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Essentials of marketing analytics : 2024 Release ISE / Joseph F. Hair, Dana E. Harrison, Haya Ajjan.

By: Contributor(s): Material type: TextTextPublisher: New York : McGraw Hill Education, 2024Edition: First editionDescription: 474 pages : illustrations? ; 25 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781266931628
Subject(s): DDC classification:
  • 23 658.8 j.h.e.
Contents:
Part 1: Overview of marketing analytics and data management – 1. Introduction to marketing analytics; 2. Data management -- Part 2: Exploring and visualizing data patterns – 3. Exploratory data analysis using cognitive analytics; 4. Data visualization -- Part 3: Analytical methods for supervised learning – 5. Regression analysis; 6. Neural networks; 7. Automated machine learning -- Part 4: Analytical methods for unsupervised learning – 8. Cluster analysis; 9. Market basket analysis -- Part 5: Emerging analytical approaches – 10. Natural language processing; 11. Social network analysis; 12. Fundamentals of digital marketing analytics.
Summary: A timely, comprehensive introduction to marketing analytics for undergraduate and graduate business students. Combines theory with tools like Tableau and Python and explores topics such as neural networks, social network analysis, automated machine learning, and NLP. Supported by McGraw Hill Connect digital platform.turn0search6turn0search2turn0search7
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Holdings
Item type Current library Call number Copy number Status Date due Barcode Item holds
Books Books Media and mass communication Library AK3 658.8 H.J.E C.1 Available MA0003114
Total holds: 0

Part 1: Overview of marketing analytics and data management – 1. Introduction to marketing analytics; 2. Data management -- Part 2: Exploring and visualizing data patterns – 3. Exploratory data analysis using cognitive analytics; 4. Data visualization -- Part 3: Analytical methods for supervised learning – 5. Regression analysis; 6. Neural networks; 7. Automated machine learning -- Part 4: Analytical methods for unsupervised learning – 8. Cluster analysis; 9. Market basket analysis -- Part 5: Emerging analytical approaches – 10. Natural language processing; 11. Social network analysis; 12. Fundamentals of digital marketing analytics.

A timely, comprehensive introduction to marketing analytics for undergraduate and graduate business students. Combines theory with tools like Tableau and Python and explores topics such as neural networks, social network analysis, automated machine learning, and NLP. Supported by McGraw Hill Connect digital platform.turn0search6turn0search2turn0search7

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