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Book synopsis

The Data Analytics Advantage is a comprehensive guide that equips readers with the essential skills to analyze and leverage social media data for strategic decision-making. Combining academic principles with case studies, social media analytics expert Laeeq Khan provides a foundational understanding of the field and its importance, introduces cutting-edge trends and tools through interactive tutorials and exercises, and offers a glimpse into future developments, including the potential impact of artificial intelligence.With its balance of technical rigor and accessibility, the textbook requires minimal coding experience while covering a wide range of topics. Using a three-stage framework--discovery, analysis, visualization--Khan emphasizes the importance of question formulation, data collection, and the skillful application of analytical tools; unveils key aspects of social media analytics, from hashtag and temporal analysis to social network analysis, data visualization, and storytelling; introduces readers to various methodologies, including monitoring metrics and KPIs, adopting advanced data visualization techniques, and mastering sentiment and network analysis; and addresses potential challenges in social media analytics, such as data access, privacy, and ethics. Readers will come away with a solid grasp of theoretical concepts as well as hands-on experience through practical exercises, making The Data Analytics Advantage an indispensable resource for students, social media administrators, marketers, and data analysts alike in the rapidly evolving field of social media analytics.

Book details

Book category Books in German Sozialwissenschaften, Recht, Wirtschaft Politikwissenschaft Staatslehre und politische Verwaltung

• Full title: The Data Analytics Advantage
• Author: Khan, Laeeq (Associate Professor and founding Director of the SMART Lab, Associate Professor and founding Director of the SMART Lab, Ohio University)
• Language: English
• Binding: Hardback
• Number of pages: 296
• EAN: 9780197814222
• ISBN: 0197814220
• ID: 48163274
• Publisher: Oxford University Press Inc
• Weight: 584 g
• Dimensions: 235 × 156 mm
• Date of publishing: 07. November 2025

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