04-611-Carnegie Mellon University Africa - Carnegie Mellon University


Strategic Use of Digital Information in Enterprises

Course discipline: Business
Units: 12
Lecture/Lab/Rep hours/week: 4 hours lecture/week
Semester/year offered (fall/spring, even/odd years): fall, all years
Pre-requisites: none

Course description:

An unprecedented access to real-time and unfiltered world information is providing enterprise with new strategic information assets. This information is characterized by 1) large volume of the data, 2) the diversity of the data, not only structured data typically created by enterprises’ transaction systems, but mostly unstructured data found in enterprises (business documents, emails, reports, customers communication documents, etc) but also from outside the enterprise (social media, multimedia (video, audio), Internet, sensors, mobile devices, non-conventional IT devices (GPS, RFID readers,…), 3) the geographical distribution of the sources of information and 4) the timeliness value of that information when captured in real time. This is sometime called BIG DATA. The ability to pull value from this data is a crucial competitive differentiator. The challenge is to turn this massive amount and continuous stream of data and information into knowledge and insights in real-time to provide actionable information to assist decision makers in enterprises in support of the execution of their strategic plan. This requires the use of new technical architectures and analytics to enable insights that unlock new sources of business value.
The data-driven enterprise of tomorrow is one that makes business decisions based on amassing and analyzing that data in real time. It leverages the enormous computational power that can now be delivered by small, abundant and inexpensive devices. All of these digital devices—soon to number in the trillions—are being connected through the Internet, turning data into intelligence, using their processing power and advanced analytics to make sense of it all. They deliver a new generation of applications that have a material impact on the top line. With this knowledge enterprises can reduce cost and waste, improve efficiency and productivity, and raise the quality of their products.
This course will cover the new emerging generation of information systems used to manage the explosion of this new real-world real-time information and deliver business analytics. 
Guest executive speakers from local and global businesses will provide direct insight into the corporate world and real business application of technologies and concepts reviewed in the course.

Learning objectives:

The primary goal of this course is provide students with an introduction to new generation of technologies providing enterprises with strategic information assets.
In this course, students will learn about:
  • the process leading from data to information (for both structured and unstructured data), from information to knowledge, from knowledge to insight and finally from insight to decision
  • the new information and communication technologies available at each step of this process
  • how businesses are using these technologies to become more competitive
  • the evolution of enterprises from transaction centric to information centric organizations


After completing this course, students should be able to:
  • Know the technologies supporting the process leading from data to decision
  • Understand and explain the business value of those technologies and how they can be used in enterprises and organizations
  • Use their knowledge of those technologies to conceive new innovative data driven solutions to business problems 

Content details:

The course will cover the following topics:
  • Information Value in Enterprises
  • Business Information Management
  • Big Data
  • Web 2.0
  • Linked Data-Open Data
  • Consumer Generated Media
  • Social Networks
  • Digital Marketing
  • Real World Aware Systems -Stream Computing
  • Real-time transcription
  • Machine translation
  • Cloud Computing
  • Digital information analytics
  • ICT in sub-Saharan Africa

Information Value in Enterprises

  • Digital information
  • Digital content and data exponential growth
  • The new generation of infonautes
  • From data to knowledge to decision
  • Semantically tagged documents
  • A different model for enterprises
  • Value of information in enterprises: how is it different?
  • Information-centric enterprises

Big Data

  • HVCATS market
  • Data science and Big Data analytics
  • Definition of big data 
  • Big data characteristics and considerations
  • Unstructured data fueling big data analytics 
  • Analyst perspective on Data Repositories
  • Data Analytics Lifecycle
  • Roles for a Successful Analytics Project 
  • Case Study to apply the data analytics lifecycle

Web 2.0

  • Web 2.0 technology
  • Web 2.0 business models
  • Long tail pricing
  • Crowd computing

Open data

  • Linked data
  • RDF graph
  • Semantically tagged documents
  • Sharing data on the web

Consumer Generated Media

  • Emergence of CGM
  • Impact and importance of CGM
  • CGM monitoring

Social Networks

  • Classification of social media
  • Social media impact
  • The new consumer - company relation
  • Influence 2.0
  • How CMUR is using social media?

Digital Marketing

  • Traditional vs. digital marketing
  • Digital marketing vendors
  • Data-driven marketing
  • How leaders are using data-driven marketing
  • 15 metrics to improve marketing performance

Real-World Aware Systems

  • Complex event processing
  • Stream computing
  • UIMA
  • Stream analytics scenarios

Real Time Transcription

  • Speech synthesis
  • Speech recognition
  • Voice analysis
  • Needs for speech technology

Machine Translation

  • Top languages
  • Methods of machine translation
  • Conversational translation
  • Publishing translation
  • Gisting translation
  • Market segment positioning
  • Real-time translation
  • Speech-to-speech translation
  • Advantages of cloud based solutions

Cloud Computing

  • Forces driving the transformation of data centers
  • Evolution of cloud computing
  • Cloud computing delivery models
  • Attributes and benefits of cloud computing
  • Cloud solution stack
  • Cloud computing in Africa

Digital Information Analytics

  • Advanced Analytics for Information Management
  • High-bandwidth Analytics via Responsive Visual Exploration, Summarization and Tracking
  • Multimedia Analysis and Retrieval System for Digital Content Repositories
  • Multilingual Automatic Speech-to-Speech Translator
  • Sentiment Analysis 
  • Translingual Automatic Language Exploitation System
  • Text Analysis and Knowledge Mining
  • Spoken Web

ICT in Sub-Saharan Africa

  • Importance of SMEs
  • Three key new information technologies
  • Business value for SMEs and Africa

Delivery: Face-to-face

Faculty: Michel Bezy