Text Analytics for Business Decisions A Case Study Approach.

This book helps for business analysts who wish to increase their skills in extracting answers for text data in order to support business decision making. --

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Fortino, Andres
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Bloomfield : Mercury Learning & Information, 2021.
Temas:
Data mining.
Text processing (Computer science)
Business > Decision making > Data processing.
Exploration de données (Informatique)
Traitement de texte.
Business > Decision making > Data processing
Data mining
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Contents
  • Preface
  • On the Companion Files
  • Acknowledgements
  • Chapter 1 : Framing Analytical Questions
  • Data is the New Oil
  • The World of the Business Data Analyst
  • How Does Data Analysis Relate to Decision Making?
  • How Do We Frame Analytical Questions?
  • What are the Characteristics of Well-framed Analytical Questions?
  • Exercise 1.1
  • Case Study Using Dataset K: Titanic Disaster
  • What are Some Examples of Text-Based Analytical Questions?
  • Additional Case Study Using Dataset J: Remote Learning Student Survey
  • References
  • Chapter 2 : Analytical Tool Sets
  • Tool Sets for Text Analytics
  • Excel
  • Microsoft Word
  • Adobe Acrobat
  • SAS JMP
  • R and RStudio
  • Voyant
  • Java
  • Stanford Named Entity Recognizer (NER)
  • Topic Modeling Tool
  • References
  • Chapter 3 : Text Data Sources and Formats
  • Sources and Formats of Text Data
  • Social Media Data
  • Customer opinion data from commercial sites
  • Email
  • Documents
  • Surveys
  • Websites
  • Chapter 4 : Preparing the Data File
  • What is Data Shaping?
  • The Flat File Format
  • Shaping the Text Variable in a Table
  • Bag-of-Words Representation
  • Single Text Files
  • Exercise 4.1
  • Case Study Using Dataset L: Resumes
  • Exercise 4.2
  • Case Study Using Dataset D: Occupation Descriptions
  • Additional Exercise 4.3
  • Case Study Using Dataset I: NAICS Codes
  • Aggregating Across Rows and Columns
  • Exercise 4.4
  • Case Study Using Dataset D: Occupation Descriptions
  • Additional Advanced Exercise 4.5
  • Case Study Using Dataset E: Large Data Files
  • Additional Advanced Exercise 4.6
  • Case Study Using Dataset F: The Federalist Papers
  • References
  • Chapter 5 : Word Frequency Analysis
  • What is Word Frequency Analysis?
  • How Does It Apply to Text Business Data Analysis?
  • Exercise 5.1
  • Case Study Using Dataset A: Training Survey
  • Exercise 5.2
  • Case Study Using Dataset D: Job Descriptions
  • Exercise 5.3
  • Case Study Using Dataset C: Product Reviews
  • Additional Exercise 5.4
  • Case Study Using Dataset B: Consumer Complaints
  • Chapter 6 : Keyword Analysis
  • Exercise 6.1
  • Case Study Using Dataset D: Resume and Job Description
  • Exercise 6.2
  • Case Study Using Dataset G: University Curriculum
  • Exercise 6.3
  • Case Study Using Dataset C: Product Reviews
  • Additional Exercise 6.4
  • Case Study Using Dataset B: Customer Complaints
  • Chapter 7 : Sentiment Analysis
  • What is Sentiment Analysis?
  • Exercise 7.1
  • Case Study Using Dataset C: Product Reviews
  • Rubbermaid
  • Exercise 7.2
  • Case Study Using Dataset C: Product Reviews-Windex
  • Exercise 7.3
  • Case Study Using Dataset C: Product Reviews-Both Brands
  • Chapter 8 : Visualizing Text Data
  • What Is Data Visualization Used For?
  • Exercise 8.1
  • Case Study Using Dataset A: Training Survey
  • Exercise 8.2
  • Case Study Using Dataset B: Consumer Complaints
  • Exercise 8.3
  • Case Study Using Dataset C: Product Reviews

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