Text Analytics For Business Decisions A Case Study Approach Andres Fortino by Andres Fortino ce53fff9-0b60-4138-9b9c-34e130e2aa20, CE53FFF9-0B60-4138-9B9C-34E130E2AA20 instant download after payment.

With the rise in data science development, we now have many remarkable techniques and tools to extend data analysis from numeric and categorical data to textual data. Sifting through the open-ended responses from a survey, for example, was an arduous process when performed by hand. Using a case study approach, this book was written for business analysts who wish to increase their skills in extracting answers for text data in order to support business decision making. Most of the exercises use Excel, today’s most common analysis tool, and R, a popular analytic computer environment. The techniques covered range from the most basic text analytics, such as key word analysis, to more sophisticated techniques, such as topic extraction and text similarity scoring. Companion files with numerous datasets are included for use with case studies and exercises(available for downloading with Amazon proof of purchase by writing to [email protected]).

Features

+Organized by tool or technique, with the basic techniques

presented first and the more sophisticated techniques presented later

+Uses Excel and R for datasets in case studies and exercises

+Features the CRISP-DM data mining standard with early chapters for

conducting the preparatory steps in data mining

+Companion files with numerous datasets and figures from the text (available for downloading with Amazon proof of purchase by writing to [email protected])

Brief Table of Contents