Course Description

Course Name

Big Data and Business Intelligence (in English)

Session: VSVS1121

Hours & Credits

45 Contact Hours

Prerequisites & Language Level

Taught In English

  • There is no language prerequisite for courses at this language level.


Course Description: Managing and analyzing data have always offered the greatest benefits and also challenges for small to large organizations in all industries. Businesses have always struggled with finding the right approach to capture information about their customer, products and services. As companies and the markets in which they operate have grown complicated, companies added more product lines and diversified how they deliver these products in order to survive or to be competitive. All this required information and with the advent of technology and the emergence of new sources of information, such as social media and click-stream data generated from website interaction, the volume of data has increased exponentially. Big data is becoming one of the most important technology trends that has the potential for dramatically changing the way organizations use information to enhance the customer experience and transform their business models. How does a company go about using data to the best advantage? What does it mean to transform massive amounts of data into knowledge? This course will introduce you to the concept of Big Data we provide you with insights into how technology transitions in software, hardware, and delivery models are changing the way that data can be used in new ways and how business can create value from its adoption.

Course Contents:

Part I: Getting started with Big Data

· Grasping the Fundamentals of Big Data

· Examining Big Data Types and Characteristics

Part II: Technology Foundations for Big Data

· Big Data Technology Components

· Examining the Cloud and Big Data

Part III: Big Data Management

· Looking at Operational Databases (RDBMs, Nonrelational, key-value pair….)

· MapReduce Fundamentals

· Hadoop and Hadoop Foundation and Ecosystem Fundamentals

Part IV: Analytics and Big Data

· Using Big Data to Get Results

· Understanding Text Analytics and Big Data

· Customizing Models and Approaches for Analysis of Big Data

Part V: Big Data and Business

· Integrating Data Sources

· Making Big Data a Part of the Operational Process

· Implementation Needs and Issues

· Data security and Protection

Material: Compilation by lecturer and online resources

*Course content subject to change