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Duration 14 hours
Course Outline
Introduction to Databricks and Applications in Finance
- Exploring the Databricks ecosystem
- Overview of standard financial data analysis workflows
- Practical use cases: risk modeling, financial reporting, and audit logging
Getting Started with Databricks Notebooks
- Creating and navigating notebook interfaces
- Utilizing Python and SQL within Databricks
- Enhancing collaboration through comments and version history
Data Ingestion and Cleansing
- Importing financial data from CSVs, databases, and APIs
- Leveraging Spark DataFrames for data cleaning and preparation
- Managing missing values and statistical outliers
Transforming and Aggregating Financial Data
- Computing KPIs and key financial ratios
- Filtering, grouping, and pivoting datasets for analysis
- Manipulating and resampling time-series data
Visualizing Financial Insights
- Building dashboards using Databricks' visual tools
- Tailoring charts specifically for financial reporting needs
- Exporting visuals for executive presentations or regulatory compliance
Optimizing Queries and Leveraging Delta Lake
- Fundamentals of Delta Lake architecture
- Ensuring data reliability through ACID transactions
- Enhancing performance via data partitioning strategies
Collaboration, Scheduling, and Data Sharing
- Managing access controls and permissions for finance teams
- Automating reporting through job scheduling
- Securely exporting data and analytical results
Summary and Recommended Next Steps
Requirements
- A solid grasp of core data analysis principles
- Proficiency in either Python or SQL
- Working knowledge of financial data structures and reporting standards
Target Audience
- Financial analysts and business intelligence specialists
- Data analysts focused on the finance industry
- Data engineers supporting financial operations teams
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
