Your cart is empty.
Keep shopping
Data Analytics for Finance Professionals: Excel, SQL & BI
131 students
Data Analytics for Finance Professionals: Excel, SQL & BI
Master financial reporting, data analysis, dashboards, and business intelligence.
Created byAxial Consulting
Last updated 6/2026
English
English [Auto],
What you'll learn
- Perform advanced financial variance analysis and what-if scenario modeling using Excel Pivot Tables and Waterfall charts.
- Automate financial data cleaning and ETL pipelines using Power Query to eliminate manual reporting tasks.
- Build interactive Power BI dashboards using custom DAX measures to track KPIs and business performance.
- Write SQL queries to extract, filter, and analyze massive corporate financial datasets from databases.
- Leverage Python for finance in Google Colab to forecast revenue trends and export interactive visuals.
- Deliver high-impact executive presentations and data storytelling using the consulting S.C.R. framework.
Explore related topics
Course content
8 sections • 22 lectures • 1h 39m total length
Requirements
- Basic understanding of corporate finance and accounting principles (Revenue, Margins, Net Income).
- Working knowledge of Microsoft Excel (No advanced VBA or complex macros required).
- No prior coding experience required. We provide complete, beginner-friendly introductions and code snippets for SQL, Python, and DAX.
- A free Microsoft Power BI Desktop download (Windows only) and a free Google account to access Google Colab for Python exercises.
- Access and basic knowledge of Canva or any designing tool to create canvas design from scratch.
Description
This course contains the use of artificial intelligence. The course is designed for mid-career finance professionals looking to confidently step into the world of data analytics and elevate their decision-making capabilities. Spanning 1 hour and 40 minutes, it blends foundational concepts with practical, hands-on tools tailored specifically for financial data.
The journey begins with core principles of data-driven decision-making and visual storytelling, helping you understand not just how to analyze data, but how to communicate insights effectively. You will then dive into Excel, where you’ll learn to perform variance analysis using pivot tables, build variance matrices, and create impactful waterfall charts.
Building on this, the course introduces Power BI for cleaning datasets, developing key financial measures, and creating interactive visualizations. You’ll also explore SQL and Python—not as a coding bootcamp, but through a finance-first lens. In SQL, the focus is on data retrieval and aggregation, enabling you to extract meaningful insights from structured datasets. In Python, you’ll work on data cleanup, calculations, and visualization, with an emphasis on understanding the logic behind the code so you can confidently interpret and use AI-generated scripts.
Finally, you’ll refine your storytelling skills by applying brand elements to dashboards and making your visuals shareable across platforms. The course concludes with an executive script-writing exercise, ensuring you can present insights with clarity and impact.
Who this course is for:
- Early and mid-career Financial Analysts and FP&A professionals looking to upgrade their manual reporting workflows with Power BI, SQL, and Python.
- Mid-career Accounting and audit professionals aiming to transition into high-paying Business Intelligence, Advisory, or Data Analytics roles.
- Finance Managers and Directors seeking to implement automated data pipelines and data-driven decision-making in their departments.
- Early and mid-career business professionals who want to master financial data storytelling and bridge the gap between raw data and executive presentations.