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Packt – Data Forecasting and Segmentation Using Microsoft Excel 2022

Updated August 10, 2026 10.3 MB
Packt – Data Forecasting and Segmentation Using Microsoft Excel 2022

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Description

Data Forecasting and Segmentation Using Microsoft Excel is designed as a practical guide to performing linear forecasting, time series analysis, and data segmentation without having to write a single line of code. The book begins with a tutorial on basic statistics so that users can assess the modeling potential of their data. This approach helps analysts implement complex machine learning processes with the tools available in Excel.

A key part of the book is teaching the K-means clustering algorithm through Excel add-ins. This algorithm allows users to discover parts of the data that are not visible in conventional analytics and business intelligence (BI). Identifying outliers that may indicate fraud or network failures is another important skill that the reader will master by the end of this book.

Book Features

  • Complete training in data segmentation, regression, and time series forecasting without the need to code
  • Applying the K-means machine learning algorithm to manage and cluster multiple variables
  • Identifying outliers to detect financial fraud and errors in data structure
  • Suitable for data analysts, financial experts, auditors, and business intelligence professionals
  • Step-by-step training in statistical modeling based on past data with the familiar Microsoft Excel environment

Book specifications

  • Publisher: Packt
  • Instructor/Author: Fernando Roque
  • Number of pages: 325
  • Number of chapters: 13
  • Format: pdf

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Data Forecasting and Segmentation Using Microsoft Excel

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Data Forecasting and Segmentation Using Microsoft Excel

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What is included

  • Complete training in data segmentation, regression, and time series forecasting without the need to code
  • Applying the K-means machine learning algorithm to manage and cluster multiple variables
  • Identifying outliers to detect financial fraud and errors in data structure
  • Suitable for data analysts, financial experts, auditors, and business intelligence professionals
  • Step-by-step training in statistical modeling based on past data with the familiar Microsoft Excel environment