Turn raw spreadsheets into decisions people trust
A foundations-first data analytics path — start in Excel with the spreadsheet skills every analyst leans on daily, move into SQL to query relational data directly, then build interactive dashboards in Power BI you can publish and share. All 12 weeks are live, ending in a full end-to-end capstone that ties all three tools together.
Prerequisites & tooling
What you should already know
- Comfortable using a computer and opening files in a spreadsheet app
- No prior programming, database or BI tool experience required
- A Windows or Mac machine with Microsoft Excel (or Google Sheets) installed
- Curiosity about turning numbers into a story — not a math degree
Stack you'll work with
The exact three tools most business, product and finance analyst roles list as requirements.
The full 12-week roadmap
Twelve modules, from Excel fundamentals and SQL querying through joins, aggregation and window functions, to Power BI data modeling, DAX and published dashboards — capped by an end-to-end capstone. Every week below is live.
Excel Fundamentals: Formulas, Functions & Clean Data
The spreadsheet habits every later week — and every analyst job — assumes you already have.
- Cells, ranges & absolute vs. relative references
- Core formulas:
SUM,AVERAGEIFS,COUNTIFS& nestedIF - Cleaning messy data with text/date functions & data validation
SQL Fundamentals: Querying Relational Data
Stop asking someone else to pull the data — write the query yourself.
- Tables, rows & columns: what a relational database actually is
SELECT,WHERE, sorting & removing duplicates- Aggregate functions, a first
GROUP BY& handlingNULL
Excel Lookups, PivotTables & Your First Dashboard
Turn a flat table into a summary someone can actually act on.
VLOOKUP,XLOOKUP&INDEX/MATCH- PivotTables & PivotCharts for fast, reshapeable summaries
- Slicers, conditional formatting & a one-page KPI dashboard
Power Query & Power Pivot: Modeling Data at Scale
Move past copy-paste and let Excel clean and combine data for you, repeatably.
- Importing, shaping & merging data with Power Query
- Building a data model across multiple tables with Power Pivot
- Refreshable reports that survive a new week of raw data
SQL Joins & Relational Data
Real questions live across more than one table — this is how you combine them.
- Primary & foreign keys, and why relationships exist at all
INNER,LEFT,RIGHT&FULLjoins, with real query examples- Spotting a fan-out and avoiding accidental row duplication
Aggregation, Grouping & Summarizing Data in SQL
Turn thousands of rows into the one number a stakeholder actually asked for.
GROUP BYwith multiple columns & filtering groups withHAVINGCASE WHENfor conditional aggregation- Writing a query someone else on the team can actually read
Subqueries, CTEs & Window Functions
The SQL that separates "I can pull data" from "I can actually analyze it."
- Subqueries & readable
WITH(CTE) queries ROW_NUMBER,RANK& running totals withOVER()- Month-over-month comparisons with
LAG/LEAD
SQL for Analysts: Views, Optimization & Real Datasets
Take a query from "it eventually finishes" to something a dashboard can call every day.
- Views for reusable, shareable queries
- Reading a query plan & the basics of indexing
- A guided analysis project against a real multi-table dataset
Power BI Fundamentals: Importing & Modeling Data
Bring Excel and SQL data into one tool built for interactive reporting.
- Connecting Power BI Desktop to Excel, SQL & CSV sources
- Power Query in Power BI & building a star-schema data model
- Relationships, cardinality & why a data model matters before charts
DAX: Calculated Columns, Measures & Time Intelligence
The formula language that makes a Power BI report actually answer questions.
- Calculated columns vs. measures — and when to use each
CALCULATE, filter context & the DAX mental model- Year-to-date, month-over-month & other time-intelligence measures
Building & Publishing Interactive Power BI Dashboards
Ship a report that updates itself and that other people can actually open.
- Choosing the right visual & designing a dashboard that reads at a glance
- Slicers, drill-through & cross-filtering between visuals
- Publishing to Power BI Service, scheduled refresh & row-level security
Capstone: End-to-End Analytics Project — Excel → SQL → Power BI
Apply every module in one project — clean, query and visualize a real dataset.
- Clean & shape a raw dataset in Excel with Power Query
- Query it in SQL to answer a set of real business questions
- Publish a portfolio-ready Power BI dashboard you can show employers