Introduction to Transforming with Data Analytics and the Digital Organization
About this Course
Every modern organization is a digital organization or will rapidly become digital. Artificial intelligence, Google/Amazon/Facebook/Uber, and big data have dramatically raised customer expectations and demand. Organizations that are effective in using data will win in the economies of the mid-21st century. These must-have core competencies include data analysis, machine learning, data visualizations, data mining, and predictive analytics, and deep learning. Organizations that won't or can't digitally transform will go the way of Blockbuster or Border's Bookstore. The organization that better harnesses the power of data to create a superior customer experience will thrive in the new business realities. The question is, how does an organization digitally transform? There are many digital technologies for organizations to choose from - too many choices! And digital technologies are only part of creating a digital organization. The employees must be trained in the new technologies, leaders must learn how to use data in making strategic decisions, and the organization's business processes must be reinvented. So many choices to make and the stakes have never been higher! This course will give you a framework to help you successfully navigate the challenges posed by digital transformation. First, we will discuss how to use the organization's dynamic capabilities to start the digital transformation. Second, we will use fitness landscapes to build a competitive digital business model. Finally, we will implement a strategic foresight function to help evolve the digital business model for the organization's continued success.Created by: The University of Maryland, College Park,University System of Maryland
Level: Introductory

Related Online Courses
This course assumes that you are comfortable with Microsoft Excel, but you do not need training in statistics. If you wish to receive a verified certificate, you must download the free SIPmath™ M... more
Durante las últimas décadas se ha producido un desarrollo explosivo en las tecnologías de almacenamiento y procesamiento de datos y por tanto un incremento en los volúmenes de información para ser ... more
Spreadsheet proficiency is a superpower. Learn how to use the various functionalities of Google Sheets to manipulate, inspect, and interpret data, separating the noise from what’s actually h... more
The job of a data scientist is to glean knowledge from complex and noisy datasets. Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the... more
Students learn to construct a wide variety of SQL statements – from beginning to more advanced concepts – such as joins, common table expressions, window functions, etc. Students also learn the bas... more