Excel for Data Analytics

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Master the World’s Most Powerful Data Tool—No Coding Required.

Excel is more than just rows and columns—it’s a powerhouse for data analytics used by professionals across every industry. Excel for Data Analytics is a comprehensive, step-by-step guide to turning data into decisions using the tools you already have on your computer.

Whether you’re a student, business analyst, marketer, finance professional, or someone transitioning into a data role, this book equips you with the essential skills to explore, analyze, and visualize data with confidence.

What You’ll Learn:

  • 🔍 Data Cleaning & Preparation: Learn how to structure, filter, and clean raw data for accurate analysis.

  • 📊 Descriptive Statistics & Analysis: Use formulas and functions to summarize trends, identify patterns, and uncover insights.

  • 🔄 Pivot Tables & Pivot Charts: Quickly break down large datasets to answer complex questions with ease.

  • 📈 Data Visualization: Create dashboards, charts, and graphs that make your data easy to interpret and share.

  • 🧠 Logical & Lookup Functions: Master IF statements, VLOOKUP, INDEX-MATCH, and more to supercharge your analysis.

  • 💡 Real-World Use Cases: Apply your skills in business scenarios like sales reporting, customer insights, and operational metrics.

The book includes downloadable practice files, templates, and real-world datasets so you can apply what you learn right away.

No prior experience needed. Just open Excel and follow along—you’ll be amazed how quickly you level up.

If you’re ready to start making data-driven decisions and stand out in the job market, this is the guide you need.

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$1,499.00

Turn raw data into clear insights with the power of Excel.
Excel for Data Analytics is your practical guide to mastering spreadsheets for real-world data analysis.
Learn how to clean, organize, and visualize data using formulas, functions, pivot tables, charts, and more.
Designed for beginners and intermediate users, this book makes complex concepts easy to understand and apply.
Whether you’re in business, marketing, finance, or research, this is your first step to becoming a data-savvy professional.

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