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
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Über diesen Kurs
Karriereergebnisse der Lernenden
50%
25%
Karriereergebnisse der Lernenden
50%
25%
Zertifikat zur Vorlage
100 % online
Kurs 4 von 5 in
Flexible Fristen
Ca. 9 Stunden zum Abschließen
Englisch
Lehrplan - Was Sie in diesem Kurs lernen werden
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.
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.
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.
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.
Bewertungen
Top-Bewertungen von COMMUNICATING BUSINESS ANALYTICS RESULTS
The case studies used in the course point out how complicated analytics can be, but the reality check is useful to set real world expectations. Overall, this course is very valuable and
I really enjoyed the materials presented in this course. I wish recommendations on reference books were provided in any of these courses.
The best part of this course was the final week in which the instructor wonderfully presented and explained the case study.
Very good course, Case based learning and examples explaing use of analaytics clarifed the course a lot.
The case study walk through in week4 for customer segmentation and churn was highly informative.
Great introduction , very detailed. Recommend to everyone good development practice.
give me an insight to how to present data into readable chart to the audience
Thank you! I love the instructor. I wish I could take his c
Informative and bite-sized. This was an effective course
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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 den Spezialisierung Advanced Business Analytics
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