How to Learn Power BI in 30 Days: A Study Plan
A realistic 30-day Power BI plan: what to install and which free sample data to use, a concrete output for every day across four weeks of Power Query, data modelling and DAX, report design, and the Power BI service, mapped to the skill areas Microsoft lists for Power BI data analysts, and how to check progress.
GloryTecks Team
Training & Placement Faculty
Last updated: 25 September 2026
Thirty days is enough to go from opening Power BI for the first time to building, modelling and publishing a sound report, if the days are spent building rather than only watching. This plan assumes one to two hours a day and basic Excel skills. Every day ends with something you made, because the output is what makes a skill stick, and it is what you will show later.
The four weeks follow the areas Microsoft uses to describe a Power BI data analyst's job: preparing data, modelling it, visualising and analysing it, and managing and securing it in the Power BI service (Microsoft Learn: PL-300 study guide). You do not need to take the exam, but its skill list is a reliable map of what "knowing Power BI" means.
Before day 1
- Install Power BI Desktop. It is a free download for Windows (Microsoft: Power BI pricing).
- Get two datasets. Microsoft's Financial Sample workbook, which can also be loaded from Desktop's sample data (Microsoft Learn: Financial Sample), and one dataset from your own work or interests for the final project.
- Create a notes file to record every error you hit and how you fixed it. It becomes your most useful reference.
Week 1: Get and prepare data (days 1 to 7)
| Day | Focus | Output |
|---|---|---|
| 1 | Interface tour; load the Financial Sample | A first page with one table and one chart |
| 2 | Power Query Editor: applied steps, data types | The sample with every column's type checked and corrected |
| 3 | Profiling: column quality, distribution, profile | A list of three data problems you found and fixed |
| 4 | Cleaning: renaming, trimming, replacing, removing rows | A cleaned query with steps named clearly |
| 5 | Combining: merge and append queries | A second table merged in, with row counts checked |
| 6 | Reshaping: unpivot, group by, custom columns | A wide table unpivoted into a tidy one |
| 7 | Review | Rebuild week 1's queries from scratch without notes |
Week 2: Model the data and write first measures (days 8 to 14)
| Day | Focus | Output |
|---|---|---|
| 8 | Facts and dimensions | The sample split into a fact table and two dimensions |
| 9 | Relationships: cardinality and filter direction | A model diagram with one-to-many relationships |
| 10 | Date table | A date table with year, month and month number, marked as the date table |
| 11 | First measures: SUM, COUNTROWS, DIVIDE | Sales, profit and margin measures, checked against Excel |
| 12 | Measures versus calculated columns | One of each, with a note on why each belongs where it is |
| 13 | CALCULATE basics | A share-of-total measure |
| 14 | Review | Explain your model aloud in three minutes, as if to a manager |
Star schema in Power BI and the DAX guide cover the ideas behind days 8 to 12.
Week 3: Deeper DAX and report design (days 15 to 21)
| Day | Focus | Output |
|---|---|---|
| 15 | Time intelligence: year to date, prior year | YTD and year-over-year measures |
| 16 | Variables and readable measures | Two measures rewritten with VAR and RETURN |
| 17 | Choosing visuals; page layout | A one-page report answering three written questions |
| 18 | Slicers, filters and visual interactions | Interactions edited deliberately on every visual |
| 19 | Conditional formatting and KPI cards | A matrix with rule-based colours and a card row |
| 20 | Drillthrough, tooltips and bookmarks | A drillthrough page and a custom tooltip |
| 21 | Review | Ask someone else to use the report and note where they get stuck |
DAX CALCULATE explained supports days 13 to 15.
Week 4: The Power BI service and a project (days 22 to 30)
| Day | Focus | Output |
|---|---|---|
| 22 | Publishing and workspaces | The report published to a workspace |
| 23 | Refresh and gateways | A scheduled refresh configured, or a note on why it needs a gateway |
| 24 | Row-level security | A role that limits a user to one country, checked with "View as" |
| 25 | Sharing: apps, access, endorsement | A short note on how you would share this report at work |
| 26 to 28 | Project on your own dataset | A complete report: cleaned data, star schema, measures, two pages |
| 29 | Performance and polish | Performance Analyzer run, slow visuals improved, titles and labels checked |
| 30 | Review and next steps | A one-page write-up of the project and a list of weak areas |
For the project, building a sales dashboard from scratch shows the full sequence, including checking every measure against independently calculated values.
How to check your progress
Microsoft's study guide lists specific skills under each area, from "create a common date table" to "implement row-level security roles". At the end of each week, go through that week's area and mark each skill as done, shaky or not yet. Shaky items become the next week's warm-up. Microsoft also offers a free practice assessment, which is a useful check on day 30 even if you have no plans to sit the exam.
Habits that make 30 days enough
- Build every day, even for twenty minutes. Watching tutorials without building leaves little behind.
- Check numbers against a source, such as the Excel sheet or a SQL query. Trustworthy numbers matter more than impressive visuals.
- Name things properly from day 1: queries, steps, tables, measures.
- Keep the error log. Most problems repeat.
- Stop polishing early on practice files; save polish for the final project.
After day 30
Thirty days builds a solid working foundation, not mastery. The natural next steps are deeper DAX, larger datasets and performance, and working with real stakeholders. The Power BI roadmap sets out the longer path to job readiness, and PL-300 preparation covers the certification if you want it.
Can I really learn Power BI in 30 days?
Do I need to know Excel first?
What if I miss days?
Do I need a paid licence?
Every topic in this plan, from Power Query and data modelling to DAX, dashboard design and the Power BI service, is covered in the Power BI course.
Sources
- Study guide for Exam PL-300: Microsoft Power BI Data Analyst (Microsoft Learn) — Microsoft Learn
- Power BI pricing (Microsoft) — Microsoft
- Download the Financial Sample Excel workbook for Power BI (Microsoft Learn) — Microsoft Learn
GloryTecks Team
Training & Placement Faculty
The GloryTecks faculty team mentors learners across Data Science, AI and Data Engineering, with a focus on real-time projects and placement readiness in Hyderabad.
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