Databricks Training in Varna

Databricks offers a unified Lakehouse platform that integrates Spark, Delta Lake, and governance capabilities (Unity Catalog) to facilitate scalable data engineering and analytics workflows.

This instructor-led, live training (available online or on-site) targets intermediate-level technology managers with a data engineering background who aim to migrate complex procedural OLAP logic to a Lakehouse architecture utilizing Databricks, Spark, Delta Lake, Unity Catalog, and native workflows.

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

• Describe Lakehouse architecture and the Bronze→Silver→Gold (Medallion) pattern.
• Convert 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.

Course Format

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

Customization Options

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

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 Varna (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.