California University of Management and Technology
1135 Sonora Ct., Sunnyvale, CA 94086
Email: info@calmat.us
CSIT 700 Big Data Concept course Syllabus v1.01
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CSIT 700 Big Data Concept
Jian J. Shi
jian1@sbcglobal.net
(650) 315-8548
jianjshi
February 7, February 21, March 14, *April 4, 2015
CSIT 700
2 Credit Hours
8 weeks (4 class meetings)
9:30 pm—12:00 pm
by appointment
Big Data Glossary
By Peter Warden
ISBN: 978-1-449-31459-0
Other Materials:
Basic Requirement:
Supplementary readings will be provided on uLearn
Basic MBA and Computer knowledge
Course Description:
This course is an introduction to basic Big Data concept and help students to understand how Big
Data will impact future business, and how to use big data to create and improve your business.
Topics covered will include introduction of Big Data concept, NoSQL database, Hadoop, Map
Reduce, Storage, Servers, Processing and the logical and physical structure of big data. The
business benefits will be by using big data. Introduce the major big data provider and their strong
points. Introduce machine learning, virtualization concepts.
Course Objectives:
Students will be able to:
1. Understand what is big data, where is the big data come from, why we need SQL and
NoSQL database.
2. Understand Big Data, Map Reduce, and Storage Servers, Processing and NLP concept
and relationship.
3. Define the data elements needed to solve the problem. Define the business requirement to
find out the data need.
4. Read and interpret high level big data and computer system, hardware and software to
support the big data.
5. Learn more hands on Oracle Big Data Lab to better understand how to using big data at
real industry.
Students who successfully complete this course will be able to analyze a business problem and
successfully make a high level design project by using big data and relational database to solve
that problem. Students are expected to present their design and explain how the project to solve a
real-world problem.
Software:
Oracle Big Data software
(OTN License)
Rec. Reference:
Documents Set for Oracle Big Data
Instruction Methods: In Class Lectures and some hands on Lab
Requirements:
Draft Schedule:
Week
1 02/07/2015
2 02/21/2015
3 03/14/2015
4 43/04/2015
Participate Saturday class-room seminars
6-12 hours a week read assignment and online learning
Homework due on time
Topic
Big Data, SQL and NoSQL
Hadoop, Map Reduce, Storage
Servers, Processing, NLP
Oracle Big Data Lab
Grading:
30%
20%
40%
10%
Homework
in class midterm quiz
Final Project
Participation in class
Grading System:
Letter Grade
A+
A
AB+
B
BC+
C
C-
Grade Points
4.0 = 96 ~ 100
4.0 = 91 ~ 95
3.7 = 88 ~ 90
3.3 = 85 ~ 87
3.0 = 82 ~ 84
2.7 = 79 ~ 81
2.3 = 75 ~ 78
2.0 = 73 ~ 75
1.7 = 70 ~ 72
Reading Assignment
Chapter 1, 2
Chapter 3, 4
Chapter 5, 6
Oracle Big Data Docs
D+
D
DF
1.3 = 65 ~ 69
1.0 = 63 ~ 65
0.7 = 60 ~ 63
0.0 = 0 ~ 59