Unlock Microsoft Excel's hidden potential with this dynamic guide designed for data professionals and enthusiasts. You'll start by reviewing Excel basics before advancing to powerful tools like Excel Tables, Pivot Tables, and Power Query. Each chapter enhances your ability to analyze and visualize data efficiently, from complex lookups and dynamic arrays to essential data validation techniques that ensure accuracy and integrity in your spreadsheets.

As you progress, you'll learn how to protect your work with advanced sheet protection methods and collaboration tools for seamless teamwork. The book also covers sophisticated functions like INDIRECT, OFFSET, and LET, preparing you to tackle complex data challenges. Additionally, you'll receive critical advice on avoiding the pitfalls of machine learning-driven features and maintaining clean, organized data.

By the end of the guide, you'll have mastered Excel's advanced capabilities, empowering you to streamline workflows, optimize data processes, and make confident, data-driven decisions. This guide is your comprehensive resource for transforming your approach to data analysis with Excel.

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Spis treści

Guerrilla Data Analysis Using Microsoft Excel. Overcoming Crap Data and Excel Skirmishes eBook -- spis treści

• 1. Reviewing the Basics
• 2. Excel Tables: The Glue in Dynamic Spreadsheet Development
• 3. Collaboration Tools
• 4. Summing and Counting with Criteria
• 5. VLOOKUP and XLOOKUP
• 6. Pivot Tables: The Turning Point!
• 7. Power Query
• 8. Conditional Formatting
• 9. De-duping in Excel
• 10. Dynamic Arrays
• 11. Data Is Never 100% Clean (Not for Very Long)
• 12. Data Validation: Controlling Inputs and Maintaining Data Integrity
• 13. Protecting Sheets and Cells
• 14. Octopus Spreadsheets
• 15. INDIRECT
• 16. OFFSET
• 17. Recognizing Patterns
• 18. Data Types and Stock History
• 19. Graphing
• 20. The Dangers of Just Diving In
• 21. The LET Function
• 22. Warnings About Machine Learning–Driven Features in Excel and Power Query
• 23. Avoid Working on Your Source Data
• 24. Using Slicers
• 25. Data Models and Relationships
• 26. People, Processes, and Tools
• 27. Keeping Your Data in as Few Places as Possible
• 28. Rough-and-Tumble Tips and Insights
• 29. Spreadsheet Layout and Development