Excel + Power Query & Power BI (Advanced)

What you'll learn

Transform data once in Power Query and never do it by hand again
Combine several sources into one table that updates on refresh
Model finance data properly — star schema, and a date table time intelligence will work against
Write DAX including YTD, prior period and variance without helper columns
Publish a Power BI dashboard on scheduled refresh, validated against the reconciled books

Week by week

Every week, what you can do by the end of it.

1Power Query foundations (Get & Transform)5h
The Query Editor; import from CSV/Excel/web; clean, split, merge, retype
ChatGPT to write/fix an M step
2Power Query pipelines (multi-source & refreshable)5h
Merge (joins) & append; combine months/branches; import a whole folder
AI for join logic & folder-import M
3Data modelling & Power Pivot5h
The data model; fact vs dimension tables; a finance star schema
AI to design a star schema from your tables

What you'll build

You leave with work you can show, not only a certificate.

A refreshable Power Query pipeline (multi-source import + clean) — Wk 1–2
A finance data model with relationships & measures — Wk 3–5
An interactive Power BI dashboard (published, scheduled refresh) — Wk 6–7
Capstone: end-to-end automated management-reporting solution — Wk 8

Tools you'll use

Power Query (M)
Power Pivot & Data Model
DAX
Power BI Desktop

Afterwards

Graduate can automate finance data pipelines, model financial data, write finance DAX, and build & publish interactive dashboards — eliminating manual monthly reporting. Roles: Financial Analyst · FP&A Analyst · BI/Data Analyst (Finance) · Management Accountant · Finance Automation specialist. Directly strengthens Ascent Finance reporting capability, and pairs with the Data Analytics track