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Data literacy is one of the key skills that companies are looking for but it's a specialist skill - currently. This book is your comprehensive guide to becoming data literate: understand data analytics, how to use data insights effectively in your organisation, and how to talk about data with experts and non-experts confidently.
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Data literacy is one of the key skills that companies are looking for but it's a specialist skill - currently. This book is your comprehensive guide to becoming data literate: understand data analytics, how to use data insights effectively in your organisation, and how to talk about data with experts and non-experts confidently.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Pearson ITP
- Seitenzahl: 250
- Altersempfehlung: ab 18 Jahre
- Erscheinungstermin: 26. Mai 2022
- Englisch
- ISBN-13: 9781292421209
- Artikelnr.: 64133674
- Verlag: Pearson ITP
- Seitenzahl: 250
- Altersempfehlung: ab 18 Jahre
- Erscheinungstermin: 26. Mai 2022
- Englisch
- ISBN-13: 9781292421209
- Artikelnr.: 64133674
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Martin J. Eppler, PhD, is a chaired professor of communications management at St. Gallen University, one of Europe's top 10 business schools, where he is the director of a global MBA program. He is the author of 22 books, including the getabstract international business book of the year winner "Meet up!" (Cambridge University Press). He is a 10 times "MBA course of the year" winner and received numerous best paper awards for his research on communication issues in management. His research has been featured in The Guardian, Businessweek, the Harvard Business Review, Inc. magazine, the MIT Technology Review. He is an advisor to organizations such as the European Central Bank, the United Nations, IATA, Tawuniya, Porsche, Swiss Re, or Nike. He has been a guest professor at Georgiatech in the US, Cambridge University in the UK, Simon Fraser University in Canada, Aalto University in Finland, and CUFE in China, as well as Pacifico in Peru. For the last 15 years, he has been editor of Europe's largest and longest running change management journal ZOE (part of Handelsblatt).
Fabienne Bünzli, PhD, is a lecturer and project manager at the University of St. Gallen where she conducts research on persuasive communication . Her research has been published journals such as the Journal of Nonprofit Management & Leadership, Journalism, or the Journal of Philanthropy and Marketing. Her work has been recognized with the Best Paper Award of the Swiss Association of Communication and Media Research in 2018. Prior to her academic career, she has worked as a public relations and communications specialist.
PART I: The Manager as Data User: Making Sense of Data
1. Overcoming Analytics Anxiety
2. Making sense of statistics: Achieving a global view of data
3. Predicting outcomes: Modelling the world with data
4. Understanding relationships: Probing for the when, how, and why
5. Differences that make a difference: How to segment the world
statistically (and what machine learning looks like)
PART II: The Manager as Data Facilitator: Conveying Data-based Insights
6. The Five Magic Ingredients of Data Storytelling
7. The Data Storytelling Canvas
8. How to visually DESIGN your Data: A Manager’s Chart Guide
9. How to Work with Software in front of others
10. Effective Analytics Q & A Sessions
PART III: The Manager as Collaboration Partner: Making Analytics Work
11. A Typology of common cooperation challenges in Analytics
12. A Recipe for Better Analytics Collaboration
Conclusion: Future proof Analytics
1. Overcoming Analytics Anxiety
2. Making sense of statistics: Achieving a global view of data
3. Predicting outcomes: Modelling the world with data
4. Understanding relationships: Probing for the when, how, and why
5. Differences that make a difference: How to segment the world
statistically (and what machine learning looks like)
PART II: The Manager as Data Facilitator: Conveying Data-based Insights
6. The Five Magic Ingredients of Data Storytelling
7. The Data Storytelling Canvas
8. How to visually DESIGN your Data: A Manager’s Chart Guide
9. How to Work with Software in front of others
10. Effective Analytics Q & A Sessions
PART III: The Manager as Collaboration Partner: Making Analytics Work
11. A Typology of common cooperation challenges in Analytics
12. A Recipe for Better Analytics Collaboration
Conclusion: Future proof Analytics
PART I: The Manager as Data User: Making Sense of Data
1. Overcoming Analytics Anxiety
2. Making sense of statistics: Achieving a global view of data
3. Predicting outcomes: Modelling the world with data
4. Understanding relationships: Probing for the when, how, and why
5. Differences that make a difference: How to segment the world
statistically (and what machine learning looks like)
PART II: The Manager as Data Facilitator: Conveying Data-based Insights
6. The Five Magic Ingredients of Data Storytelling
7. The Data Storytelling Canvas
8. How to visually DESIGN your Data: A Manager’s Chart Guide
9. How to Work with Software in front of others
10. Effective Analytics Q & A Sessions
PART III: The Manager as Collaboration Partner: Making Analytics Work
11. A Typology of common cooperation challenges in Analytics
12. A Recipe for Better Analytics Collaboration
Conclusion: Future proof Analytics
1. Overcoming Analytics Anxiety
2. Making sense of statistics: Achieving a global view of data
3. Predicting outcomes: Modelling the world with data
4. Understanding relationships: Probing for the when, how, and why
5. Differences that make a difference: How to segment the world
statistically (and what machine learning looks like)
PART II: The Manager as Data Facilitator: Conveying Data-based Insights
6. The Five Magic Ingredients of Data Storytelling
7. The Data Storytelling Canvas
8. How to visually DESIGN your Data: A Manager’s Chart Guide
9. How to Work with Software in front of others
10. Effective Analytics Q & A Sessions
PART III: The Manager as Collaboration Partner: Making Analytics Work
11. A Typology of common cooperation challenges in Analytics
12. A Recipe for Better Analytics Collaboration
Conclusion: Future proof Analytics







