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6.6 MB
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B0E11EC66F46AEA370A2386C2FEA3789D928462D
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Sept. 16, 2025, 6:35 a.m.
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(Last updated: Sept. 16, 2025, 6:38 a.m.)
| File | Size |
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| Khan L. The Data Analytics Advantage. Strategies and Insights...2025.pdf | 6.6 MB |
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450.1 MB
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2025-01-22
| Uploaded by anonymouspor | Size 450.1 MB | Health [ 5 /0 ] | Added 2025-01-22 |
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SOURCE: Khan L. The Data Analytics Advantage. Strategies and Insights...2025
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MEDIAINFO
Textbook in PDF format 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 (AI). 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. Social Media Analytics (SMA) comprises a diverse range of individuals and organizations. It can be performed by professionals within organizations as in-house teams. Depending on the financial prowess of an organization, large corporations can invest significantly in an in-house analytics team. Alternatively, SMA can be sourced out to outside vendors and companies. Professionals who engage in SMA can have distinct roles and responsibilities, which can depend on the type of organization and the overall needs and requirements of a social media project. You might have heard of titles such as social media analyst, social media manager, digital marketing analyst, data analyst, and data scientist. These are all interrelated terms and serve as good examples of professionals who perform SMA. What is common to all these roles is that these professionals possess the skills to make sense of social media data. It is worth noting that some roles require a more advanced skill set and understanding of tools and methodologies to conduct sophisticated analyses. Some would have advanced programming know-how in computer languages such as R and Python, while others would make detailed analyses using specialized tools for data analysis (such as SPSS). Yet others will specialize in data visualization and storytelling employing tools such as PowerBI and Tableau. Data cleaning, organization, and structuring are crucial steps in the text analysis process. Various tools provide a means to effectively structure and modify textual data, converting unprocessed, disorganized data into neat, organized information. Structuring textual data is crucial for academic research, business analytics, and SMA, as it forms the basis for exploration. The data structuring tools below offer a wide range of functionalities, including simple text manipulation and advanced data cleaning and transformation capabilities. They are suitable for both novices and experienced professionals in data analytics. Microsoft Excel (MS Excel) is a well-known spreadsheet application. It is included in the Microsoft Office 365 productivity software suite but can also be purchased separately. MS Excel is extensively used for various tasks, from fundamental data entry and accounting to advanced data analysis, charting, and financial modeling. Hence, MS Excel provides several functionalities for basic text structuring and analysis. However, it is essential to note that it has limitations, mainly when dealing with large datasets or when advanced text analytics capabilities are required. For more complex text analysis, specialized software or programming languages such as Python or R, commonly paired with NLP software, would be preferable. In the near future, the integration of Artificial Intelligence is set to further facilitate how users are able to engage in text structing an analysis. Preface Introduction: Analytics Overview Social Media Analytics Framework Goals, Metrics, and Measurement Data Gathering, Organizing, and Cleaning Textual Data Structuring Text Analytics Interpretative Methods and Tools Social Network Analysis Image and Video Analytics Data Visualization Spatial Analytics for Social Media Integrating Design Thinking into Dashboards and Reports Artificial Intelligence and the Future of Social Media Analytics
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