SQL for Finance professionals
Course Description
This focused course equips finance professionals with practical SQL skills for data analysis and reporting. Participants will learn SQL fundamentals, connect Excel to cloud databases, write tailored financial queries, and use Excel's data modelling and visualization tools. With hands-on exercises, this course enhances financial data retrieval, aggregation, and visualization, making data-driven decision-making more efficient. The course structure ensures that finance professionals gain practical SQL skills applicable to their daily tasks, enhancing their data analysis and reporting capabilities.
Duration: 1 days
Prerequisites
Intermediate knowledge of Excel. No prior experience with SQL is required.
Learning Objectives
By the end of this course, participants will be able to: Understand the role of SQL in financial data analysis and decision-making. Learn how to connect Excel to cloud-based databases for efficient data retrieval. Master basic SQL queries to extract, filter, and manipulate financial data. Apply GROUP BY and HAVING clauses to aggregate financial information. Use JOIN operations to combine financial data from multiple tables. Understand primary and foreign keys in financial datasets for data integrity. Develop skills to create dynamic financial models using SQL and Excel PowerPivot. Learn to refresh and update data models with live database connections. Utilise visualisation tools in Excel to represent financial data insights. Gain hands-on experience with real-world data queries and reporting.
Introduction to SQL in Finance
Role of data in financial organisations. Overview of SQL and its importance in finance. Types of data formats and storage solutions in financial contexts.
Connecting Excel to Cloud-Based Databases
Introduction to cloud databases and their benefits. Using Excel Power Query to establish connections with cloud databases. Practical exercise: Connecting Excel to a sample cloud-based financial database.
Fundamentals of SQL Queries
Basic SQL syntax and structure. SELECT statements: Retrieving specific financial data. WHERE clause: Filtering financial records based on conditions. Practical exercise: Writing basic queries to extract financial data.
Advanced SQL Techniques for Finance
GROUP BY and HAVING clauses: Aggregating financial data. JOIN operations: Combining data from multiple financial tables. Understanding primary and foreign keys in financial datasets. Practical exercise: Performing complex queries on financial data.
Data Modelling and Analysis in Excel
Introduction to Excel PowerPivot for data analysis. Creating data models from SQL query results. Refreshing data models with updated cloud data. Practical exercise: Building and updating a financial data model in Excel.
Visualising Financial Data
Utilising Excel's data visualisation tools to represent financial information. Creating charts and graphs to interpret financial data insights. Practical exercise: Designing visual representations of financial datasets.
Schedule
| Name | Date | Location | |
|---|---|---|---|
| SQL for Finance professionals | 2025-05-27 | Online |
SQL SQL Scripting Structured Query Language SQL Server Azure Excel SQL for finance professionals