Databricks Training in Nepal

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

This instructor-led, live training session (available online or onsite) is designed for 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.

Upon completing this training, participants will gain the ability to:

• Articulate the principles of Lakehouse architecture and the Bronze→Silver→Gold (Medallion) layered design pattern.
• Convert stored-procedure logic into implementations using Spark DataFrames and notebooks.
• Design and deploy incremental ingestion, merge operations, and optimization routines using Delta Lake.
• Construct end-to-end orchestrated pipelines utilizing Databricks Workflows, version control, testing frameworks, and governance standards.

Course Delivery Format

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

Customization Options

• This course can be customized to align with your specific environment, datasets, and governance requirements; please contact us to arrange for tailored 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 (available online or onsite) is tailored for beginner to intermediate data analysts and finance professionals seeking to perform large-scale data analysis using Databricks in financial contexts.

Upon completing this training, participants will be able to:

• Leverage 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.

Course Format

• Interactive lectures and discussions.
• Ample exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Customization Options

• To request customized training for this course, please contact us to make arrangements.

This instructor-led live training in Nepal (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.