Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to Databricks and Financial Applications
- Exploring the Databricks ecosystem
- Reviewing financial data analysis workflows
- Case studies: risk modeling, financial reporting, and audit logs
Beginner's Guide to Databricks Notebooks
- Creating and navigating through notebooks
- Utilizing Python and SQL within Databricks
- Collaborating via comments and version history
Data Ingestion and Cleansing
- Importing financial data from CSV files, databases, and APIs
- Employing Spark DataFrames for data cleaning and preparation
- Addressing missing values and outliers
Transformation and Aggregation of Financial Data
- Computing KPIs and financial ratios
- Filtering, grouping, and pivoting datasets
- Manipulating and resampling time series data
Visualizing Financial Insights
- Building dashboards using Databricks visual tools
- Tailoring charts for financial reporting
- Exporting visuals for presentations or regulatory compliance
Query Optimization and Delta Lake Utilization
- Overview of Delta Lake architecture
- Ensuring data reliability through ACID transactions
- Enhancing performance via data partitioning
Collaboration, Scheduling, and Distribution
- Managing access controls and permissions for finance teams
- Scheduling jobs for automated reporting
- Securely exporting data and results
Summary and Future Directions
Requirements
- A solid grasp of fundamental data analysis concepts
- Proficiency in Python or SQL
- Knowledge of various financial data types and reporting standards
Target Audience
- Financial analysts and business intelligence specialists
- Data analysts focused on the finance sector
- Data engineers providing support to financial teams
