Instructor:	George Wyner
Email:	wynerge@bc.edu
Twitter:	@geowyn
Voice:	617-733-6517
Office:	Fulton 254D (@Fulton254D)
Office Hours:	Open office hours from 3-4:30 pm each class day.
Teaching Assistants:	Erin Ballengee (ballener@bc.edu) Daewoo Jeong (jeongdb@bc.edu) Mercedes Kephart (kepharme@bc.edu)
TA Office Hours:	Monday – Thursday afternoons (Fulton 413) – check http://bit.ly/cat19oh

Note: You can also download a pdf version of this syllabus.

Note: Tableau's data visualization software is provided through the Tableau for Teaching program.

Thanks to Lucidchart for making their charting software available to the class!

Overview

Data has become an ever more powerful source of competitive advantage for modern enterprises.  New technologies and business practices have led to an “orders of magnitude” change in the amount of data available for analysis, as well as to techniques, often referred to as analyticsor business intelligence, which are now available to derive meaning from that data.  The term “big data” refers to the sometimes surprising implications emerging from these changes in both the scale and type of data available to analyze. The Big Data Module is intended to provide managers, leaders, entrepreneurs, and knowledge workers in general with a deeper understanding of how data can be structured, captured, and queried in order to support decision-making, process and product innovation, and strategic insight. 

Learning Objectives

In this course students will:

• Develop insight into data as a source of advantage and insight by exploring some current examples of how data has been put to such use, with a special focus on big data examples.
• Gain a working knowledge of the key concepts and terms in use in the world of big data and business intelligence.
• Learn to design a database and to describe the resulting data model using Entity Relationship Diagrams.
• Gain insight into data by querying databases using SQL.
• Explore data visualization using Tableau.
• Understand the process by which an analytics team develops and executes an analytics initiative, using the CRISP-DM industry standard as a point of reference

Course Website

The course website is hosted here on Canvas. This site includes an updated version of the course schedule along with detailed directions on how to complete and submit all course assignments.

Textbook

There is one required book for the class, which was handed out at the start of Catalyst. If you didn’t get your copy or it went missing, please let me know!

Sam’s Teach Yourself SQL in 10 Minutes, Fourth Edition by Ben Forta.  Sams, 2013.  ISBN 9780672336072

The textbook will also be on reserve at the O’Neill Library and is available electronically via the online course reserves.

Online Readings

In addition to the textbooks, I will be assigning several online readings (links will be posted on Canvas).

Grading

The module grade will be based on a set of four exercises each of which is worth 25% of the module grade. There are no quizzes or examinations for this module.

About the Exercises

Exercises serve a few purposes in the Big Data module:

To give you feedback about whether you are understanding the concepts in advance of class discussion and to help you pinpoint where you need clarification. 

To give you a chance to apply the techniques you are learning in class.  Learning data skills requires you to try things for yourself. Doing the exercises is where most of the learning actually happens.  You can't fully learn this stuff by taking notes in a lecture and you need to wrestle with the skills to master them.  

Submit (at least) the first part of each exercise before class.  You can resubmit later.

What we do in class depends on everyone having engaged with the topics in advance.  For this reason, it is essential that you try each exercise in advance of class and submit your work before class (which I am guessing means the night before unless you are an early riser).  This allows me to look at your work to assess how best to approach that day's session.  This also ensures that you are aware of any issues you need clarified so you can get the most out of our classroom time.

To prepare for an exercise you will typically be asked to watch one or more brief videos and do some reading. 

You are welcome to work in groups on these exercises and to also seek out help at office hours in advance of class.  Working with others can be a great way to learn these skills.  Just be sure that you own the work you submit.  Example: you had a hard time with a certain SQL query. Working together, one of your classmates came up with something that worked.  You actually enter the same query.  That is ok (in this class) but make sure you run it on your computer. Make sure you understand why and how it works.  Make one little change to make it yours.  This last is a key to your learning.  You can and should own this material!

It is not essential to finish an exercise entirely before class.  Some questions are intended to be more challenging and take more time and you may wish to hold off on those until after we have gone over material in class. Note that the starred (*) questions are actually for extra credit. You can get a perfect score without doing them, but they are worth a look and will help you to go a little further with your SQL skills. 

Go as far as you can and submit what you have.  You will be able to resubmit exercises as many times as you want until Tuesday, July 16th, and your final grade on each exercise will be the highest grade you received.

Expectations

Expect the course to be challenging and fun.

Please show up on time and be prepared to actively participate. Arriving late is a disruption.

Use of Laptops and Mobile Devices

We will be using our laptops for hands on exercises in almost every class.  Please bring your laptop if possible.  If, for whatever reason, you are not able to bring your laptop to class you can look on with someone else.

While we will make use of laptops in class, as you are well aware, laptops can be a tremendous distraction in a classroom setting.  Our classroom discussions will be intellectually challenging, and it goes without saying that the Internet offers many tempting escapes from this level of focus.  Therefore, classroom policy is that laptops are to be closed except when doing an in-class exercise, taking notes, or following along with an example.  If you do not absolutely need your laptop, I suggest you keep it closed.  Cell phones and tablets should be silenced and set aside as well (unless you are using your mobile device as a “laptop”). Much as I hate being the “device police,” I reserve the right to ask us all to close our devices if needed to get refocused on the topic at hand.

Academic Integrity

In this course our learning process will be highly collaborative, but be sure that individual assignments represent your own work. Please refer to BC’s academic integrity policy for further information:  http://www.bc.edu/offices/stserv/academic/integrity.html.

Disability Services

If you are a student with a documented disability seeking reasonable accommodations in this course, please contact Kathy Duggan, (617) 552-8093, dugganka@bc.edu, at the Connors Family Learning Center regarding learning disabilities and ADHD, or Paulette Durrett, (617) 552-3470, paulette.durrett@bc.edu, in the Disability Services Office regarding all other types of disabilities, including temporary disabilities. Advance notice and appropriate documentation are required for accommodations.