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How to Read This Book

Namaskar, friends! I am Ravindra Bagale. This book is my class, just on paper. I have written it the way I speak in class: technical things in English, and here and there, in the tip boxes, our Marathi (and a little Hindi), so that while reading you feel "Sir is sitting right in front of me".

How this book is organised (English main body):

  • Technical content is in English. Menu names, click paths (for example Home › Transform data), DAX, M code and SQL appear exactly as in Power BI. You will use these words in jobs and interviews.
  • Devanagari in brackets only for hard abstract words the first time they appear — for example cardinality (how many rows on each side of a relationship match), hierarchy, outlier. Everyday words stay English only: filter, slicer, table, column, report, dashboard, measure.
  • Marathi / Hindi voice sits mainly in Ravindra Bagale's Tip boxes and short classroom lines — not in long main-body paragraphs.
  • Every substantial lesson aims at the depth pattern in LESSON_DEPTH_STANDARD.md: problem, then explain, then data, then demonstrate, then result, then what happened, then explore, then mistakes, then practise, then think like a professional.
  • Roadmap (Beginner, then Professional):
    • Beginner: ch01–ch08 overview, ch11–ch12 model, ch13.1–13.7 base measures, ch14 visuals. Checkpoint: small CSV + Total Sales + City slicer.
    • Intermediate: ch06.10 folding, ch08.12 column vs measure, ch13.3 and 13.8 CALCULATE, ch21–ch23 design, ch27–ch28 project. Checkpoint: % under 10 minutes + View as for one city.
    • Advanced: context transition, ALL/KEEPFILTERS, iterators, performance (ch13 later sections, ch29).
    • Professional: measure tables, RLS + 7:00 IST refresh, portfolio story that names a decision.
    • Author detail tables: sources/powerbi/LEVELS.md and LESSON_DEPTH_STANDARD.md (not separate site pages).
  • Start and end of each module. A short opener, and a quick recap box at the end. Before an exam, recap boxes alone are useful revision.
  • Interview answers in Modules 30 and 31 are clean professional English on purpose.
  • Glossary (Module 33) lists terms with a Marathi meaning column where useful.

Fictional data

All Blinkit and Amazon Now figures in this book, and industry-style figures in Module 36, are fictional sample data for learning. They are not real company, hospital, bank or government statistics.

Learning path

Beginner checkpoint: load a small CSV, one relationship, Total Sales + City slicer. Intermediate: CALCULATE + one multi-page report. Advanced: explain filter context on a whiteboard. Details: LEVELS.md.

Chala tar mag, suru karuya! Ghabru naka – one module at a time, a little practice every day, and Power BI will come.