Thinking With Data. A Complete Beginner's Course in Data Analytics Thinking With Data. A Complete Beginner's Course in Data Analytics
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Sprache:Englisch
7,49 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
ePUB
Kopierschutz
Ja
Family Sharing
Ja
Text-to-Speech
Ja
Erscheinungsdatum
24.09.2026
Verlag
Juan Pablo Muñoz NietoSeitenzahl
(Printausgabe)
Dateigröße
159 KB
Sprache
Englisch
EAN
9798237350357
From zero to your first analytics role no mathematics degree, no coding background required.
Data analytics has a public image problem. Ask most people what it involves and they'll picture dense spreadsheets, cryptic code, and years of statistics no one outside a classroom actually uses. Thinking With Data takes that misconception apart, chapter by chapter, and replaces it with something more honest: analytics is built on instincts you already use every day noticing what's different, asking why, and checking whether your answer actually holds up.
This is a complete, structured course, not a collection of tips. It follows one running example throughout a fictional grocery delivery company and the manager learning to make sense of its numbers so every concept lands somewhere concrete instead of staying abstract. You won't just learn what a median is; you'll watch someone use it to make a real decision, get it wrong, and figure out why.
What's inside:
The book is organized into six parts and twenty-four chapters, walked in order so nothing assumes knowledge you haven't been given yet.
Part One Seeing the Field Clearly: what data analytics actually is, the four kinds of questions data can answer, and who does what on a real team, so you know where you'd fit.
Part Two The Way Work Actually Gets Done: why process matters more than any tool, the six phases every project moves through, how to frame a question worth answering, and the unglamorous cleanup work no one mentions in job postings.
Part Three Statistical Thinking Without the Dread: averages, spread, samples, uncertainty, and the correlation-versus-causation traps that catch even experienced analysts explained without academic jargon.
Part Four Building Your Toolkit: a practical tour of spreadsheets, SQL, Python, dashboards and BI tools, and how to work productively alongside AI assistants, pitched at someone who has never opened any of them.
Part Five Making People Care: choosing the right chart, cutting what doesn't help, directing attention to what matters, and structuring an argument so your findings actually change a decision instead of being politely ignored.
Part Six Putting It All Together: one complete project from start to finish, how to build a portfolio with nothing to show yet, a realistic learning plan, and where to go once you've finished the book.
Each chapter closes with a short in-plain-terms summary and reflection questions meant to be sat with, not rushed through.
Who this is for: complete beginners, career switchers with no technical background, and anyone who has bounced off a "learn data analytics" course that opened with a math refresher instead of a real problem. No prior experience with spreadsheets, statistics, or programming is assumed.
By the end, you won't just know terminology you'll know how to ask a sharp question, find a defensible answer in messy real-world data, and explain what you found clearly enough that someone acts on it.
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