Here is the study guide for the first exam.
In addition, Sajin will hold an exam review session. Look for email separately.
Department of Management Information Systems, Temple University
Here is the study guide for the first exam.
In addition, Sajin will hold an exam review session. Look for email separately.
1. Read
2. Take quiz
3. Do assignment 1 due to me 3 pm Sept. 29. Also note that the data set is different than the in-class exercise we did. Assignment 1: Tableau (Covid cases spreadsheet)
4. Check out some tools and how-tos on visualization. There are several ‘how to’ articles on how to tell a story with data, just google ‘telling stories with data’:
https://www.google.com/search?q=telling+stories+with+data
They all tell pretty much the same story, so you can choose the one that works for you.
Differences between infographics and data visualizations are discussed in these two posts:
https://www.statsilk.com/blog/real-difference-between-infographics-and-data-visualizations
https://killervisualstrategies.com/blog/difference-between-infographics-data-visualization.html
We use Piktochart to create an infographic on MIS0855, but there a numerous other web-based tools available:
https://www.creativebloq.com/infographic/tools-2131971
5. Remember that week 6 is exam week and we’ll meet on Canvas with exam available at 5:30 pm. We’ll have a review in class and Sajin will have one separately. Here’s the study guide of what to know.
Read
2. Take quiz
3. Reminder Tableau extra credit due to me Sept 25. This is the week we’ll be working with it.
4. Read the materials and look over in class and assignment 1, which is due to my inbox 3 p.m. Friday Sept. 29.
Bonus:
1. Read the following:
2. Take the quiz due before next class start.
3. Download Tableau and do extra credit.
4. Look over in-class work for week ahead (see schedule).
Bonus reads…
An old but still relevant TED talk by Eli Pariser on how the web is being inconspicuously personalized for individual tastes creating bubbles of like-minded people.…and its critique…and a more recent take on the topic.
In addition…
We will discuss open data sets this week. Aside from what’s in readings and the class materials here are some others:
In addition take 2…
We will be talking about visualizations that are scheduled for Week 4. The idea here is to work ahead a bit so the following week is spent on Tableau hands on (in class and assignment 1) the entire session.
Note: This extra credit is due to me via email Sept. 24.
On your Temple portal, you have access to a service called LinkedIn Learning.
In either case, we are going to skip around a bit in the training to get you acquainted with it. It’ll will come in handy later. Once you’re in LinkedIn, you create a quick profile and search for Tableau. Here’s a popular course to use.
There’s also a broad overview that’s popular, but less hands on.
Another option you could use is Tableau’s training videos here.
Instructions:
Basically it’s watch 3 of those Tableau videos in that second part (starting with the joining data). Get me a screen shot of the video and 3 bullets about what’s in the video.
The extra credit is 1 point tacked on to your final grade.
Go with:
That should get you enough info to digest a bit of part 5 and 6. Those areas will be in the in-class assignment and first assignment.
Here’s a primer for week 2.
1. Read:
2. Then take quiz.
3. Look over these data science terms that’ll be handy (2 minute read).
4. Download Tableau and do extra credit (see post on community site and your email for the product key).
5. Look over in-class work for week ahead (see schedule).
This course uses Tableau a good bit. You can get a full copy of the Tableau software – PC or Mac – for free. The key you’ll need to activate is an email I sent.
To request a free copy of the software:
Tableau’s site has a series of quick start guides and video-based training. If you want to do something that we don’t cover in class, check there.
MODULE 1
Session 1
Decks
Exercise
Session 2
Readings
Decks
Exercises
Session 3
Decks
Readings
Bonus read
Exercises
Session 4 (we will use this class for one exercise and first assignment)
Exercise
Readings
Session 5
Decks
Readings
Bonus read:
Exercises
Session 6
Exam 1
Session 7
Readings
Decks
Exercises
Session 8
Readings
Decks:
Exercises:
Session 9
Readings
Decks
Exercise
Session 10
Exam 2
Session 11
Readings
Decks:
Exercises:
Session 12
Readings
Decks:
Exercise:
Session 13
Readings
Decks
Exercises
We are all drowning in data, and so is your future employer. Data pours in from sources as diverse as social media, customer loyalty programs, weather stations, smartphones, and credit card purchases. How can you make sense of it all? Those that can turn raw data into insight will be tomorrow’s decision-makers; those that can solve problems and communicate using data will be tomorrow’s leaders. This course will teach you how to harness the power of data by mastering the ways it is stored, organized, and analyzed to enable better decisions. You will get hands-on experience by solving problems using a variety of powerful, computer-based data tools virtually every organization uses. You will also learn to make more impactful and persuasive presentations by learning the key principles of presenting data visually.
It’s also worth noting that data science and literacy will apply to every profession. In fact, data science is forcing more integration between various fields and careers.
The schedule will show you the cadence of the course
Here’s the syllabus (you’ll need to be logged into your Temple account)