Databricks Training in Radom

Databricks is a unified Lakehouse platform that combines Spark, Delta Lake, and governance (Unity Catalog) to support scalable data engineering and analytics workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level technology managers with a data engineering background who wish to migrate complex procedural OLAP logic to a Lakehouse architecture using Databricks, Spark, Delta Lake, Unity Catalog, and native workflows.

Upon completion of this training, participants will be able to:

• Explain Lakehouse architecture and the Bronze→Silver→Gold (Medallion) pattern.
• Translate stored-procedure logic into Spark DataFrame and notebook implementations.
• Design and implement incremental ingestion, merge, and optimization routines using Delta Lake.
• Build end-to-end orchestrated pipelines with Databricks Workflows, version control, testing, and governance.

Format of the Course

• Intensive, instructor-led sessions with focused demonstrations and explanations.
• Daily hands-on labs using representative datasets and migration exercises.
• Guided code reviews, performance tuning clinics, and workflow orchestration practice.

Course Customization Options

• This course can be tailored to your environment, datasets, and governance requirements; please contact us to arrange customization.

Databricks Lakehouse is a unified data and AI platform that combines data engineering, data science, and analytics on a single, scalable foundation.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level data engineers and analytics practitioners who wish to gain end-to-end, production-ready skills in data engineering using Databricks, Apache Spark, orchestration, and downstream visualization.

By the end of this training, participants will be able to:

• Design and implement scalable ETL/ELT pipelines on the Databricks Lakehouse platform.
• Use Spark and advanced SQL effectively for large-scale data processing and optimization.
• Build, train, and deploy models using Big Data ML patterns and Databricks tooling.
• Implement data modeling and ingestion patterns aligned with analytics and reporting needs.
• Automate workflows with Airflow/Astronomer and operationalize with Git-based CI/CD.
• Create production-grade dashboards and visualizations using Tableau connected to Databricks.
• Deliver a customized capstone project demonstrating an end-to-end Lakehouse solution.

Format of the Course

• Theoretical lectures with focused daily topics and reading.
• Extensive hands-on labs in Databricks and cloud environments.
• Weekly practical assessments and certification badge preparation.
• Guided project work with instructor mentorship and peer reviews.
• Final customized capstone project and presentation.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Azure Databricks is a cloud-based collaborative platform that supports big data analytics and machine learning using Apache Spark and the Microsoft Azure ecosystem.

This instructor-led, live training (online or onsite) is aimed at intermediate-level data professionals who wish to design, build, and deploy machine learning models using Azure Databricks for financial use cases.

By the end of this training, participants will be able to:

• Build and train machine learning models using financial data in Azure Databricks.
• Use MLflow to track experiments, manage models, and deploy solutions.
• Apply models to detect anomalies, assess risks, or forecast trends in finance.
• Integrate ML models into scalable pipelines for continuous evaluation.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Databricks is a unified analytics platform designed for big data and machine learning in collaborative environments.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level data analysts and financial professionals who wish to perform large-scale data analysis using Databricks in finance-related use cases.

By the end of this training, participants will be able to:

• Use Databricks notebooks to query and analyze financial datasets.
• Clean and transform raw financial data for reporting and insights.
• Create dashboards and visualizations for performance tracking.
• Collaborate with team members in real time on shared notebooks.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Radom (online or onsite) is aimed at data scientists and developers who wish to set up, deploy, and manage data analytics solutions using Databricks.

By the end of this training, participants will be able to:

• Set up and configure Databricks.
• Understand how Databricks and Apache Spark work together.
• Learn how to load and transform data in Databricks.