| Description |
1 online resource (175 pages) |
| Contents |
Cover; Half Title; Title Page; Copyright Page; Dedication; Table of Contents; Acknowledgements; Foreword; 1. Introduction; For the practising manager; A non-technical book; Structure of the book; 2. Big Data revolution; Data driven decisions and value creation; History of data and Big Data; Data and analysis; Data analysis and statistics; Data analysis and computing; Advances in collection mechanisms; Relational databases; Data warehouse and business intelligence; Data mining; Google web search; Big Data analysis on the cloud; Structured data; Unstructured data; Big Data; Customer data |
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Employee dataCompetition data; Summary; Notes; 3. Creating value from Big Data; Value drivers in commercial organizations; The proforma income statement and balance sheet; Market value and non-financial values; Investments where Big Data can create value; Creating value from additional revenue from existing customers -- higher prices; Creating value from customer satisfaction; Creating value from reduced subscriber acquisition costs; Creating value from more effective marketing -- acquiring more customers; Creating value from customer retention value |
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When data itself is the source of value creationSummary; Notes; 4. Big Data techniques and solutions; Big Data analytics; Operational excellence; Smart decision making; Innovation; Data analytics techniques; Statistical analysis; Social network analysis; Semantics; Data visualization; Predictive analysis; Summary; Notes; 5. Introducing the model: design and implementation; C-ADAPT model of Big Data value creation; 1. C (Challenges and/or goals); 2. A (Areas identification); 3. D (Data discovery); 4. A (Analysis and insights); 5. P (Presentation and visualization) |
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6.T (Testing the value created, refine and repeat)C-ADAPT worksheet; C -- Challenges and goals; A -- Areas related; D -- Data discovery; A -- Analysis and insights; P -- Presentation and visualization; T -- Testing the value created, refine and repeat; Summary; Notes; 6. Big Data case studies; Ooredoo (formerly Qtel); Rebranding and message amplification; Domino's Pizza; Understanding buying behavior; Leading antivirus company; Increasing engagement and driving revenue; Gate Gourmet; Use of data for competitive analysis; Tesco; Knowing customer insights from data; Delta Airlines |
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Data is helping them find lost baggageIntel; Saving manufacturing costs with Big Data; TXU Energy; Saving costs by using smart electric meters; OmedaRx; Big Data to improve medication adherence; John Deere; Revolutionizing farming using Big Data; Airbnb; Price recommendations using Big Data; Walmart; Smart searching using semantic analysis; Huffington Post; Using Big Data to drive the traffic; Summary; Notes; 7. What practitioners say; Big Data is important -- very important!; Key value from Big Data; Challenges in implementing Big Data projects; Summary; Notes; 8. Conclusion and discussion |
| Summary |
In today's fast growing digital world, the web, mobile, social networks and other digital platforms are producing enormous amounts of data that hold intelligence and valuable information. Correctly used it has the power to create sustainable value in different forms for businesses. The commonly used term for this data is Big Data, which includes structured, unstructured and hybrid structured data. However, Big Data is of limited value unless insightful information can be extracted from the sources of data. The solution is Big Data analytics, and how managers and executives can capture value from this vast resource of information and insights. This book develops a simple framework and a non-technical approach to help the reader understand, digest and analyze data, and produce meaningful analytics to make informed decisions. It will support value creation within businesses, from customer care to product innovation, from sales and marketing to operational performance. The authors provide multiple case studies on global industries and business units, chapter summaries and discussion questions for the reader to consider and explore. Big Data for Managers also presents small cases and challenges for the reader to work on - making this a thorough and practical guide for students and managers |
| Notes |
Index |
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Print version record |
| Subject |
Big data.
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Management.
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Value.
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management.
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value (economic concept)
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Big Data Management.
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big data.
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business intelligence.
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Creating Value.
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Data Analytics.
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machine learning.
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operational performance.
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product innovation.
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sustainable value.
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Big data
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Management
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Value
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| Form |
Electronic book
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| Author |
Malmgren, Mike
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| LC no. |
2018022753 |
| ISBN |
9780429952616 |
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0429952619 |
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9780429952609 |
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0429952600 |
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