks, enabling them to extract meaningful insights and make data-driven decisions
  • Understand the fundamentals of data governance and compliance, including data privacy regulations and best practices for ensuring data security and compliance within an organization
  • Assess and visualize data using Databricks Data Validation Tool (DVT), enabling employees to create insightful charts, graphs, and dashboards to communicate findings and insights to stakeholders

Key Benefits of the Databricks Group Training

Attending our Databricks classes tailored for corporations offers numerous advantages. Through our Databricks group training classes, participants will gain confidence and comprehensive insights, enhance their skills, and gain a deeper understanding of Databricks.

  • Provides a deep understanding of data concepts, tools, and techniques
  • Enables organizations to evaluate the effectiveness of their data strategies and initiatives
  • Enables employees to apply advanced data analysis techniques and tools in real-world scenarios
  • Trains employees to refine the organization's data practices and improve overall business performance
  • Fosters a culture of creativity and innovation by empowering employees to create data-driven solutions
  • Encourages professionals to synthesize their knowledge and skills to solve complex data-related challenges
  • Enables employees to manipulate and transform data, build machine learning models, and visualize insights
  • Leverage the newfound skills of employees to analyze complex business problems, make data-driven decisions, and drive innovation within the organization
  • Enables the professionals to integrate data from various sources, clean and prepare data for analysis, and synthesize insights to generate actionable recommendations
  • Develops a solid foundation in data manipulation, data governance, statistical analysis, and visualization, allowing them to understand the underlying principles and best practices in data management and analysis.

Topics and Outline of Databricks Training

Our virtual and on-premise Databricks training curriculum is divided into multiple modules designed by industry experts. This Databricks training for organizations provides an interactive learning experience focused on the dynamic demands of the field, making it relevant and practical.

1. What is Apache Spark?

2. Defining big data

3. Spark languages

  • Scala
  • Python
  • R
  • Java
  • SQL

4. Introduction to Databricks community edition

5. Databricks architecture

6. Understanding data analytics

7. Understanding machine learning

8. Azure implementation of Databricks

9. AWS implementation of Databricks

  1. Creating a Databricks workspace on Azure
    • Account setup
    • Workspace creation and configuration
  2. Creating and configuring your Databricks cluster
    • Cluster types and specifications
    • Instance sizing and scaling options
    • Cluster configuration settings
  3. Creating and attaching your first notebook in Databricks
    • Notebook creation and organization
    • Notebook settings and configurations
  4. Testing and running your Notebook in Databricks
    • Executing code cells
    • Debugging and troubleshooting
    • Monitoring and logging
  1. Creating a table in Databricks
    • Table creation options
    • Schema definition and data types
  2. Connecting to a Spark data source
    • Importing data from various sources (e.g., CSV, JSON, databases)
    • Configuring connection settings
  3. Previewing data in your Table
    • Sampling data
    • Exploring data structure and content
  4. Basics of columns and datatypes in Databricks
    • Working with columns and column operations
    • Understanding data types and conversions
  1. Writing SQL queries to import data into Databricks notebook
    • SELECT, INSERT, and other SQL operations
    • Filtering and sorting data
  2. Viewing aggregates in Databricks
    • Aggregation functions (e.g., COUNT, SUM, AVG)
    • Grouping and aggregating data
  3. Performing joins in Databricks
    • Different types of joins (e.g., inner, outer, left, right)
    • Joining multiple tables
    • Handling join conditions and duplicates
  1. Understanding data types in Databricks
    • Numeric, string, boolean, and complex data types
    • Type conversions and casting
  2. Working with DataFrames in Databricks
    • DataFrame creation and manipulation
    • Filtering, transforming, and aggregating data
  3. Handling Images in Databricks
    • Image data formats and processing
    • Image manipulation and analysis
  4. Exploring structured streaming DataFrames in Databricks
    • Real-time data processing and analysis
    • Windowing and time-based operations
  5. Creating plots in Databricks
    • Data visualization libraries and tools in Databricks
    • Plotting charts, graphs, and histograms
  6. Choosing chart types and using the chart toolbar
    • Customizing chart appearance and styling
    • Selecting appropriate chart types for different data scenarios
  7. Layout and styling considerations for visualizations
    • Arranging multiple charts and visuals
    • Adding titles, labels, and annotations
  8. Visualizations for machine learning in Databricks
    • Visualizing model outputs and predictions
    • Interpreting model performance metrics
  1. Creating a Job in Databricks
    • Job configuration settings
    • Defining job tasks and workflows
  2. Viewing Jobs and Job details in Databricks
    • Monitoring job status and progress
    • Accessing job logs and history
  3. Running your first Job in Databricks
    • Executing job tasks
    • Handling job dependencies and inputs
  4. Scheduling Jobs in Databricks
    • Setting up recurring and automated job runs
    • Configuring scheduling options
  5. Setting parameters for Jobs in Databricks
    • Parameterizing job tasks and inputs
    • Passing parameters at runtime
  6. Viewing completed jobs in Databricks
    • Analyzing job results and outputs
    • Reviewing job performance metrics
  7. Managing dependencies in Databricks
    • Handling interdependent tasks and workflows
    • Managing job dependencies and execution order
  8. Setting up alerts for Databricks jobs
    • Configuring email notifications and alerts
    • Monitoring job failures and critical events
  1. Getting data into Delta Lake in Databricks
    • Creating Delta tables
    • Importing data into Delta format
  2. Performing delete, update, and merge operations in Delta tables
    • Modifying data in Delta Tables
    • Handling updates and deletes efficiently
  3. Working with constraints in Delta Tables
    • Defining constraints (e.g., uniqueness, referential integrity)
    • Enforcing data integrity in Delta Tables
  4. Versioning in Delta Tables
    • Tracking and managing table versions
    • Rollbacks and time travel capabilities
  5. Concurrency considerations in Delta Tables
    • Handling concurrent read and write operations
    • Managing conflicts and consistency
  6. Integrations with other systems in Databricks
    • Integrating Delta tables with other data systems
    • Data sharing and interoperability
  7. Overview of Delta engine in Databricks
    • Accelerating query performance with Delta engine
    • Benefits and use cases of Delta engine
  1. Collaboration features in Databricks
    • Notebooks collaboration
    • Workspace sharing and permissions
    • Version control and Git integration
  2. Scaling capabilities of Databricks
    • Auto-scaling clusters
    • High-performance distributed computing
  3. Integrating Databricks into data pipelines
    • Data ingestion and ETL processes
    • Integration with data storage systems
    • Streamlining data workflows

Target Audience for Databricks Training Course

The Databricks training program can also be taken by professionals at various levels in the organization.

  • Data Engineers
  • Data Scientists
  • Data Analysts
  • Big Data Engineers
  • Machine Learning Engineers
  • Data Architects
  • Software Engineers
  • AI Engineers
  • ETL Developers
  • Data Integration Specialists
  • DevOps Engineers
  • Data Managers

Prerequisites for Databricks Training

The professionals attending the Databricks training course need to have a basic understanding of big data concepts and with relevant tools and technologies. Experience in working with databases and SQL.

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Corporate Group Training Delivery Modes
for Databricks Training

At Edstellar, we understand the importance of impactful and engaging training for employees. To ensure the training is more interactive, we offer Face-to-Face onsite/in-house or virtual/online for companies. This approach has proven to be effective, outcome-oriented, and produces a well-rounded training experience for your teams.

 Virtual trainig

Our virtual group training sessions bring expert-led, high-quality training to your teams anywhere, ensuring consistency and seamless integration into their schedules.

With global reach, your employees can get trained from various locations
The consistent training quality ensures uniform learning outcomes
Participants can attend training in their own space without the need for traveling
Organizations can scale learning by accommodating large groups of participants
Interactive tools can be used to enhance learning engagement
 On-site trainig

Edstellar's onsite group training delivers immersive and insightful learning experiences right in the comfort of your office.

Higher engagement and better learning experience through face-to-face interaction
Workplace environment can be tailored to learning requirements
Team collaboration and knowledge sharing improves training effectiveness
Demonstration of processes for hands-on learning and better understanding
Participants can get their doubts clarified and gain valuable insights through direct interaction
 Off-site trainig

Edstellar's off-site group training programs offer a unique opportunity for teams to immerse themselves in focused and dynamic learning environments away from their usual workplace distractions.

Distraction-free environment improves learning engagement
Team bonding can be improved through activities
Dedicated schedule for training away from office set up can improve learning effectiveness
Boosts employee morale and reflects organization's commitment to employee development

Explore Our Customized Pricing Package
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Databricks Corporate Training

Elevate your team's performance with our customized Databricks training. Find transparent pricing options to match your training needs. Start maximizing your team's potential now.

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        Edstellar: Your Go-to Databricks Training Company

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        Get Your Team Members Recognized with Edstellar’s Course Certificate

        Upon successful completion of the Databricks training course offered by Edstellar, employees receive a course completion certificate, symbolizing their dedication to ongoing learning and professional development.

        This certificate validates the employee's acquired skills and is a powerful motivator, inspiring them to enhance their expertise further and contribute effectively to organizational success.

        Course Completion Certificate

        We have Expert Trainers to Meet Your Databricks Training Needs

        The instructor-led training is conducted by certified trainers with extensive expertise in the field. Participants will benefit from the instructor's vast knowledge, gaining valuable insights and practical skills essential for success in Access practices.

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