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.
Ce cours fait partie de la Spécialisation Advanced Business Analytics
Communicating Business Analytics Results
proposé par
Programme du cours : ce que vous apprendrez dans ce cours
Semaine
1Introduction 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 vidéos (Total 35 min), 1 quiz
4 vidéos
1. Information Action Value Chain Redux5 min
2. Analytics in Classic Business Problems11 min
3. Analytics in Emergent Business Problems13 min
1 exercice pour s'entraîner
Week 1 Quiz20 min
Semaine
2Best 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 vidéos (Total 28 min), 1 quiz
7 vidéos
Module Introduction2 min
Vehicles to Present Quantitative Information4 min
Data Visualization Examples3 min
Graphs in Excel and ASP5 min
Graphical Excellence4 min
Techniques to Display Multiple Variables4 min
Excel Charts to Avoid2 min
1 exercice pour s'entraîner
Week 2 Quiz30 min
Semaine
3Interpreting, 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 vidéos (Total 62 min), 1 quiz
7 vidéos
Common Cognitive Biases10 min
Misleading With Data8 min
Market Experiments: When the action is the question7 min
Know thy Audience11 min
Telling compelling stories6 min
Making It Real9 min
1 exercice pour s'entraîner
Week 3 Quiz38 min
Semaine
4Acting 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 vidéos (Total 40 min), 2 quiz
4 vidéos
Case Study 2: Multidimensional Analysis for Customer Acquisition - Part 15 min
Case Study 2: Multidimensional Analysis for Customer Acquisition - Part 211 min
Case Study 2: Multidimensional Analysis for Customer Acquisition - Part 310 min
2 exercices pour s'entraîner
Week 4 Quiz16 min
Final Course Assignments
4.3
12 avis33%
a bénéficié d'un avantage concret dans sa carrière grâce à ce cours
Meilleurs avis
par SK•Mar 1st 2018
I really enjoyed the materials presented in this course. I wish recommendations on reference books were provided in any of these courses.
par AK•Mar 18th 2018
Very good course, Case based learning and examples explaing use of analaytics clarifed the course a lot.
Enseignants
Manuel Laguna
ProfessorLeeds School of Business
Dan Zhang
ProfessorLeeds School of Business
David Torgerson
InstructorÀ propos de 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.
À propos de la Spécialisation 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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