Data Analysis with Databricks for Finance

• An understanding of data analysis concepts
• Experience with Python or SQL
• Familiarity with financial data types and reporting

Audience

• Financial analysts and business intelligence professionals
• Data analysts working in the finance sector
• Data engineers supporting financial teams

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.

Introduction to Databricks and Financial Use Cases

• Understanding the Databricks ecosystem
• Overview of financial data analysis workflows
• Use case examples: risk modeling, financial reporting, audit logs

Getting Started with Databricks Notebooks

• Creating and navigating notebooks
• Using Python and SQL in Databricks
• Collaborating with comments and version history

Data Ingestion and Cleaning

• Importing financial data from CSV, databases, and APIs
• Using Spark DataFrames for cleaning and preparation
• Handling missing values and outliers

Transforming and Aggregating Financial Data

• Calculating KPIs and financial ratios
• Filtering, grouping, and pivoting datasets
• Time series manipulation and resampling

Visualizing Financial Insights

• Creating dashboards with Databricks visual tools
• Customizing charts for finance reporting
• Exporting visuals for presentations or regulatory review

Optimizing Queries and Using Delta Lake

• Introduction to Delta Lake architecture
• ACID transactions and data reliability
• Improving performance with data partitioning

Collaboration, Scheduling, and Sharing

• Managing access and permissions for finance teams
• Scheduling jobs for automated reporting
• Exporting data and results securely

Summary and Next Steps