SEO700 - Big Data Analysis

Outline info
Last revision date 2018-07-20 12:01:46.845
Last review date 2018-07-20 12:02:01.867

Subject Title
Big Data Analysis

Subject Description
Decision makers are being overwhelmed by the amount of information available for collection both on-line and off-line today. And the challenge has become, how to present it cleanly and clearly. Students will be introduced to data modeling using various platforms for analysis. Excel Pivot tables/charts, splicers, and functions will be examined to mine large data sets for insights. Students will also be introduced to additional data visualization tools for added analysis and presentation. Along with data presentation tools and personal skills training. 

Credit Status
1 full credit

Learning Outcomes
Upon successful completion of this subject the student will be able to:

·        Demonstrate an in-depth understanding of data visualization.
·        Demonstrate knowledge of the various visualization data options and their relevance to specific types of data presentation.
·        Apply knowledge of data visualization tools to answer specific presentation challenges.
·        Demonstrate competent knowledge of various presentation tools and techniques.
·        Apply knowledge of visualization techniques to support strategies for effective presentations.
·        Demonstrate effective presentation skills and coordination through a group presentation.  

Cheating and Plagiarism
Each student should be aware of the College's policy regarding Cheating and Plagiarism. Seneca's Academic Policy will be strictly enforced.

To support academic honesty at Seneca College, all work submitted by students may be reviewed for authenticity and originality, utilizing software tools and third party services. Please visit the Academic Honesty site on for further information regarding cheating and plagiarism policies and procedures.

All students and employees have the right to study and work in an environment that is free from discrimination and/or harassment. Language or activities that defeat this objective violate the College Policy on Discrimination/Harassment and shall not be tolerated. Information and assistance are available from the Student Conduct Office at

Accommodation for Students with Disabilities
The College will provide reasonable accommodation to students with disabilities in order to promote academic success. If you require accommodation, contact the Counselling and Disabilities Services Office at ext. 22900 to initiate the process for documenting, assessing and implementing your individual accommodation needs.


Topic Outline
Data Presentation
·        Presentation challenges in today’s marketplace.
·        Tools and techniques for data presentation.
·        Charts and table options.
·        How do we make data readable and exciting for our target audience?
 Pivot Tables and Charts
·        Basic chart and table types.
·        Differences between PivotChart reports and standard charts.
·        Working with source data.
·        Comparing a PivotTable report and a PivotChart report.
·        Using slicers to filter Pivot Tables
Data Visualization
·        Collecting, examining and rendering data.
·        Why is it even more important today to consider visual appearance?
·        Tools for visualization:
-       iCharts
-       Fusion charts
-       Modest maps
-       Pizza pie charts
-       Chartkicks
-       Ember charts
-       Springy           
Presentation Skills
·        Useful presentation skills for the creative.
·        How to present data effectively.
·        Public speaking for data presentation.
·        Visual application tools for presentations.
·        How to be “that presenter” that everyone admires.

Mode of Instruction
The primary mode of learning will be through classroom lecture and instruction. Additional modes of instruction will include class discussions, a group presentation assignment, and question and answer periods. Class participation is critical to success in this course.

Prescribed Texts
The following course material(s) will be provided:

  •  Various current industry articles and resource materials.
  • Reference URLs.
  • Handouts. 

Required Supplies
Note taking materials are required.
USB flash drive.

Promotion Policy

Grading Policy
A+ 90%  to  100%
A 80%  to  89%
B+ 75%  to  79%
B 70%  to  74%
C+ 65%  to  69%
C 60%  to  64%
D+ 55%  to  59%
D 50%  to  54%
F 0%    to  49% (Not a Pass)
EXC Excellent
SAT Satisfactory
UNSAT Unsatisfactory

For further information, see a copy of the Academic Policy, available online ( or at Seneca's Registrar's Offices.

Modes of Evaluation

Project One  20%               
Project Two  20%               
Quiz  10%                           
Final Project  35%               
Final Exam  15%   

This subject is part of the Search Engine Optimization Analyst, Certificate Program. Those students choosing to pursue their Search Engine Optimization Analyst Certificate are required to complete assessment(s). The passing grade for each course is 50%.

Approved by: Denis Gravelle