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Mixed · Self-paced2026 Edition

Power BI for Analysts

Power BI end-to-end: Power Query for ETL, the data model with star schemas, DAX from CALCULATE through time intelligence, and Power BI Service for governance. Built for the analyst at a Microsoft shop who'll be the in-team Power BI authority within six months.

12

Modules

~10h 10m

Reading time

Mixed

Level

Self-paced

Format

§

Syllabus

  1. 01

    Orientation — Desktop, Service, Pro vs Premium

    What lives where: Desktop is the IDE, Service is the cloud, Premium is the capacity tier. Licensing landmines (Pro, PPU, Premium per capacity) you'll be asked to advise on.

    ~35 minModule 01
    →
  2. 02

    Power Query — connect, clean, shape

    Connectors, transformations, the M language underneath. Why ETL belongs in Power Query, not in DAX or the data source.

    ~55 minModule 02
    →
  3. 03

    The data model — star schema and relationships

    Fact and dimension tables, one-to-many vs many-to-many, bi-directional filtering and its dangers. Why analysts who skip modelling fight DAX forever.

    ~55 minModule 03
    →
  4. 04

    DAX fundamentals — measures vs calculated columns

    Row context vs filter context — the single concept that makes DAX click. SUM vs SUMX. Why calculated columns are usually the wrong answer.

    ~55 minModule 04
    →
  5. 05

    CALCULATE — the most important DAX function

    Modifying filter context. CALCULATE + ALL, CALCULATE + FILTER, KEEPFILTERS. The four most common DAX patterns built from this one function.

    ~60 minModule 05
    →
  6. 06

    Time intelligence — YoY, YTD, rolling averages

    DATEADD, SAMEPERIODLASTYEAR, TOTALYTD, DATESBETWEEN. Why a proper Date dimension is non-negotiable and how to build one.

    ~50 minModule 06
    →
  7. 07

    Advanced DAX — variables, iterators, context transition

    VAR for clarity and performance. SUMX, AVERAGEX, RANKX. Context transition — when row context becomes filter context — and the bugs that hide there.

    ~60 minModule 07
    →
  8. 08

    Visuals — built-in, custom, and the conditional-format trick

    Which built-in visual for which claim. AppSource custom visuals worth using. Conditional formatting as the analyst's most under-used feature.

    ~45 minModule 08
    →
  9. 09

    Row-level security and dynamic permissions

    Static vs dynamic RLS, USERNAME and USERPRINCIPALNAME, the security-by-role table pattern. Mandatory before any finance dashboard ships.

    ~50 minModule 09
    →
  10. 10

    Performance — model size, query folding, aggregations

    DAX Studio, the storage engine vs the formula engine, query folding in Power Query, aggregations for large fact tables. The seven causes of slow Power BI.

    ~55 minModule 10
    →
  11. 11

    Power BI Service — workspaces, apps, deployment pipelines

    Dev → test → prod via deployment pipelines, scheduled refresh, gateways for on-prem data sources, Power BI apps as the consumer surface.

    ~45 minModule 11
    →
  12. 12

    Governance — endorsement, sensitivity, audit, COE

    Certified vs promoted datasets, sensitivity labels, audit logs, the Centre of Excellence pattern. What separates a few power-users from an enterprise capability.

    ~45 minModule 12
    →

How to use this course

Start with module 01 if the material is new; skip ahead if you have prior exposure. Each module is self-contained but the arc is sequential — the projects in the final module assume the toolkit from modules 1-11. Every module ends with key takeaways and a curated further-reading list with primary sources.