Course Syllabus

*** Note that the official course syllabus is maintained in the course Canvas site. ***

Overview

This course covers the fundamental technical and organizational concepts and challenges related to the development of Business Intelligence Systems, a key component crucial to the competitiveness of a wide range of organizations.  Topics covered include: data profiling, dimensional data modeling, data transformation, metadata systems, data governance, data delivery options, and an overview of emerging technologies in this space.  Course is comprised of interactive lectures, work/lab sessions, and a substantial team project.

Learning Outcomes

• A core understanding of Business Intelligence and Data Warehouse design, with a focus on dimensional data modeling, and industry accepted practices.
• How to use BI/DW techniques to enable data informed decision making.
• An understanding of current products and product classes and how they are used in conjunction to support an organization’s information needs.
• Hands on experience developing a working Proof of Concept BI solution using industry leading BI/DW products.
• An understanding of the Business Intelligence, Data Warehouse, and Data Analytics technologies used in modern enterprise data solutions and how these systems are used to solve various data challenges.

Meeting Times and Locations:

Tuesday 10:10-11:25 AM at TBD

Thursday 10:10-11:25 AM at TBD

Friday Two Discussion Sections:

10:10-11:00 at TBD

11:15-12:05 at TBD

Contacts:

Instructor:  Jeff Christen

Email:  jrc42@cornell.edu

Office Hours:  Friday 9:00-10:00 AM at Gates 231

TA: TBD

Readings

Course Textbook: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling (by Ralph Kimball and Margy Ross), Third Edition, John Wiley & Sons, Inc., 2013 (ISBN: 978-1-118-53080-1).

This book is available hardcopy from Amazon and other sources.

Additional readings will be available through Blackboard.

Also Required:  An iClicker device or the REEF Polling application.  Please see below for details.

Software

Tableau’s data visualization software is provided through the Tableau for Teaching program. www.tableau.com/data-visualization-software

WhereScape RED, Data Warehouse Automation tool, is being provided by www.wherescape.com

Dell Boomi, Integration Platform as a Service, is being provided by boomi.com

The virtual desktops and databases are being provided by Amazon Web Services aws.amazon.com

Policies

Attendance and Participation

Attendance: Although attendance will not be taken, it is highly encouraged.  Fourteen percent of the student’s grade is based on attendance (via Blackboard and Clicker activity) and participation in class discussions.  The concept quizzes will also be taken in class and cover material from class lectures.  There is some flexibility built into the class regarding quizzes and assignments.  You can throw out your lowest two quiz scores and your lowest individual assignment score. This should give you enough flexibility to plan for interviews, religious holidays, unexpected sicknesses, family emergencies, etc.

Participation: Substantial time in class will be set for small-group and class-wide discussion. You are expected to actively participate in, contribute to, and enrich these discussions. Students may be called on to summarize the major arguments, strengths, weaknesses, or problems, in the course content being discussed. The instructor will evaluate at the end of the semester the quality and quantity of your contribution to small-group and class-wide discussions.

Laptops and phones in the classroom

You are encouraged to use your laptop/tablet to take class notes, refer to course materials, or augment the class discussions. A laptop/tablet is required for the in class quizzes. Having your laptop/tablet open, however, risks being distracted by activities other than the class, which are considered disrespectful to the other students and the teaching staff. If we notice that your device is distracting you from being actively present and participating in class, we will ask you to put it away. Phones should be silenced and put away at all times.

Late Submission

All assignments are due at the beginning of the class on the day that they are due. All assignments must be submitted via Blackboard.  Late assignments will be strictly penalized. Exceptional circumstances will be considered only if discussed with the instructor in advance.

Late assignments will have points deducted as follows: -20% Up to 24 hours late: -50% Up to 48 hours late: -100% More than 48 hours late. Note that you may throw out your lowest individual assignment grade.

Academic Integrity

Academic integrity is crucial to your personal scholarly identity. Your rights and responsibilities in this area are outlined in the Cornell University Code of Academic Integrity http://cuinfo.cornell.edu/aic.cfm.

Violations of the code of conduct include but are not limited to:

• Submitting work in this class that has also been submitted for a grade in another course without prior permission of both instructors.
• Using, obtaining, or providing unauthorized assistance on papers or any other academic work. All outside assistance should be reported, and the work of others should be properly cited.
• Misrepresenting another person’s work as your own. This means presenting somebody else’s words or ideas without proper attribution, which is considered plagiarism. Proper attribution includes quotation marks and page numbers for any words taken directly from any piece of another author’s work, and/ or a citation when you have paraphrased or summarized somebody else’s work. Sources need not be published to be cited; any document that you use as a source that you are not the sole author of must be cited or attributed in this way. If you have any questions or concerns about how to attribute or whether a source must be cited, please ask for clarification in advance. Plagiarism will not be tolerated and will be strictly sanctioned. More information is available at http://plagiarism.arts.cornell.edu/.

You are responsible for obeying the Code of Academic Integrity. Ignorance of the code is not an excuse. Academic integrity is a serious matter and will be treated as such.

Accommodations for Students with Disabilities

If you think you need an accommodation for a disability, please let me know at your earliest convenience. Some aspects of this course, the assignments, the in-class activities, and the way we teach may be modified to facilitate your participation and progress. It is Cornell policy to provide reasonable accommodations to students who have a documented disability (e.g., physical, learning, psychiatric, vision, hearing, or systemic) that may affect their ability to participate in course activities or to meet course requirements. Students with disabilities are encouraged to contact Student Disability Services and their instructors for a confidential discussion of their individual need for academic accommodations. Student Disability Services is located in 420 CCC. Staff can be reached by calling 607-254-4545.

Grading

Grading Scale

The following scale will be used in converting numeric scores to letter grades in this course.

Team Project

The course contains a substantial team project where teams will gather business process requirements, develop dimensional models, use business intelligence tools to instantiate and populate the data model, and finally build dashboards to provide visual representation of the data.  The teams will present their projects to the class and customers at the end of the semester.

Team Selection and Project assignment

Teams of 4-5 members will be assigned by instructor.  Teams will be assigned to one of several projects working with de-identified data from Cornell systems.

Project Deliverables

Teams will report project status regularly to class and customers. Key deliverables include:

• Project plan
• Requirements & Logical Dimensional Model
• Physical Data Model with populated data
• Data Visualizations
• team ePortfolio
• short presentation to client