Laurel Miller

I was really looking forward to working in a professional environment at Cross America. I knew that I would be able to expand my knowledge in business by actually being in a workplace/office opposed to a classroom or retail store. I realized that people working in my office were generally laid back and cool people. I think some classes paint the professional world as uptight and always formal, but this does not seem to always be the case. I learned to chat about everyday things with my superiors and co-workers in addition to discussing work. It was nice to actually be contributing to a company. Classes do not have a real world impact like working an internship does, and I liked that what I was doing mattered to the economy.

The one thing that you can never learn unless you are in the work environment is that you don’t always get recognized for every effort you make. Unlike in the classroom where you always get a grade as a reward for your hard work, in a professional setting you don’t always get that recognition. Sometimes even mid-project, the whole thing is cancelled or whatever you worked on is not even used and is thrown in the trash. The lesson is to get used to it, know that your work is valuable and keep getting better at your job.

Throughout my experience, I have learned that many tasks aren’t as simple with a direct answer. Many tasks required me to reach out to various members in order to retrieve data and get specific perspectives. These tasks are best performed through communication and working with others as a team. Next, we aren’t always given tasks we have done before, sometimes we are given new assignments that require us to learn new skills in order to achieve them. Next, time is another important thing to keep in mind, it is necessary to prioritize tasks depending on what is needed and when. Deadlines get pushed around a lot so you have to be ready to work on different projects at the same time or shifting between projects based on priority. Finally, the biggest difference between the textbook and actual experience is when you complete a project on the job it feels a lot better to accomplish knowing that you made a difference in a process or an actual outcome within a company.

In my internship something I learned is to get questions answered sometimes I had to be persistent. To solve problems it was not as simple as walking into office hours or asking a question during class. I had to understand first who would be able to help me and what I specifically needed from them. In the first few weeks of my internship I would go to meetings and leave realizing no one really gave me what I wanted. So I learned to have specific questions ready and different way to ask these questions. Most employees do not care about interns, but throughout the summer I learned how to make people value my time so I could complete tasks. This persistence is not something I could have learned in the class room.

Throughout my internship I have learned a lot of technical skills and soft skills that you cannot just learn in a classroom. Some of the technical skills I have learned are performing test execution audits and setting up databases in MS-Access. Audits would be very hard to teach effectively in class because its really something that you need to deal with real testers and situations for a period of time in order to learn. Creating databases in MS-Access you can learn to an extent in class but it was so much different doing it in the business world where many of your requirements are not ideal and theres no answer in a textbook to your specific problem, its a lot of learning on your own through trial and error. Some of the soft skills I have learned are effective communication, determining priority between multiple projects, and being a team player. For me working on the IT Governance team has provided an interesting team-environment where I work with QA, Change Management and Compliance daily and each group has different skill sets and needs. So determine how to communicate with each individual, who to help first and how to work everyone has been essential.

Throughout my internship as a software developer I have learned different coding languages and have learned to research on the web. In school everything is set up and we learn php as our main language. In the beginning of the project I was in, people were debating which language to develop in. Our team decided to code in a new rising coding language. I also became a better developer by learning how to research on the web. I have learned which key word to use when looking for different pre-written code. Also getting the experience in the working environment was something I was not able to pick up at school. Working in an open area with co workers right next to me was not a setting I have worked in.

The main skills I developed over my internship that weren’t learned in the classroom dealt with professional communication, and more specifically email etiquette. At Pfizer, the majority of people I interacted with were at least twice as old as me, so there was certainly a learning curve on how to effectively communicate with them in a professional manner. When I first started there, I would spend a lot of time editing and revising my emails in order to come off professionally and while it seemed tedious at first, it truly paid off. My sponsor and other colleagues took note of my email skills, and would frequently come to me to distribute large emails to members of the organization. While this may seem like a small thing, it was rewarding that higher-ups on my team noticed the effort I put in and this ultimately helped me get my name out there at Pfizer.

One of the many things I learned at my internship over the summer that I could not learn in the classroom is the importance of asking questions. During meetings with stakeholders or project sponsors I learned it was vital to ask questions to really dig down to the core of the problem or issue at hand. I also learned the importance of building relationships with those you work with. This is important so whenever you come to a roadblock or need help you can reach out to those you’ve built these relationships with, and they can help you with any issues. These two key learnings were vital throughout my internship at BD.

Facebook is the online data-driven service that I use most frequently. For Facebook, each row of the spreadsheet would represent a different person. The first column could show the first name of a person; the second column shows the middle name, and the third column shows the last name.. That way you could count how many people have similar names. Another column could show the number of friends a person has while the next column could show the number of photos the person has. Other potential columns include: number of posts, number of private messages sent/received, number of liked pages, high school name, college name, etc.

One data-driven service that I use quite frequently is Instagram. The rows would represent different Instagram accounts. Some of the columns would include: the person’s user name, the number of pictures, the number of followers, the number of people followed, average likes per picture, and the number of tagged photos.

One data-driven service that I use at work is HEDWIG. It is a service used by residence halls to log packages for students. One row could represent a student’s name or a package. The information in the columns would include a student’s TUID and room number. For the package the columns would include the carrier, where it’s shipping from, the date it was delivered, and the bar code we need to scan.

The data-driven service I use the most regularly is Blackboard. If I want to store the data in the spreadsheet,
1st row: Name of the Subject and subject code
2nd row: Name of Professor
3rd row: The name of the file(assignment) I uploaded on the blackboard
4th row: The date I uploaded my file
5th row: the score of each assignment
The other rows: The content of the assignment, The magnitude of the assignment(how important it is in %), The type of the file(ppt, word, pdf)
By using this spreadsheet, I can know how many files I uploaded in a certain period(1 day, 1 week, 1month), the average of my score, which subject has the most assignments and so on.

I use GroupMe, a group message app, very often. It would be interesting to break down everyone’s individual groupme data. One column would be name of the person, one would be how many groups they are a part of, one could be how many messages they send on average each day.

A data-driven service I use frequently is something called coriscahockey. Corsica hockey is a data base that shows detailed advance hockey statistics. A spreadsheet that would contain the data of this service would have rows such as: player name, player position, player team, and each individual row for different player statistics.

A data-driven service I use regularly is an app that logs my study hours. Each row could represent a week while the columns would include avg. study hours per day, study location, and how many hours left until the user reaches his or her weekly goal for hours studying.

One data driven service that I use regularly is blackboard. A row on a spreadsheet could represent each course that I’m taking. The different columns in the spreadsheet could contain information about the professor of the course, the data and time of the class, and different assignments for the class, as well as my grades on those assignments.

A data driven service that I use regularly is Apple Music. A row in the spreadsheet could represent each artist in Apple Music. The columns in the spreadsheet can be how many songs, how many albums, genre(s), rankings (ie #3 on the pop charts) and also how many total streams they have gotten.

I use Spotify everyday. If I wanted to analyze the data derived from this app, I would be most inclined to study the artists I listen to most often. Thus, each row could represent my 10 most listened-to artists. A column could be the song or album of that artist I listen to the most.

A data driven site/app that I use almost everyday is Apple music. If this data was transformed into a spreadsheet it would include things like genre, name of playlist, artist in the columns. Then in the rows it would include the name of the song.

Instagram is a data driven app that I use everyday. If the data was transformed into a spreadsheet it would be based off each user’s page. The row would be each Instagram user’s page and the columns would be based off the number of followers the page has, the posts of the user, as well as the likes and comments they get on each post.

I use Blackboard everyday as a data driven app. The data if made into a spreadsheet would have my classes, teachers, and grade in the columns. In the rows would be the full name of the class, who teachers that class, and the specific grade I have in that class.

A data-driven app I use on a regular basis is SnapChat. The row would contain the individual’s username, in the columns there would be the number of snaps they send in a day, how many streaks do they have, how many snap points they have, the number of snaps on their snap story, and the number of users they have on their “Best Friends” list.

A data-driven app I use everyday is Spotify. If Spotify’s data were to be transformed into a spreadsheet, it would report song titles, artists, albums, and the type of genre the song falls under. The row could represent its rating in your playlist or your most recent songs listened too.

A data-driven source I use every day is my Scottrade brokerage account. I use Scottrade to invest in many different stocks as well as researching other stock quotes for future stock purchases. Some columns I use in my excel spreadsheet to track my investments are stock price, stock quantity, gain/loss, dividend distributions per share, and total gain/loss. Each row lists the company’s name and ticker symbol.

I frequently use Spotify. A good way to organize a Spotify spreadsheet would be to make each row its own song. Columns would each be details about the song. For example, these could be things like artist, featured artist, producer, name of the song, duration, release date, album, genre, number of plays, stream or download etc.

Canvas is a data driven source that I use often. If it were in a spreadsheet, the first column could list the class, and the following columns could contain other information pertinent to each one. For example, due dates, grades, and assignments could all be listed in the following columns. This would be a great way of organizing an academic schedule.

A data driven service that I frequently use is Amazon. If I wanted to analyze Amazon data in a csv format, I would have the product name, product number, price list, reviews using 1-5 number. From this data, I would be able to analyze if certain products are most frequently purchased by customers.

A data driven service I would use would be Twitter. My data I would be storing would be, the time majority people tweet on the East Coast, the average likes or retweets they receive on post, the area in which the tweet the most. From this data I would be able to determine which States have the most twitter activity.

A data driven service that I would like to see in a spreadsheet would be Amazon. I would have rows for the product name, product description, and company that makes it. For columns I would like to see the price of the product, the SKU number, average star rating of the total reviews, and number of times that the product has been purchased. By having it in this format, I believe that the information would be keep in a clean matter, allowing the data to be easy to follow.

I use GrubHub service often times and I believe if I’d store their massive data in a spreadsheet would be:

Column 1: restaurant ID
Column 2: User ID
Column 3: Restaurant Name
Column 4: Restaurant Location by Zipcode
Column 5: Dynamic User ID Location
Column 6: OrderID

All the rows would be values of each specific column.

A data service I use regularly is Twitter. A spreadsheet for Twitter would include rows for the profile picture, tweets, likes, retweets, followers, and columns would include the number of tweets, likes, retweets and followers.

I use the ESPN app often to check scores of games which I’m interested in and check out specific stats of players I like. To make a spreadsheet I could make rows of the teams, players, positions, etc. and columns filled with things such as points per game, blocks, points allowed, passing yards, etc.. You could filter this by being able to minimize to specific positions of whichever league you’re looking at or on a certain team as well.

Twitter is a data driven service used daily by millions of people. Twitter stores posted tweets. A tweet would be a row in the spreadsheet. The columns in the spreadsheet would be the name of the person, the date, the time, and the number of characters.

Uber is a data driven service that many people use regularly. Uber stores uber rides. In a spreadsheet, a row would be an individual Uber ride and the columns would be how long the Uber ride was, the distance, the traffic involved, and the number of people riding.

Canvas is a data driven service used daily by Temple students. Each row in the spreadsheet would represent classes the student is enrolled in. Some of the data columns would be syllabus, schedule, grades, assignments, and announcements.

Google Drive is a file storage service developed by Google. Google Drive stores all kinds of files including Word documents and Powerpoints and allows users to collaborate on documents. A row in Google Drive’s database would be information on an individual file. Columns would include metadata on the file including the upload date, contributors, name, last edit date, size, and the actual data included in the file.

The grade center in Blackboard records the grades earned by each student. If put in to an Excel spreadsheet, the row would be the grade received, and the columns would include what class the grade was for, how heavily it is weighted overall, what kind of grade it was (quiz, exam, homework, etc.), who the professor of the class is, and date the grade was posted.

The data driven service I use everyday would have to be Canvas. If I were to make an Excel spreadsheet for the information that is stored on Canvas the rows would be all my different classes. The columns would represent professor name, my grades for each class, upcoming assignments, assignments completed, and dates for exams/projects.

Amazon stores information about different products for consumers to search and choose from. If the information was to go on a spreadsheet, the columns would be: Product name, Category, Price, Seller, Rating, Number Purchased.

A data driven service I use everyday would be snapchat since it’s used by millions of users every second. If I were to store the data for snapchat in a spreadsheet what each column in the spreadsheet represent would be the time I posted my snapchat story, how many people viewed it, and how many responded to it. The rows would be individual users I sent a snap too or users I got a snapchat from.

A data driven source I used regularly is Twitter. If data from Twitter were put into a spreadsheet, a row would be an individual’s Twitter handle, and the columns would be things like the individual’s total number of tweets, number of tweets on a specific day (or over a period of time), number of retweets, number of likes, number of media posted, number of followers, number of people the individual is following. Or, a row would be an individual tweet, and the columns could be the Twitter handle of the person who made the tweet, the number of characters, the time and date posted, how many likes and retweets the tweet got, and how many times the tweet was viewed.

Amazon is a data driven source used regularly by millions of people. If i were to use it and put it in a spreadsheet, some of the columns of data ratings would include product name, average rating, price, manufacturer and category. I could also put average shipping and handling if that is done through the individual seller or amazon and is a fixed price.

Instagram is a website and app for sharing photos and videos. One row could be for pictures and another row could be for videos posted. The columns could be how many likes, comments, and the date it was posted.

UberEats is an app I use, which is a data driven source. Rows would be location, restaurant, name of food, order time, delivery, and delivery driver. Columns would likes, dislikes, comments, and date.

YouTube is a website/app that millions of people use everyday to view videos about all different kinds of things. In Excel, a row would be a specific video and the columns could be the name of the video, the date posted, the genre of the video (music, sports, travel, etc.), the length of the video, the number of views it has, the number of likes/comments it has, whether the video has ads on it, and the name of the account posting it.

Amazon is an app I am constantly using to buy things on the go. I would put the items bought in the rows and in the columns I would put information such as: price, amount of time the item remained in the buyers cart, date of purchase, the delivery time, information on whether or not the buyer wrote a review, and if the item was kept or returned.

One of a data-driven service is the Linkedin, a professional social networking site for business community. Some of the column would be the LinkedinID, Experience, Skills, Accomplishments, Place of work/ Study, and Contact Information. The rows would be information of each person that create a profile in Linkedin.

Amazon is a service with inordinate amounts of data behind the scenes. I think if I had the data for Amazon it would likely include product names, price, customer rating, a short description, and seller. If the data was made available things like number of sales and number of returns or complaints would be extremely helpful to amazon and its sellers; with that information they could fix issues with their products and bolster their sales numbers.

An example of a data-driven service that I use regularly would be Amazon. If I were to store the data (of my purchases) for that service in a spreadsheet, the information would be formatted by rows = list of products and columns = product name, order date, shipped date, delivered date, delivery location, price, and average customer rating. We could also add a column titled “type of product.” This would be a cool way to analyze my shopping patterns of either house supplies, kitchen supplies, office supplies, etc.

A data driven service I use everyday is my Citi credit card application and the Citi credit card online banking. If I wanted to integrate the data into Microsoft Excel, the rows would be categories of the purchases. For example, the rows would be named entertainment, merchandise, restaurants, organizations, and vehicle services. On the other hands the columns would represent the time period such as November 2017, October 2017, September 1017, and so on. The cells would be the total amount of money spent on the purchase category in accordance with the time period accrued.

Netflix is a data-driven service that I use often. If I wanted to create a spreadsheet to store data each row would be the name of a movie/show and some examples of the columns would include genre, length, rating, actors, director, and Netflix category.

Snapchat is an example of a data-driven service that I use every single day. If I created a spreadsheet to show Snapchat’s data, I would make the rows be individual users. For the columns, I would put their snap score, how many snapchats they send per day, what filters they used, and how long their streaks are with other people/their highest snap streak.

Instagram is a data-driven service that I use everyday. If I wanted to store information into an Excel spreadsheet, I could do multiple things. One spreadsheet could include making the rows, the individual account’s username. In the columns, I could put the number of followers the account has, the number they are following, how many pictures have they posted, how many likes have they received, the average number of likes per a photo, and number of photos they have liked.

One data- driven service is black board. If I put blackboard’s data into a spreadsheet I would have many different columns. One would be courses so that the data in the other columns can be organized in rows by course. Then it would be assignments and grades. All the data would be filtered by courses.

rotten tomatoes stores movie reviews. the row will be short reviews, and columns will be the name of the movies, how many stars the movie got (0-5), the year of the movie produced, names of the director and main actors, which type the movie is, and who writes the reviews.

A data driven service that I use on a regular basis would be YouTube. Some examples of columns could be the YouTuber’s username, genre of video, and what is trending. The rows would include the information of these categories or a potential link to any given video.

An example of a data-driven service I use regularly is my bank account. And the spreadsheet would have different columns. That is my spendings like cash and different categories like food, entertainment, and transportation.

A data driven service that I use regularly is Facebook. On a spread sheet, each individual row would probably be a facebook page. Each column would then be an attribute of that facebook page. There are probably over 100 collumns per facebook page, however some of the columns would be, an Indentification number, the Page name, page type, Date created, Login email, login password, gender, description, etc.

One data driven service I use regularly is Amazon. This online retail site keeps record of every purchase I make. In a spread sheet the item I purchase would be in rows and the columns would include price, order number, seller information, and my method of payment.

I use Blackboard just about everyday, even if it is just to check if any grades have been entered, which they usually haven’t. If it were to be converted to excel, some rows could be grades, upcoming assignments and and the email address for the professor. The columns in this sheet would be the classes themselves, and with those rows showing everything about the classes that is necessary.

A data driven app that I use regularly is Serato, my personal database for music. If I were to make an Excel spreadsheet for the information that is stored on Serato the rows would be the different crates I’ve made. The columns would be for the song name, BPM (beats per measure), artist, album, and the year that the song came out.

A data-driven service that I use regularly is blackboard. The rows would represent each individual class. There could be a lot of columns. One could be the professor. Another would be the name of the course. The CRN for the course could be used as the id, or you could just assign an id to class. You could also have a column for my grade in the course. Lastly, there could be a column that is just a description of the course.

Ebay is a data driven source used for online shopping. Columns would be product type/category, price, sales, etc and rows would be product names, quantitative data, etc. Buying behavior and trends can be identified from the data to gain key marketing data for better overall market insights. This can include prediction of trends, pricing, promotion, etc.

A data driven service I use frequently is Amazon for online shopping. The row would be my my order number. And some columns could be the items I ordered, the price I paid, method of payment, shipping address, company the product is coming from.

A data-driven source that I use almost every day is Amazon. I buy multiple items from this company a week. if I was to put my order history into a spreadsheet I would put the products I bought into the rows and for the columns, I would put in details such as price, customer rating, and the category the product falls in and its shipping and arrival dates.

I use Twitter a lot and if the data used from Twitter was placed into a spread sheet the rows would most likely consist of trending topics, tweets per day, number of total tweets, and most used hashtags.

Twitter is a data driven service that I use regularly. If I put twitter data into a spreadsheet, one row could represent tweets that I compose myself. Another row could be tweets that I retweet. Some columns could be the time the tweet was composed, the date the tweet was composed, the number of likes that the tweet received, the number of retweets the tweet received, the amount of comments and some of the most popular ones.

Data Driven Service – Gmail

The columns will store the data like categories

Example:: NAME OF SENDER SUBJECT

The rows will have a more detailed fields following the column so for example

NAME OF SENDER. Subject
Joe MIS weekly questions

Data Driven service : Stats.nba
In an excel spreadsheet, the NBA stats per player would be listed. Player/Team names would be in columns and the individual statistics would be in rows. Statistics used in our previous in class exercise for NCCA such as field goal percentage, etc. An additional row that could be added that wasn’t included in the in class exercise could be forecasts for players in future games.

Instagram is a data driven service that I use everyday. I could have the rows be the usernames. The columns could include things like number of followers, posts, likes, and comments.

DARS is a data-driven service that I regularly visit. Rows could be individual courses, while the columns would consist of all of the descriptive information and student data; these would include fields such as Course Location, Semester/Year, Subject, Final Grade, Grade Point Earned, Number of Attempts.

1. The subject of our group project is “University Data Analysis”.
We feel data from universities is easily accessible because these businesses tend to brag a lot with statistics such as job placement rates, acceptance rates, retention rates, etc. Therefore, an in-depth analysis of such data will be possible and effective.

2. Group members: Dan Moy, Anne Lin, Jeevan Jaganath, Henry Fok

1.) The subject of our group project is about how women’s and men’s professional soccer varies in popularity and why this is the case.
2.) Group members: Caroline Doyle, Graceanne LeNoir, Tom Hess, and Alexa Lessard.

The subject of our project is looking at NBA allstars, like over the past few years, and looking at those allstars measurement at there rookie predraft combine and seeing if certain factors in measurements can predetermine an all star, or at least boost their chances.

Group Members: Myself (Julien Bombara), Sayem Rahman, Kaoi Peixoto, and Nicholas Napolitan

1. Relationship between police positioning with the crime rate
2. Kendall Jones, Devisha Walia, Nalah Clark

1. Our subject will be a comparison between the 2008 Philadelphia Phillies and 2008 Tampa Bay Rays
2. Joseph Benvenuto, Nick Tarducci, Joseph Rovnan, Ryan Stifnell and Will McAndrews

1. Are NFL pocket quarterbacks more successful than NFL running quarterbacks?
2. Alex Brennan, Zachary Kressler, Robert Snyder, Jonathan Ganon

1. Social media trends over time
2. Brianna Morales, Michael Vidra, Grace Stuart, Mariah Tulaney, Hussain Alshola

1. Our subject is Health/Wellness across different neighborhoods in Philadelphia
2. Kacie Rettew, Cassidy Lorenz, Dalton Veight, Nick Thull

1. Our subject will be the comparison between the different type of crimes people are jailed for in Philadelphia.
2. Jose Gil, Chongxin Zhao, Amanda Barnabie, Dmitriy Summovskiy, Justin Waters.

1. Our subject is the success of different Philadelphia stadiums.
2. Briana Vetter, Jillian Thompson, Glen Diener, Josh Ogg

1. For our subject we will be looking at the Indego bike share trips and comparing the usage of the bikes in the summer months compared to the winter months.
2. Danielle Redman, Summer Holmes, Xiaoyu Liang, Hasan Husain

1. Our subject is comparing the in-game performance of the Cleveland cavaliers vs the golden state warriors.
2. Zeke Menke, Bob McPeake, Nadir Munir, Joseph Pavelick

Subject:
Airbnb Data Set
We are going to analyze data about Airbnb’s in different cities and compare the results of the cities each of us choose. Each person will choose one city as there are thousands of rows of data per city.

Group Members:
Nicholas Griffaton
Zach Delphais
Kate Sliwinski

Subject: Which Big 5 Philly School has the Safest Campus?
Members: Vanessa Ioannidi, Zach Burkhardt, Jacqueline McCarrik, and Jeffrey Angstadt

Subject: We will be focusing on the amount of crime that occurs around schools. We will compare the same types of crimes, and look at the different factors that affect the crime rate.
Members: Raghad Ayoub, Rami Aboud, William Wrobel, Luke Reynolds

Subject: Complaints against the Philadelphia Police Department. We are going to analyze the lack of service, abuse, and unprofessional conduct of the department. We will also be analyzing each summary of the event that was filed.

Members: Kieragh McMenamin, Jessie Turner, Bennett Sigourney, Preston Monah, Adam Scalfani.

Subject: We are going to answer the question: Who is the best statistical NFL player to play the quarterback position. We will compare numerous key statistics, such as: QBR, passing yards, interceptions, etc. to answer this question.

Members: James Villani, Brandon Weiss, Noah Clay, and Shabbir Lageli

1. TED Talks datasets, we’re analyzing the most viewed and most favorited Talks of all time? the TED main dataset contains information about all talks including number of views, number of comments, descriptions, speakers and titles dating from 2006 to September 21, 2017.
2. Members:
Jasmine Rogers
Bosung Park
Phoebe Davidson
Hansel Tan
Devon Hill

Subject: Black Friday deals vs. Cyber Monday deals
Members:Tracy Glova, Kayla Cohen, Courtney Wilson, Kourtney Thompson

Article: https://newsroom.intel.com/editorials/intel-power-5g-network-2018-olympic-games/

Explanation: I chose this article because it is about the 2018 Winter Olympics. I always watch both the winter and summer Olympics, so this information is very interesting to me. In the article, the author talks about how they are creating a “foundation for a massive new wave of connected devices and data” as Intel is collaborating with South Korea’s KT Corporation in order to share their advancements with 5G technologies.

Most Female and Male Occupations Since 1950

I found this article very interesting. The author performs an analysis on trends related to occupations in terms of gender. The data is eye opening and shows the progression society has made within gender roles.

People Are Skeptical Of The GOP’s Tax Bill. Can Trump Change Their Minds?

This article is interesting to me because it discusses Trump’s tax bill and I am an accounting major and am doing a project that has to deal with the tax reform. Only 25% of people believe the tax plan is a good idea, but that is pretty good. The 25% of people that think it is a good idea probably know about taxes while the rest may not know or just do not approve of Trump. Also 39% of Americans did not form an opinion yet.

https://www.theguardian.com/environment/2017/sep/26/national-park-plastics-bottled-water-ban
I found a really interesting article pertaining to the environment and how Trump’s reversal of the ban of water bottles in national parks will continue to hurt the environment. There are 331 million people that go and visit the US national parks each year and there are one million plastic bottles sold per minute. That is a lot of people who will come and want to bring water bottled. Because of this idea, the national parks banned the use of water bottles, which saved them 2 million water bottles, which is the equivalent to 419 cubic yards of landfill space. With all of this great information found, Trump reversed the ban 3 months later, leaving the national parks and the environment vulnerable.

https://www.techrepublic.com/article/mobile-data-leak-of-46m-users-could-put-entire-population-of-malaysia-at-risk/

This article is about the recent mobile data leak of 46 million users in Malaysia. The leaked data includes personal user information, ID card numbers, mobile phone numbers, SIM card information, and addresses. The main threat of this data leak is for the affected customers to have social engineering attacks against them where further information could be leaked, or the information could be enough for the criminals to crate fraudulent identities to make online purchases. This is particularly interesting to me as it relates to cyber-security, a field I may decide to work in in the future.

An article I recently read was: https://www.theguardian.com/news/datablog/2017/oct/31/terror-trends-what-are-the-most-common-phobias-among-us-adults. I thought it was only fitting to include it here since Halloween was just a week ago. The article presents data about the most common phobias among adults. As an advertising student, I found this article quite interesting because of the demographical insights they were able to pull from the survey. These insights included “being female, young, and low income increased the risk of developing any of the phobias, while being Asian or Hispanic decreased risk.” I’m easily fascinated by how the mind works and I liked how they were able to gather these conclusions off of a simple survey. Insights like these are what drive successful advertising campaigns.

http://fivethirtyeight.com/features/the-ultimate-halloween-candy-power-ranking/
I found this article, “The Ultimate Halloween Candy Power Ranking” to be very interesting and relevant because Halloween was a few days ago. I thought it was interesting that the collectors of the data split what makes candy most desirable into 9 categories (i.e. chocolate, fruity, contains peanuts, etc.). I thought this was a very cool article to read because it shows that data really is everywhere, and even something as simple as what Halloween candy is the most popular can be analyzed to figure out exactly why people find certain candies more appealing than others.

Days Without a Mass Shooting

I think this article is very interesting and relevant to today. Its about the mass shooting problem in America, that seem to never end. In 2017 there were no more than five days without a mass shooting. The data shows that each circle, sized by total deaths and injuries, represents a mass shooting. A mass shooting is defined as when at least four people are injured or killed in one location, not including the suspect with a firearm. This is an ongoing problem in America because of all the gun control debates, but its deeper than that. This kind of stuff doesn’t happen in other developed Nations like in Western Europe, Asia, and Australia, the problem is America has an obsession with guns. Gun control won’t end it until the culture of the obsession with guns ends.

Percentage of People Who Married, Given Your Age

This article shows is an interactive graph, showing the percentages of people who are married at a certain age, vs those who aren’t married at that age. They also break it down by race, which I thought was interesting because in todays day and age there are a lot of mixed relationships/ marriages. The graph would have been better if it allowed you to mix and match races as well as genders, considering the world we live in now. Other than that I found the article to be interesting and informative to an extent.

http://www.dailyinfographic.com/threat-to-humanity

One thing that I also shared with Elon Musk that we are not fascinated with the advancement of Artificial Intelligence(AI). For me, human should always be the one that rule the earth. If, A.I managed to take advantage on the all available data on earth about us, together with their super analytics capabilities, doomsday might be looming.

People Are Skeptical Of The GOP’s Tax Bill. Can Trump Change Their Minds?

I find this article extremely interesting because if this tax bill is passed, it would be the biggest reconstruction of the tax system since the 1980’s. This article goes in depth on the polling numbers in regards of how people view this potential bill passing into legislation. Further in the article they show the approval ratings of President Trump, and also the Democratic advantage over the republicans on the generic congressional ballot which i thought both were very interesting.

https://sports.yahoo.com/eagles-now-4th-best-odds-192411317.html
My article has to do with super bowl odds and MVP odds. Right now the Eagles have the 4th best odds at winning the super bowl behind the Patriots, Seahawks, and Packers. Carson Wentz also has high odds of winning MVP this season behind Alex Smith and Tom Brady. I love the Eagles so that is why this data is relevant to me.

https://www.engadget.com/2017/11/07/mobile-phone-data-could-replace-census-questionnaires-in-the-uk/
This article talks about how in the UK, the use of collecting mobile phone data could replace the census questionnaire. The Office of National Statistics collects census reports through paper questionnaires but are also looking into mobile phone data. I think this is very interesting because this is a new way of collecting data. I see a problem with using phone data as the collection process because not everyone has a phone or some people have multiple phones (one for work and one personal).

I chose this article of Biometrics in sports because it is interesting and also similar to the fitbit/insurance reading we did in class. In summary, sports are using the app Whoop, which measures heart rate, sweat, and other factors, that show potential exhaustion in sports. This is a blessing and a curse for sports, because while it can warn of potential dangers, it also limits the amount of playing time for a player, which can cause the star players being forced to come out because of “warning” from the app even if the player wants to stay in, he will be forced out by coaches.

http://variety.com/2017/tv/ratings/sunday-night-football-ratings-1202607733/
As someone who is interested in the sports field, a KPI of how popular the sport is, can be the television ratings that the nationally televised games bring in. I also wrote a paper on declining NFL ratings last year when this trend started, so keeping up to date with the ratings has become somewhat of a hobby of mine. This article pointed out that the most recent Sunday Night Football game hit a season low in ratings, if these trends continue, it could create the panic that the networks had last year.

American Daily Routine

From this article and data set, I found it interesting that the 3 activities those who are employed so with their time is sleep, work, and socializing/leisure/relaxing time. Those who are unemployed spend most of the time sleeping, socializing/leisure/relaxing, and household activities.

Diagnosing the Internet of Things: Predictive Maintenance Through Analytics

This article talks about data analytics and the internet of things. The internet of things is a system where every device that’s part of the business is connected to the internet. One of companies they talk about in the article is Augury. Augury has 35000 devices and growing that institutes the internet of things.

https://www.cnbc.com/2017/10/27/bitcoins-origin-story-remains-shrouded-in-mystery-heres-why-it-matters.html
This article was interesting to me because the creator of bitcoin’s identity is still unknown and the creator essentially owns 5% of the 21 million finite supply of bitcoin. For comparison purposes, the united states holds the most gold reserves in the world at about 8,000 tons, which is a little over 4% while the creator of bitcoin owns 5% of the bitcoin supply valued at around over 5 billion. In other words, the creator of bitcoin has more currency dilution power than the united states has over gold. Dumping more currency in circulation essentially decreases its value and having this unknown identity that owns about 5% of a rapidly appreciation currency can be troublesome in the short term if this person were to dump their stash of bitcoins on the market.

https://www.theguardian.com/news/datablog/2017/oct/31/terror-trends-what-are-the-most-common-phobias-among-us-adults
This article was about the most common phobias among our population. the sample size for the study was 43,093 people. the data was displayed in a table, and also displayed in a graph that is shaped like a mountain because a fear of heights is one of the phobias. The graph showed just the 5 most prevalent ones. I thought this article was interesting because the graph was very appealing, so I thought they did a good job with that display of data. I also thought it was interesting because most people have weird things that creep them out, so it was pretty cool to see some of the most common ones.

https://www.washingtonpost.com/news/the-switch/wp/2017/11/08/equifax-says-it-owns-all-its-data-about-you/?utm_term=.611c3f5a59c7

This article has an extremely interesting take on the Equifax data breach, the dives into why it happened in the first place. I’ve always known that when you submit information for something free in return you are the product so it doesn’t surprise me that Equifax has been making a profit off of all the consumer data they collected through credit karma. What does interest me is that Verison and Yahoo are defending Equifax’s rights to own the data, while this might legally be true I’m concerned about what precedent it sets for future businesses.

If they own are data does this mean they have a right to decide whether or not they want to protect it from potential hacks?
For example, if your identity was stolen from this data breach, does this mean you can’t hold Equifax accountable for not protecting the data you gave voluntarily? Does we forfeit the rights to our own data when we are given something free in return?

This article is about how people can use social media platforms like instagram to make money. The article suggests that people with 3,000 to 10,000 followers can make around 250 US Dollars for one branded post. I found this interesting because I use social media everyday, and while I do not have this many followers on Instagram or Twitter, it is funny to think that having followers can become a career for some people.
http://www.businessinsider.com/inkifi-website-tells-you-how-much-your-instagram-posts-are-worth-2017-11

https://www.theguardian.com/news/datablog/2017/oct/31/terror-trends-what-are-the-most-common-phobias-among-us-adults

According to a survey of over 40,000 Americans, the most common phobias are animals (birds, insects, and others) and heights (mountains, tall buildings, bridges). The researchers found that people most likely to have phobias are young, low-income females and that the average age for developing a phobia is between 9 and 10. Some of the other most common phobias include being in closed spaces, being in/on water, thunderstorms, and traveling.

Mapping happiness

This is a pretty cute chart that is mapping happiness. It shows each state and a smiley face or frowning smiley face. The bigger the smile the happier those people are living in those states. If the face is frowning, most people in that state are more likely to report worse physical and financial health. These people are more likely to be obese, smoke, or have little interest in life.People living in PA are moderately happy. Some of the happiest people come from Texas, Hawaii, Arizona, and Maine. A lot of unhappy people live in Mississippi, Ohio, and Rhode Island.

http://www.propertycasualty360.com/2017/10/26/wearable-technology-discoverable-data
I found this article interesting because it covers how wearable technologies such as smart watches and fitbits can provide data for new uses. For example, in a Canadian court case the claimant provided evidence of requiring disability benefits by presenting data from their fitbit proving they have insomnia. This is interesting because this is a unique way to prove existing health conditions.

Can An NHL Player Finally Score 50 Goals In 50 Games Again?

This article is about how there are only 5 players in the entire NHL history that have scored 50 goals in the first 50 games of the season, and the last to do it were 25 years ago. However, due to data on previous seasons, looking at trends, there’s reason to believe that this year may be the year to break the 25 year curse. Those reasons being several rule changes to hopefully boost the number of goals per game, as well as a low among goaltending that’s the lowest it’s been in almost 10 years. Goalies are just not covering the goals as well this year as previous years. Not to mention superior players that are capable of the milestone, based on their stats thus far. All of this has the potential to break new records, something that the last 25 years of hockey has been missing for decades.

https://www.theguardian.com/us-news/datablog/2017/nov/06/not-your-imagination-mass-shootings-now-happen-more-frequently-in-the-us

This article was written shortly after the tragic shooting at the Texas church. This is a scatter plot that portrays the number of mass shooting, as well as the severity of mass shootings since 1984. What makes this scatter plot effective is that the thickness of each plot represents the severity of the shooting. Therefore, the bigger the shooting, the larger the size of the plot is. The graph shows that mass shootings are becoming both more common and more severe as time goes onI think this is very relevant because it was a tragic event and need to be aware of one of the biggest dangers in this country which is mass shooting.

Can An NHL Player Finally Score 50 Goals In 50 Games Again?

I found this article to be interesting to me because the main question it focus’ on, “Can an NHL Players score 50 goals in 50 games?” I am a big hockey fan so this article caught my eye instantly. The site shows the reader graphs about the top scorers throughout the years and how many goals they got. It is a very hard thing to do and it gives a challenge for the players. Gives detail about the players and compare stats throughout the article.

http://www.newsweek.com/russia-checking-facebook-stores-data-countrys-servers-banning-social-network-705709
I found this article interesting because it deals with the rights of a private company versus the rights of a sovereign nation. Russia wants the company to store data of Russian citizens on servers in Russia rather than outside the country and are currently checking to see if Facebook is compliant with Russian law if Facebook isnt then Russia will ban the website in the country.

http://www.dailyinfographic.com/driverless-rideshare-evolution-of-transport

I found this article really interesting which it talks about the driverless Ubers, so more and more cars without drivers will pick people up and take them wherever they want to go.

American Daily Routine

This article is interesting because it shows how different groups of people spend their time throughout the day. It shows that a majority of females who aren’t look for employment spend their weekdays sleeping from 10pm-8am, doing household activities from 8am-12pm or 4pm-5pm, and socializing, relaxing, and leisure from 1pm-10pm. On the other hand, males who aren’t looking for employment don’t focus on household activities as much as females and spend more time on socializing and leisure activities. It’s interesting to see the variation of things people do through the day depending on whether its a weekday or weekend, if they are male or female, and if the are employed, unemployed, or not looking.

Article: http://flowingdata.com/2017/10/19/american-daily-routine/

This data visualization focuses on different types of activities people do, what time they do it, and the percentage of the activity during all hours of the day. When i first opened the article, i had assumed that it was going to be a little bit more trickier than it was to read and comprehend, but it turns out the data was represented very clearly. All of the activities in the chart are listed on the left side, while the bars are represented in different levels of color to indicate the percentage. Overall, i really like this visualization. I have never seen information represented the way this one is laid out but I think it is very clear. The only thing about it that could be improved is to add more activities to it.

http://results.regattatiming.com/backoffice/webpages/staticRaceResults.jsp?raceId=429 This is the results page from the Princeton Chase regatta about two weeks ago. This is important data to me because my team and I look at this data to see how we compared to other teams that showed up and how teams performed this year versus last year. Race results are always important to look at because we can pull a lot of statistics and data from them.

https://www.cnbc.com/2017/11/08/microsoft-starts-using-linkedin-data-to-help-you-get-a-better-job.html
I think this article is interesting and relevant to me because I use LinkedIn on a daily basis, and for one, I was never aware that Microsoft owns LinkedIn. I also didn’t know that Microsoft has a program called The Resume Assistant, which could be very helpful to me. I think it’s cool that Microsoft uses data from LinkedIn and helps people see different descriptions of the job they’re looking for and the skills necessary for it, too.

Article: http://www.dataversity.net/data-analytics-education-advances-villanova/

This article interested me because it discusses a new program that Villanova University is implementing in the Fall of 2018 to help its accounting students obtain the CPA 150 credit requirement. As an accounting major this is really relevant to me because obtaining 150 credits for the CPA exam is no easy task. The program is called MACDA, which offers 36 credits with classes on Big Data and Data Analytics. The courses are all online, which was done to allow students to allocate more of their time to prepare for the CPA exam. Some courses offered in the program are Data Modeling/Business Intelligence and ERP Systems/Data Analytics.

Cities projected to be under water by 2100

This article describes and graphs what cities it predicts will be under water by 2100. Climate change appears is a real thing and people are still in denial about it, and it only seems to be getting worse. It is estimated that 275 million people will be not be able to live where they do now due to flooding.

https://www.usatoday.com/story/tech/news/2017/11/01/russians-used-facebook-way-other-advertisers-do-tapping-into-its-data-mining-machine/817826001/

This article is about the controversy surrounding the president and Russia’s involvement in our last election. It speaks of how the Russians used the masses the same way advertisers do, by data mining. This is the act of using an algorithm to filter data and taper it to an individual’s preferences. There isn’t much about how or why they did it, but it is an interesting development to the whole story.

The One County In America That Voted In A Landslide For Both Trump And Obama

So this morning Fivethirtyeight put out a new article showing the voting landscape of a county in Iowa. I am really into politics so for me it is really interesting to see the trends and demographics shifts in polling data. The article pointed out that there was only one country in the united states that voted both Obama in 2012 and with Trump in 2016 in land slide victories, and that county was Howard County in northern Iowa. Landslide victories are described as winning the vote by more than 20%. This paints a bigger pitcher on what the country wants from their president. They want change, and Hilary reflected she was not that.

Recently, about two weeks ago, I received an email informing me that I may have been affected by a privacy breach on Equifax. I was granted a free credit report for each of the main three bureaus. The article I read discusses why Equifax even contains some of these peoples information. Supposedly Equifax does not believe that they should have to give up individuals personal information because they “own” it, even though people would prefer to opt out of them storing the information. All in all, Equifax is an ethics battle determining if they should be able to withhold personal data of many Americans who prefer them not to have the data.

https://www.engadget.com/2017/11/27/google-trends-real-time-search-data-news-images-video/
This article highlights a tool Google created in 2015. The program is able to show what people search for on Google in real time using the system’s analytics. Being able to trace and follow trends in an instant, is extremely valuable to companies and media outlets alike.

https://channels.theinnovationenterprise.com/articles/how-has-big-data-shaped-social-media
This article is interesting because it explains how big data influences social media. Obviously the two are connected but it did not occur to me to think about social media in terms of the data being collected from our posts. It’s also interesting to see how it’s changing the business of social media.

Disney-Fox market share

This article is interesting because i didn’t know that disney studio is in the lead with the most movies revenue. Now Disney is trying to make a deal with 21 centry Fox. If deal were to go through, then disney will most likely be the top revenue maker in movie studio since they own other studios too like marvel.

http://www.foxbusiness.com/politics/2017/11/02/trump-s-tax-plan-major-changes.html

This article focuses on the proposed Tax Cuts and Job Act which adds a fourth tax bracket to the economy and no longer touches retirement plans. If this bill were to pass, the average middle-class family would save over $1,000 on taxes each year. I found this article interesting because one of the areas I could potentially end up working in is tax as a CPA. I could potentially do income taxes for individuals or corporations, and both of these groups would be affected by this bill. Corporations could see up to a 15% decrease in the corporate income tax. This bill is relevant to me because of my parents income too; also, I could save money on taxes in the future if this bill passed depending on my income level. Some of the data relevant to this article includes: individual’s names, taxable income, deductions, amount of deductions, number of dependents, amount saved, and more.

http://www.zdnet.com/article/tableau-ge-aviation-partner-on-data-analytics-for-planes/

This article is focusing on the recent partnership between GE, specifically the Aviation department, and Tableau by leveraging their service to visually analyze data to help improve fuel efficiency and customer experience, among other things. It is awesome to see that companies are starting to recognize how useful of a tool Tableau is for their business, and its ability to diagnose business problems/successes an act accordingly to what you find . Being a senior, and having Tableau experience on my resume, I can personally say it is making me more attractive as a candidate, and seeing more corporations starting to use this technology hopefully more job opportunities this year.

https://www.nytimes.com/2017/10/30/arts/franco-moretti-stanford-literary-lab-big-data.html

The article “Reading by the Numbers: When Big Data Meets Literature” discusses professor Franco Moretti’s revolutionary way of close reading texts through the use of computers. Distant Reading is defined as the computer-assisted crunching of thousands of texts at a time. Rather than emphasizing certain books that “have stood the tests of time,” this method allows for the analysis of works that have been long forgotten and overlooked. By using computers to create data based on numerous forms of literature, we will be able to gain a more holistic view of literary history. Trends, themes, and histories will be easier to link throughout said history. This is relevant to my studies of literature. As an English major, I have to close read, analyze, and critique multiple texts throughout the semester. Tools like this will assist scholars in obtaining more accurate pictures of books and in placing them in the correct context in which they were written.

Educating New Data Experts for the World of Data Management

I find this article interesting because it talks about my generation the Millennials. My generation is going to make up 75 percent of the workforce by 2025. Our generation is already “tech-savvy” so companies just have to get us on board to do data professional roles. The article states that you do not even have to go to school for data jobs. The article states that the millennials have “to be groomed to take on Data Architect, Data Steward, and Data Governance jobs”. You can find talent in people who did not go to school for data jobs because they have a diverse set of skills and can work on different challenges. Millenials do not like doing the same thing all the time we like to be challenged and we like our assignments to change. This article interests me because I could get a data position in the future by an employer.

https://www.accountingtoday.com/news/pcaob-leans-toward-issuing-blockchain-and-data-analytics-guidance

This article goes in to depth about how at the most recent PCAOB meeting they are urging auditing firms to get a better grasp of data analytics. The PCAOB believes furthering their staff’s knowledge of data analytics will help them be more successful in their auditing effort. This article is interesting to me because one of the majors I am considering is accounting. Also, since I am taking two different MIS classes data analytics have been talked about to great extents.

https://www.forbes.com/sites/bernardmarr/2017/11/03/why-ai-machine-learning-and-big-data-really-matter-to-b2b-companies/#107964251f2a

For about two years, I keep hearing that AI is bad in a way that it will steal our jobs in the future. However, based on reading this article, AI + Big Data will actually help small businesses and companies to utilize their IT in positive direction such as lead generation, streamlining lead scoring, to monitor customer behavior and update us if we needed to interfere, and free up our time to do more high value work.

Gun Laws Stop At State Lines, But Guns Don’t

The article I picked, titled “Gun Laws Stop At State Lines, But Guns Don’t” is another controversial matter that has been up in the air among US gun laws. Among the recent tragedy that happened in the recent years, guns laws is up for a debate among lawmakers and its oppositions. According to the data published in the article, even though gun laws are very strict in certain states, the people can still purchase guns to neighboring states with less strict gun laws and carry the product to their home state loosely. Thus, strict gun laws is not working if it doesn’t have a unified gun laws in every states. I find this article very interesting due to the nature of the gun laws in the US itself and how loosely it can be tricked.

https://www.wsj.com/articles/out-of-the-frying-pan-in-china-kfc-tests-high-tech-and-healthy-options-1509964205
(the whole article is available only for paid members) “Fast Food Gets a Reboot in China: Tuna-Pesto Paninis, Paid for by Facial Recognition”
Usually, many people in China avoided going KFC because they thought fast foods are not good for their health. However, many fast food restaurants in China are trying their best to offer healthy menu and the annual gross is increasing a lot. It was so interesting that about 45% of whole sales in KFC were mobile payments.
The reason why I choose this article was that it provided a lot of data to check the new trend of fast foods in China. This article provided the stock price (growing rates) of each major company in China and the growth rate of the whole profit. I could effectively check the changing trend and could realize that marketers always have to prepare for new trend.

Gun Laws Stop At State Lines, But Guns Don’t

This article discusses the relationship between state gun laws and the paths traveled by firearms before being recovered by law enforcement. The analysis of the data proposes that even if a state has strict gun laws, if the neighboring states do not, the strict regulations will be undermined by people transporting guns from surrounding states. As a criminal justice major, I found this article very insightful, especially in light of recent mass shootings in America.

MyMusicTaste, which allows fans to request live events, gets $11M Series C

This article is about an interesting new app that takes a different approach in booking events. The concept behind it is pretty straightforward, the group has partnerships with artists and use user requests alongside other data to determine where and when to book events. The company prides itself on being very open about the data it is collecting, and which campaigns are gaining movement behind them so users feel truly involved. This is a welcome change from giants like Livenation that often have partnerships with large corporations like Iheartmedia, effectively curating today’s popular music scene.

http://www.bbc.com/news/business-41919958 This article talks about former top Yahoo and Equifax executives apologizing for breaches that exposed billions of customer accounts in front of the U.S. Senate. The executives claimed that they had no control over the breaches in security. I find this extremely astounding because, seeing as Yahoo and Equifax possess such personal information, I figured they would have better safeguards against – or at least better apologizes for –
foreign hacks.

https://www.usatoday.com/sports/nfl/rankings/ This article shows the NFL football rankings so far this year. It is interesting to me because the Eagles are the number one team right now and that is Philadelphia’s football team. It is so awesome to see this since we haven’t done this good in a very long time.

http://www.bbc.com/news/uk-41898318
This article is about how the next census in the UK could be counted by where a person’s mobile phone is being used and the data from it. I think that could be very interesting but it could also be inaccurate because they are not taking into account the people that do not have cell phones with this method. But it will make counting the census a lot easier and faster. So there are positives and negatives on both sides.

https://www.fangraphs.com/fantasy/its-probably-time-to-give-up-on-maikel-franco/
This article discusses why its time for the Phillies to give up on their third baseman, Maikel Franco, who has failed to live up to expectations, and move on to a new player. It uses his statistics from last season, as well as advanced sabermetrics, to conclude that he was the worst third baseman in baseball, falling to the bottom in most categories among eligible third basemen. While his potential is appealing, these statistics make it hard to see why he is a good choice for the team in the long run.

https://www.timeanddate.com/time/change/usa
This article shows an in depth view of daylight savings and its effect nationwide. I think this is interesting because it is relevant to everyone, and it also changes the way that businesses and other entities. I would find it interesting to examine its effect on electricity bills and certain sector’s changes in production.

Roy Halladay Was The Greatest Pitcher Of His Generation

This article talks about Roy Halladay, and just how dominant he was during his time in the MLB, even calling him, “The greatest pitcher of his generation”. This article comes quite unfortunately after his tragic passing just a few days ago. Growing up, Halladay was one of, if not my absolute favorite pitcher to watch in the MLB, and I would 100% agree with this articles argument in stating that he was the greatest pitcher of his time. This article includes data that highlights several facets of his game, and all these stats show just how truly remarkable of a pitcher he was. This article shows how he is at the top of several stat points, having the highest WAR from 2000-2010, as well as having the most complete games from 2000-2010, just to name a few. These stats show just how great of a pitcher Halladay really was.

https://www.t-mobile.com/optional-services/roaming.html
This articles focuses on different data plans for international traveling. The best data plan turns out to be free unlimited text messaging and 2G internet in at least 140 countries if you have Tmobile. You can search up whatever country you plan to travel to, and all the data rates for that country will be provided. This article interests me since I love to travel. I plan to travel to several of different countries in my future, and this will be an important factor once I do so.

https://www.theguardian.com/news/datablog/2017/nov/05/america-terrorism-risk-global-data-new-york

This article is about the threat of terrorism. As we all probably know, terrorism is reported heavily in media, and unfortunately this creates the perception that it is much more common than it really is. The data in this article compares daily fatalities in western nations to the rest of the world, over a span of a decade. What the data reveals is that we in the US are not in nearly as much danger of terrorism as the rest of the world. While any fatalities, domestic or worldwide, resulting from terrorism are tragic this article may help westerners get a more objective measure of safety from terrorism.

A Brief History of Data Storage

This article discusses the history of Data Storage for computers. The first example that was given of this dates back to 1948, where Professor Fredrick Williams used Vacuum Tubes for Random Access Memory. Since then, however, we have been rapidly advancing to storage devices as Hard Drives, Solid State Drives (SSD’s), and Flash Drives. I think this article put into perspective how rapidly data storage has changed over the 70 years. To think that my cell phone has more storage on one SSD than any computer could have in the 1900’s is remarkable. I can not wait to see where and how data storage changes over the next 70+ years.

http://www.reuters.com/article/us-cyber-mobile-vulnerability/mobile-app-errors-expose-data-on-180-million-phones-security-firm-idUSKBN1D91ZA?il=0

I chose this article because in this class we have discussed the affects of large data leaks, like the Ashley Madison scandal. This article stood out because almost everyone has a smartphone or tablet of some sort, but not everyone has an Ashley Madison account. Twilio, the app in question, is an app that users can use to make phone calls, and send text messages. I also found it interesting that the cause for this security breach was not the app’s fault, but the developers of the app. This could be grounds for a major lawsuit against the company.

http://www.huffingtonpost.co.uk/entry/revealed-when-you-should-book-flights-for-your-2018-holiday-to-get-the-cheapest-deals_uk_5a0416f2e4b0f76b05c37301
An article I found interesting is an article called, “When to Get The Cheapest Flight For Your 2018 Holiday”. I choose this article because I love to travel and I have always wondered if there is a best time to buy airplane tickets, such as the day in the week, or a specific time during the day before they are marked up, especially for holiday seasons. According to the article, the best and safest time to buy an airplane ticket is two months before your travel date, and by doing that you will be saving 34%. This data could become useful when planning my next traveling trip.

https://www.forbes.com/sites/bernardmarr/2017/04/28/the-big-risks-of-big-data-in-sports/#55c460707c6f

This is an interesting article on the dangers of big data in sports. I chose this because I’m interested in the subject of sports and I think the application of next-level data to the field would be fascinating. This article is particularly intriguing because it discusses data security and how large amounts of athlete’s information could be used by opponents to hone in on a particular weakness– for example say the right arm is marginally weaker than the left, that could provide an unfair advantage to an opponent that they wouldn’t pick up just by watching them play

Girl Scouts hope to change the face of AI, robotics, and data science

This is an article discussing how the Girl Scounts of America is helping to encourage more young women to pursue a career in STEM. Raytheon has teamed up with the GCUSA to launch the first national computer science program and coding challenge for girls in middle and high school. The Girl Scouts also launched 23 new badges in July, which included several that are earned by working toward STEM-specific skills.

Yesterday, former CEO Marissa Mayer testified in front of the US Senate about the 2013 Yahoo data breach. 3 billion accounts were hacked during this breach, leaving U.S consumers personal information exposed. This is worrisome because many online companies require an email and password, and many U.S citizens use the same password for various web services that require an email and password. This lead many American vulnerable to future hacks. I’m interested in seeing what lies ahead for the C.E.Os of companies such as Yahoo, Equifax, and Verizon, and seeing where the U.S future lies as far as online security.

https://www.cnet.com/news/yahoo-equifax-breach-senate-congress-hearing-marissa-mayer-rick-smith/