The analytical process does not end with models than can predict with accuracy or prescribe the best solution to business problems. Developing these models and gaining insights from data do not necessarily lead to successful implementations. This depends on the ability to communicate results to those who make decisions. Presenting findings to decision makers who are not familiar with the language of analytics presents a challenge. In this course you will learn how to communicate analytics results to stakeholders who do not understand the details of analytics but want evidence of analysis and data. You will be able to choose the right vehicles to present quantitative information, including those based on principles of data visualization. You will also learn how to develop and deliver data-analytics stories that provide context, insight, and interpretation.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Advanced Business Analytics
Communicating Business Analytics Results
von
4,593 Angemeldet
Lehrplan - Was Sie in diesem Kurs lernen werden
Woche
11 Stunde zum Abschließen
Introduction to the Course
In this module we’ll briefly review the Information-Action Value Chain we introduced in Course 1. Then we’ll see how analytical techniques are applied in business problems, first by looking at some “classic” business problems that have been around for a long time, then by looking at some “emergent” business problems that have resulted from more recent advances in technology.
4 Videos (Gesamt 35 min), 1 Quiz
4 Videos
1. Information Action Value Chain Redux5m
2. Analytics in Classic Business Problems11m
3. Analytics in Emergent Business Problems13m
1 praktische Übung
Week 1 Quiz20m
Woche
21 Stunde zum Abschließen
Best Practices in Data Visualization
In this module we’ll learn about a variety of visualizations used to illustrate and communicate data. We will start with the different vehicles used to present quantitative information. We will then look at a set of examples of data visualizations and discuss what makes them effective or ineffective. Finally, we discuss Excel charts and why most of them should be avoided. After completing this module, you will be able to better understand the characteristics of good data visualization and avoid common mistakes when creating your own graphs.
7 Videos (Gesamt 28 min), 1 Quiz
7 Videos
Vehicles to Present Quantitative Information4m
Data Visualization Examples3m
Graphs in Excel and ASP5m
Graphical Excellence4m
Techniques to Display Multiple Variables4m
Excel Charts to Avoid2m
1 praktische Übung
Week 2 Quiz30m
Woche
32 Stunden zum Abschließen
Interpreting, Telling, and Selling
In this module we’ll cover a number of topics around interpreting data, gathering additional data, and pitching our recommendations based on our analysis. First, we’ll discuss ways in which we misinterpret or misrepresent data and how to avoid them, such as mistaking correlation with causation, allowing cognitive biases to influence how we see data, and visualizing data in misleading ways. We’ll also learn how experimentation can help us obtain more data, including compromises we may need to make in measurement. Finally, we’ll discuss how we communicate our results and recommendations, with a focus on knowing our audience, telling compelling stories, and creating clear and effective communication materials.
7 Videos (Gesamt 62 min), 1 Quiz
7 Videos
Common Cognitive Biases10m
Misleading With Data8m
Market Experiments: When the action is the question7m
Know thy Audience11m
Telling compelling stories6m
Making It Real9m
1 praktische Übung
Week 3 Quiz38m
Woche
42 Stunden zum Abschließen
Acting on Data
In our final module we’ll walk through two case studies and illustrate the ideas we’ve covered in the course and in the specialization as a whole. The first case shows how experimentation can be used to create data, sometimes with surprising results. The second case presents a comprehensive analysis that illustrates the entire analytic lifecycle, and shows how different methods and both quantitative and qualitative analysis can be brought together to solve one strategically important analytical problem.
4 Videos (Gesamt 40 min), 2 Quiz
4 Videos
Case Study 2: Multidimensional Analysis for Customer Acquisition - Part 15m
Case Study 2: Multidimensional Analysis for Customer Acquisition - Part 211m
Case Study 2: Multidimensional Analysis for Customer Acquisition - Part 310m
2 praktische Übungen
Week 4 Quiz16m
Final Course Assignment
50%
nahm einen neuen Beruf nach Abschluss dieser Kurse auf
25%
ziehen Sie für Ihren Beruf greifbaren Nutzen aus diesem Kurs
Top-Bewertungen
I really enjoyed the materials presented in this course. I wish recommendations on reference books were provided in any of these courses.
Very good course, Case based learning and examples explaing use of analaytics clarifed the course a lot.
Dozenten
Manuel Laguna
ProfessorLeeds School of Business
Dan Zhang
ProfessorLeeds School of Business
David Torgerson
InstructorÜber University of Colorado Boulder
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
Über die Spezialisierung Advanced Business Analytics
The Advanced Business Analytics Specialization brings together academic professionals and experienced practitioners to share real world data analytics skills you can use to grow your business, increase profits, and create maximum value for your shareholders. Learners gain practical skills in extracting and manipulating data using SQL code, executing statistical methods for descriptive, predictive, and prescriptive analysis, and effectively interpreting and presenting analytic results.
The problems faced by decision makers in today’s competitive business environment are complex. Achieve a clear competitive advantage by using data to explain the performance of a business, evaluate different courses of action, and employ a structured approach to business problem-solving.
Check out a one-minute video about this specialization to learn more!
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