Course ID: | MIST 7720. 1.5 hours. |
Course Title: | Emerging Analytical Technologies, Platforms, and Applications |
Course Description: | There is a need to store and analyze Big Data. Specialized
analytical platforms have emerged to provide the performance
needed to analyze this and other data. Tightly integrated
applications are available that facilitate the use of analytics
for specific purposes. Includes the latest technologies,
platforms, and applications. |
Oasis Title: | EMERGING TECH-APPS |
Prerequisite: | MIST 7600 and MIST 7770 or permission of department |
Semester Course Offered: | Offered every year. |
Grading System: | A-F (Traditional) |
|
Course Objectives: | The purpose of this class is for students to learn the emerging
analytical technologies, platforms, and applications used in
leading organizations today. Specifically, we have the following
objectives for you as a student in this course:
To understand the characteristics of Big Data, which is
characterized by high volume, high velocity, and high variety.
To understand the emerging technologies and platforms for
collecting, storing, and analyzing sets of structured and
unstructured data. To understand how these technologies and
platforms can be integrated into the larger business
intelligence environment.
To understand the analytical applications used to analyze data
and text. To have hands-on experiences using these
technologies, platforms, and applications. |
Topical Outline: | Some of the topics we will cover in class will include:
• Big Data concepts
• Enabling technologies for Big Data
• Big Data technologies and platforms
• Data warehouses
• Data appliances
• Analytical sandboxes
• In-memory analytics
• Columnar databases
• Streaming and critical event processing engines
• Third party hosted platforms
• Non-relational databases
• Hadoop/MapReduce
• Text mining
• Natural language processing
• Digital data streams
• Integrating the platforms
• Big Data applications
• Hadoop/MapReduce concepts, architecture, and
applications
• Hands-on use of various platforms and applications
• Organizational issues |
Honor Code Reference: | Every student who enrolls at the University agrees to be bound
by the policy. This means that each student has a
responsibility to read the policy. [a copy is located at
http://www.uga.edu/ovpi/honesty/main.html] and comply with it.
It’s no defense to a charge of academic dishonesty to say ‘I
didn’t know that was prohibited.’ … Students must perform all of
their academic work without plagiarizing, cheating, lying,
tampering, stealing, receiving assistance from others (unless
the faculty member authorizes that assistance) or using sources
to assist in that work (without giving fair attribution).
[Source: “A Culture of Honesty at the University of Georgia.” A
pamphlet published by the UGA Office of the Vice President for
Instruction].
Important! You are NOT to receive ANY outside assistance on the
computing projects without prior approval from the professor. In
fairness to the students who are ethical, any student found
violating the academic honor code will be prosecuted. Your
projects must be the result of your individual effort. |