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Course Outline
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
Requirements
- 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
14 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
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Testimonials (1)
All the topics covered, although many were very quick, give us an idea of what we will need to delve into further. Additionally, I liked that we got to do some hands-on practice, although I still believe the course deserves more.
Sandra Mariela Lopez Bernal - Kueski
Course - Databricks
Machine Translated
