Min-Seok Pang, Ph.D.

I work part-time at J.Crew, and part of my job is fulfilling online orders. Through our intranet, I can see the items ordered, the customer name, and whether the order was accepted or if it is pending pick from inventory. In spreadsheet format, the field names could be customer name, number of items ordered, full price or markdown, mens or womens, and the amount of that item we have in inventory. Each row would represent a complete order, and a final field could be whether or not that order has been completed and packaged.

An example of a data-driven service that I use regularly could be Snapchat. Its a stretch but in an excel spreadsheet every row could represent an individual user. Some of the data columns that can be used within this spreadsheet are number of snaps sent within a day, times that snaps were sent at, how many friends they have, location sent at, and who their best friends are.

A data driven website that I use on a regular basis is Blackboard in order to keep up with how I’m doing in each of my classes. If I were to store the data in a spreadsheet, the rows could be categorized for each specific class that I’m taking. The columns could have information such as the professor’s name, exam grades, assignment grades, attendance, and any other information relevant to how I’m doing in the class.

I frequently use Spotify to listen to any albums or artists for free. The service may have an extensive user based data record containing rows with headers for what artist, song, or album I listened to. Other information stored in Spotify is then based upon designated related artists and songs that I would listen to in relation to the chosen artists in my user based data. The data would be largely song and artist names.

I regularly use Spotify at school, at work, and in the car. In terms of how it is stored in a database, for a row it could contain the name of the song, and the column would be the genre, artist, album, year recorded.

One data driven website I use is Blackboard to check the syllabuses, see what assignments I need to work on and check grades. If I were to turn it into a spreadsheet, the columns would be homework grades, quiz and exam grades, my attendance and my overall grade in the class. The names of the classes would be in the rows. That is how I would turn the data driven site of blackboard into a spreadsheet.

A data driven website I visit regularly is Amazon. I could make spreadsheets on different aspects from items purchased, items related/suggested based on what I have purchased, or items on a wish list. For example a column could be items purchased and the rows could be name of product, price, date order was placed, date order was received, and seller, among many other pieces of data related to the item.

A data driven service that I frequently use would be Spotify. There are many different playlists available on Spotify that contain a number of songs. Data from Spotify could be stored using a spreadsheet similar to the one we created during the In-Class Exercise 11.1 that we completed on Wednesday. The columns could be listed as Playlist, Song, Artist, etc. The rows would be made up of the playlist names, song names, and artists of the songs.

A data driven service I use frequently is Instagram. Each row could be a different posting, and the columns could be Username, Date Posted, Time Posted, and the Location (if it was included). Since you don’t have to include a location, some posts may have an “N/A” for that specific column.

I used to work part-time at Brother’s Auto Repair. The business used a software called Mitchell Manager, which keeps track of customers and their car repairs. When depicting this information on a spreadsheet, the column will be the individual customers and the rows will consist of their information. The rows can be the car model, the year of the car, manufacturer, the date of repair, and the repairs the customer received.

A data driven service I normally use is LinkedIn. If I were to store the data on LinkedIn on a spreadsheet, the rows will be the names of my connections. Some of the columns can be what jobs they are currently working and for what company, their majors in college, their interests/hobbies, whether they are a primary or a secondary connection in relations to me, and I can make a column for any extra comments about other notable points of their profile.

A data driven service I frequently use is Blackboard. If the data on Blackboard was to be displayed in a spreadsheet, the rows could be each class that I am currently taken. The columns of the spreadsheet would include; total grade for the class, assignments, classwork, class participation, and homework. I think “teacher’ could either go in the rows with the class, or be another category put in a column.

A data driven service I use regularly is Nintendo’s online network. Nintendo tracks what games you play online every day and how much time you spend playing. Each row could represent each individual user, and the columns could represent games played, time spent playing, location, and game genre.

Since the baseball season started today, one site I use regularly is ESPN’s fantasy baseball site to manage my teams. Putting the data for it into a spreadsheet would be very easy. In rows, there would be the names of all the players. In columns would be the positions, team name, and all of the various stats including homeruns, hits, or strikes.

A data-driven service that I use regularly would be the PictureCarePlus program at my job at Walgreens. This data service contains the customers, name, phone numbers, type of photo order, amount of orders, time of order placed, date of order placed…etc. If I wanted to store data for this service in a spreadsheet, the row would contain the names (first and last) of all the customers, then in the columns there would be all of the photo service specifics that I mentioned above in terms of the number of orders and types or orders etc.

I work part time at Ann Taylor’s LOFT and as a means of fulfilling online order we use a system called Domestic Online Merchants (DOM). DOM records and process incoming online orders and list them so we can decide to accept or reject the order base on inshore availability. A row would be an individual order number and some columns would be customer’s name, item’s name, quantity of item, color description, style number, department number and the customer’s address. Another important column would be the decision to reject or accept the order.

A data driven service that I use would be Youtube. You could turn the data for each video into a spreadsheet. The rows could be the titles of the videos. The columns could include the Channel of the video’s creator, duration of the video, categories the video is in, likes, dislikes, views, and number of favorites (hidden but you can view who favorited the video and who did not if you are the original content creator).

A common data driven website that I use is the nhl section of espn.com. The data that I am dealing with is statistical data for each team, and each player on those said teams. This actually comes out in a spreadsheet form most of the time. The rows end up being either specific teams or players, and the columns are particular stats. A good example is the standings. You get to see the team name in the row section, ranked from best to worst, and some column headings are GP (games played), W (wins), L (losses), PTS (points), and so on.

A data driven service is one I use while working at an insurance agency the service is called D-Base. This is a service that is a collection of all the costumers information, policies, the employees hours, just about everything that is part of the business. If I had to create a spread sheet the first would be for customers with columns that could be the name of insured, what type of insurance (home/auto), the base premium, renewal/cancellation, if the agent receives commission (if so how much), and yes/no if the paper work is scanned into the system. When it comes to employees this sheet could include hours worked, vacation days, sick days, and pay per hour.

A data-driven website i frequently use is eBay. I can use the data from this website to view all of my potential buying options. I mainly use eBay to buy sneakers, and if i were to make a spreadsheet of the data, the row would represent a specific style of sneaker, and the columns would have attributes such as price, condition, shoe size, color, etc.

I work as a trainer at a fitness studio, and we use a data-driven platform called MindBody, where clients can register and pay online for classes, the staff can check and see which clients are in their classes for the day as well as which clients are new, and numerous other functions. If I were to create a spreadsheet for this info, I would make the rows each specific client, and the columns would be things like number of classes taken thus far, class payment package, number of late cancellations, payments due, class times most frequented, age, and injuries (to start with). This would be able to tell me which clients pay on time, don’t cancel late, and even see the most popular class times for the majority of the clients.

An example of a data-driven service that I use regularly could be Snapchat. Each row could be an individual user and the columns can be the number of snaps sent within a day, times that snaps were sent at. How many friends they have, location sent at, and who their best friends are.

A data driven service I use frequently is Tumblr. If I store the data in a spreadsheet, rows will contain data posted, data re-blogged, and columns will contain my user name, users I’m following, likes, and followers. I think columns may also contain my linked accounts, since Tumblr allows users to have several blogs with one email address.

Think about a data-driven service that you use regularly (i.e., Blackboard, Amazon.com, Facebook). Imagine you want to store the data for that service in a spreadsheet – what would each row in the spreadsheet represent? What would some of the data columns be?

I use blackboard on a daily basis, for homework assignments, grades, etc. Each row would represent a different class. Then the columns for each row would break down in announcements, assignments, quizzes, and grades.

One data-driven service I use daily is Blackboard. It stores my courses and grades. Each row would indicate an individual assignment and columns would include the grade, assignment title, assignment weight, subject, total points, etc.

I use blackboard regularly. If I want to store data in a spreadsheet. I think I will use rows represent different classes, and I use columns to represents the average score of different types of assignment and also exam. Then I can see the comparison between different classes, and see how I did.

A data driven website I often use is Youtube. A row would be an individual video. A column could be the artist/ producer of video, channel the video is on, number of subscribers to the channel, number of views, another video often viewed after this video, and number of likes and dislikes.

I regularly read the Wall Street Journal, so I downloaded the app for my phone. The app contains all of the articles that are printed in the journal as well as the articles on the website. In a spread sheet, the rows could represent the article title and the columns could represent the name of the author, the number of views, and the category to which the article belongs.

For a company like Amazon, each row could be a different order number. the columns for these orders are endless. They would need to store the customer’s information, the name of the item, where the order is being shipped, etc… there are plenty of things that we could categorize the orders with. we could also use user information as a column, and use the user’s information, such as credit card info, address, and order history.

A data driven website I use everyday is YouTube. If I were to store data from this website onto a spreadsheet, the columns would contain the channel name, views per channel, likes, and dislikes. The rows would contain the name of the video appearing in subscription inboxes.

A data driven sit that I use often is Facebook. I would put the name’s of people that I actually interact with on the columns line. Then I would put personalized things on the rows. For example, number of pictures, status updates, posts that they commented on, and posts that they commented on. In addition, I would probably included “check ins” or places that the people I interact with posted. I think that would be interesting. I might actually enjoy it more because I would be seeing things that are actually relevant to me. On the other hand, I might get a little more because I do not actually communicate with many people on Facebook.

A data-driven service that I use regularly is Amazon.com. In order to store the data into an Excel spreadsheet I would use customer names as the rows. Some columns would be order type, product, price, etc. This could be used to organize orders and see the products or types of products that customers are regularly buying.

Twitter would be by far one of the best options. You can have each row represent the user you follow, and each column could represent how many tweets they’ve put out, how many they’ve retweeted, and how many they’ve favorited

http://www.economist.com/node/21695071

My article is about how low wages are a double edged sword, as being both a consequence and a cause of low productivity in the global workforce. I like how it mentions both sides of the situation, addressing how in one way, people will work harder with a higher wage (which covers the cause side) and also how low productivity results in a lower wage (which covers the consequence side). This was interesting for me because I find myself in conversation about this all of the time. Personally I feel like this current generation is less of “go getters” and more of what I would call “waiters.” Rather than go out and work hard to get the higher wage, they will sit back and expect more for what they are doing (take the Mcdonald’s workers striking for $15/hour wage for an example.) That is a prime example of one sitting back, complaining, and waiting, rather than going out and doing what’s necessary to advance. Nobody ever said it will be an easy task to do so, and why should it be? If there was no incentive to work hard, we would be lacking hard workers all together.

http://fivethirtyeight.com/features/how-fivethirtyeight-is-forecasting-the-2016-ncaa-tournament/

My article talks about the predictions of the 2016 NCAA tournament and which teams have the highest probabilities of reaching the championship game. This was interesting to me because usually people predict the tournament based on intuition or who’s on a winning streak heading into the tournament, however, this article combines many factors and data sources to come up with a table. They have gathered sources from computer power rankings, preseason ratings, LRMC ratings and many more. Using these sources have allowed them to create a table for every team and the probability of that team reaching the sweet 16 and the championship game which was really intriguing to me. Go Owls

http://www.usnews.com/news/articles/2016-03-23/the-china-us-trade-relationship-in-1-gif

As an International Business major and an upcoming voter in the 2016 election, international news/statistics dealing with the U.S. economy interest me. In the article, the author included information regarding the candidates plans, specifically Trump, and an economic explanation. Halfway through the article, a GIF visually shows how large the U.S.’s trade deficit with China really is. The visualization helps put the reader in perspective, but the following economic explanation after helps the reader really understand the data presented in the GIF.

http://fivethirtyeight.com/features/failure-is-moving-science-forward/

I picked this article because the title stuck out to me, when I first saw it I was curious how failure could be moving science forward. The article talks about how hard science actually is. Taking a study and repeating to see if the results are the same, making the evidence true or if the results are different, meaning the evidence is false is not as easy as people think. The author is saying however that it is good to have failures while replicating a study because usually the original results show some sort of bias. Reading this article it makes sense that failure moves science forward. The “failures” are actually proving and creating results for tests which helps scientists or experimenters realize what’s wrong and further their scientific discoveries.

Article: “Why Donald Trump?’ http://fivethirtyeight.com/features/why-donald-trump/

The article talks about why people are choosing to vote for Donald Trump, when the media portrays him negatively. The first data visualization shows that republicans are the least trusting of the media; following independents, then democrats. I’ve seen news from the media that Donald Trump is not against the KKK and in the article the writer asks a Trump supporter what she thought about Trump’s refusal to disavow an endorsement from the former head of the KKK. She responds by saying, “If I went online and searched for “Clinton; image; KKK member” it would show up”. I did exactly what she said and I saw Hillary Clinton getting a kiss from Robert Byrd, former KKK leader. I started to think maybe Hillary is a hypocrite, just by seeing that image. However, I did some more research and found out that Robert Byrd became a senator and apologized for his actions in the KKK. Therefore, the people who are voting for Donald Trump are not intelligent enough to do more research and so they are a sheep following a wolf (blindly following a leader). Also, they are hypocrites because they are believing in the media images of the Democratic candidates.

http://fivethirtyeight.com/features/primary-turnout-means-nothing-for-the-general-election/
This article uses four data visualizations to prove that primary turnout does not have any impact on the general election. In 2016 primary elections, the Republican turnout is up and the Democratic turnout is down. The article says that voter turnout is an indication of the competitiveness of a primary contest, not of what will happen in the general election. This means that the GOP presidential primary is more competitive than the democratic race. The article uses data from past election years when the political party with higher turnout during the primaries won the general election 50% of the time. The article also used a few other measures, such as change in turnout and percentage change in primary turnout, to prove that primary turnout has no relation with the outcome of the general election. I found this article interesting because we are hearing about the outcomes from all of the primaries, but they are no indication of what will happen in November.

http://www.businessoffashion.com/articles/fashion-tech/data-is-the-new-oil-and-more-from-sxsw

This article compares how the fashion industry, more specifically in the retail market is paying more attention to their usage of data. Data is the new oil,The companies that will win are using math” said Kevin Plank, founder and chief executive officer of Under Armour, in a talk on brand building. This is especially interesting as more companies are utilizing new innovations that focuses on branding their product in a more personalize way. What I also found interesting was the usage of Conversational Commerce. To better the experience of consumers shopping online, apprehensive research are going into creating a system that link the consumer with the brand. This idea of conversational user interfaces is expected to facilitate a better, more personal experience within the ecommerce realm.

Financial Data Summit 2016

This article caught my interest because it emphasized how skewed and unused data is even after the Rogoff and Reinhart mishap and the present times of meticulous work. JW Marriot just recently started to use the ETL methood-extract, transfer, load. I know that if I was running a multi-million dollar company that I would have a group of data scientist doing the arduous work of data analyzing, but maybe that’s just because I love numbers. At the same time, I feel like everyone should look at the raw data.

http://fivethirtyeight.com/features/science-question-from-a-toddler-why-am-i-right-handed/
This article is a start of a series of questions toddlers ask since they hold so much curiosity. They try to explain what causes us to be right and left handed. This sparked my interest since it is one of those looming question in life that we just assume there are more right-handed people just because that is how it has always been. My family of five has one lefty in it so she is the outlier. Which I realized that handedness may not come from genes but, from this article it can be a factor. Just like with many ways our body works it is affected by our culture, families, and genes. They are still trying to determine what exactly causes handedness but, until then we must accept it as the mystery it is.

http://fivethirtyeight.com/features/bernie-sanders-continues-to-dominate-caucuses-but-hes-about-to-run-out-of-them/
This article is particularly interesting to me because I have been following the race for the 2016 presidency and I’m a supporter of Bernie Sanders, so seeing this data being presented is very intriguing since there are only few democratic caucuses left where he seems to be winning by a large majority. Reading this made me realize that with the democratic primaries left which are run differently than the caucuses will prove whether or not Bernie Sanders has what it takes to catch up in terms of total state delegates compared to his running mate Hilary Clinton.

http://www.wsj.com/articles/google-launches-new-data-tools-for-marketers-1458043217
This article interested me because it shows how a well known company, Google, is doing to help marketers in other businesses. It talks about how they have created new data tools that can help the marketers. The new tools can turn the data gathered by marketers into different types of interactive reports and dashboards. It makes it easier for businesses to market their products. That is why this article about Google and its new ideas interested me.

http://fivethirtyeight.com/features/the-job-market-is-pulling-in-people-who-didnt-want-to-work-before/
What caught my attention originally was the title of this article. I thought it was interesting that suddenly a number of people are trying to get into the labor force compared to the number of people who originally left the labor force due to a previous recession. Many people going back to work include stay-at-home parents, part-time college students, and early retirees who are trying to find another small source of income. It’s interesting that people are trying to get back to into work but it’s also great news for our economy.

http://fivethirtyeight.com/features/syracuse-men-in-final-four/

Admittedly, I’m not much of a sports fan, but March Madness is an exception as I have a stake in the outcome, via my bracket and how it measures up to those of my friends. This article about Syracuse’s success in this years March Madness bracket caught my eye, as my bracket is suffering due to the success of teams like Syracuse and the failure of teams such as Kansas, Michigan State, and UVA. This article talks about various KPIs used to measure the success of each team, including a specific KPI called Elo, which measures the success of any team at the given moment. After reading this article, I realized that Syracuse is one of the most improved teams in March Madness history, and seed numbers assigned before play has started can prove to be somewhat arbitrary as they do not always accurately reflect a given team’s ability to perform.

http://fivethirtyeight.com/features/the-rock-dwayne-johnson-diet/
The title of this article immediately caught my attention: “Here’s What Happened When Some Dude Ate Like The Rock For A Month.” The sheer numbers in the article (calories per day, meals per day, time to prep each meal, etc.) were interesting/shocking to look at, especially since this kind of diet/exercise regimen isn’t something that the typical person follows. Even money-wise, the guy that did this experiment for a month spent a total of $1262 on food ($42 per day)! The article also included a chart with some of his meals and their nutritional stats. I found it interesting to see how this kind of hyper-specialized diet/exercise regimen stacked up against the average person’s routine. Also, just the prep time alone to meet those kind of caloric numbers/nutrition per day is staggering!

http://www.forbes.com/sites/teradata/2016/03/25/big-data-lacks-big-questions/#40a271f620b8

This article is interesting because it partly answers the question of why the field of data processing have not managed to make much impact despite the coverage Big Data is currently getting, and correlates well with the information we have been given throughout the course thus far in that when we have so much data readily available, what is important is asking the right questions. The article also points out a need to have a unified system for cataloging data in order to form a more complete picture of any situation lest the state of data processing in the company becomes ‘like a chaotic orchestra where each musician plays independently’.

http://blogs.wsj.com/economics/2016/03/29/how-millennials-and-low-income-consumers-are-propping-up-the-u-s-economy/
My article talks about the customer spending percent change for different ages. This article attracted my attention because I was surprised by its title: “How Millennials and Low-Income Consumers Are Propping Up the U.S. Economy”. I never think one day the low-income people and young generation would prop economy more than the rich people and middle class do. This is a totally new idea to me. The writer used two bar charts to illustrate the percentage-point contributions to the year-over-year change in consumer spending for 15 metro areas and he also gave readers specific data of the chart, which really helped me to understand the changes of consumer spending percentage.

http://fivethirtyeight.com/features/villanova-will-die-or-live-by-the-three/
This article talks about Villanova’s basketball team and how they can succeed in the Final Four of the NCAA Basketball Tournament. I thought this was interesting because I am a big college basketball and Villanova fan. This article uses 3-point shooting percentage as a measure of the team’s success, stating that if Villanova can continue to reach a high shooting percentage from 3-point range, they will have a much higher chance of winning the championship.

http://thescoopblog.dallasnews.com/2016/03/dallas-animal-services-saved-more-pets-than-it-euthanized-last-year.html/
I am a person who support adoption rather than buying pet, so I am interested in this article. The good news from this article is the euthanasia rate at record low. The shelter Dallas Animal Services says it found homes for 52 percent of the nearly 30,000 animals it took in during the 2014-15 fiscal year. It is also the first time the amount of animals saved exceed the amount of euthanasia. Jones said she’s especially encouraged the trend continue during the first two months of 2016, when she said the shelter saved more than 70 percent of its animals.

http://fivethirtyeight.com/features/updated-odds-of-the-warriors-going-73-9/

This article discussed the possibilities of the Golden State Warriors to beat the NBA’s regular season record of 72-10. As the season winds down, the Warriors’ chances keep getting better. Based off of the CARM-Elo predictions, the Warriors have a 66 percent chance of beating the record. I thought this way interesting because of the unique CARM-Elo prediction that uses team personnel and the teams past performance to measure its strength.

http://www.cmswire.com/customer-experience/tech-news-to-use-using-data-science-to-stop-cancer/
This article discusses the use of data to help in the fight against cancer. Tamr wants to help speed up the fight against cancer using data integration and their own big data platform. With the enormous amount of cancer data in the US, they believe using this program will allow researchers to more quickly and easily analyze it. It would be interesting to see the implementing of a program like this. Those with the experience and knowledge of data analysis could use the mass amount of cancer data and put it into visualizations and come to conclusions about what is seen throughout.

http://fivethirtyeight.com/features/donald-trump-is-no-ronald-reagan/

Although I am not very intrigued by the topic of politics, I am interested 2016’s presidential candidate Donald Trump’s campaign. Though I assumed a slightly different argument when reading the title “Donald Trump is No Ronald Reagan”, this article still holds some thought provoking points. Based off of the polls, Trump has not lead in any of the in comparison to Clinton, yet more people dislike Hilary Clinton than they dislike Donald Trump. With this in mind, “general election polls at this point are not a reliable indicator of the outcome.” (Enten) I think this is very significant, because although numbers don’t lie, they cannot always predict the future, even when the odds for something look pretty good or pretty bad.

http://fivethirtyeight.com/features/science-question-from-a-toddler-why-am-i-right-handed/
I have never really thought about “why I am right handed” until reading this article. For generations handedness was thought to be genetics but scientists recently proved this to be false however, they do not have a true test to determine what makes humans right or left handed. They are using different tests but none prove to work all the time. Scientists even looked at what thumbs human fetuses suck in the womb to see if any correlation could be made. Overall, this article was very interesting because I always thought handedness was genetic but this article proves that wrong.

http://fivethirtyeight.com/features/villanova-will-die-or-live-by-the-three/
The article talks about how Villanova’s basketball team and how they can succeed in the final four of the NCAA basketball tournament. it uses the 3-point shooting percentage as a measure of the team’s success and how they will have a much higher chance winning the championship.

http://fivethirtyeight.com/features/syracuse-men-in-final-four/

The NCAA Tournament, coined “March Madness,” is one of the wildest, most exciting, and definitely the most unpredictable event of each year. The unpredictability that comes with it attracts not only millions of viewers, but also many data scientists to explore the stats behind it. This year in the Final Four are favorites in most brackets: North Carolina, Oklahoma, Villanova but somehow ten seed Syracuse found themselves a ticket to Houston. Their bad play through the year, gave them about a one percent chance of this actually occurring in the beginning of the tournament. In the last 11 years, they are the fourth most unlikely participant. Some did not even think they should have made the tournament, their accomplishment is incredible. This is a very interesting article but Syracuse doesn’t interest me as I had them losing in the first round for my bracket.

http://fivethirtyeight.com/features/updated-odds-of-the-warriors-going-73-9/
This article is about the odds that the Golden State Warriors have to complete the regular season with a record of 73-9 or better. This goal is significant because Michael Jordan led the Chicago Bulls to set the regular season record of 73-9 in the 95-96 season. According to FiveThirtyEight’s prediction system it gives the Warriors a 66% chance of achieving this goal, but the system can’t entirely be trusted. For example, this prediction doesn’t account for the Warrior’s coach benching key players like Steph Curry in preparation for the playoffs. I find this article interesting because it amazes how much numbers can tell you about things, but anomalies still exist so the numbers can’t always be trusted.

This article discusses both how Apple was hacked by the FBI (though not exactly how the FBI hacked the iPhone) and how Apple cannot figure out how they were hacked in order to fix the “flaw.” Our phones collect so much data about us along with others around us. While we hope that this data is secure, it is clear that this is not the case 100% of the time.

http://espn.go.com/blog/nflnation/post/_/id/200970/2016-nfl-draft-order
My article has data involving the upcoming NFL Draft. Here the data concerning the official pick order, including compensation picks, for each team is listed. When this data is put together with data involving the teams current rosters and data involving this year upcoming 2016 draft class, you can hypothesize what teams will consider which players at different parts of the draft. For example, knowing that Tennessee has an the first overall pick in the first round the the second pick in the second round, and the fact that this draft class is considered deep in Offensive Line and Cornerback, both of which are two of Tennessee’s biggest needs. You can predict that they will use their first overall pick to draft either Tackle Laremy Tunsil first then Cornerback Eli Apple second or they could draft Cornerback Jalen Ramsey first and Tackle Germain Ifedi second.

http://www.philly.com/philly/blogs/campus_inq/NJ-colleges-grant-more-degrees-than-ever.html
I found this article very interesting because it made me start putting things into perspective regarding myself. This article was providing data about how many degrees were being received in New Jersey and it helped me understand the reality behind the increase of people getting degrees. It means that it will only be more competition in terms of actually getting employment post graduation. I know this article only mentioned the information for New Jersey but you can assume the same thing is happening in other states.

http://www.wsj.com/articles/poll-finds-kasich-rubio-moving-in-opposite-directions-1457874084

The author of this article used a poll to figure out which candidate is leading in three different states. The data visualization that they use in this is very simple to read and comprehend, while also getting the point across rather simply. I think that data visualization for politics is especially helpful for people that do not know much about politics, so I appreciate this article very much.

http://www.dataversity.net/fighting-dysfunctional-cycle-data-chaos/

This data emphasizes dirty data and how its affected current data. Dirty data has hindered the input of new data in modern day. “They spend ‘ridiculous amounts of time hunting for missing data, correcting inaccurate data, creating workarounds, pasting data together and reconciling conflicting data. This results in tremendous unaccounted loss in productivity,” Dirty data puts back the progress companies make and also the time they spend fixing it negatively affects the time they spend improving their company because until the data is cleaned and fixed no company will really be able to understand their revenue, profit, etc.

Being a Phillies fan, i found an article on SI.com about the predictions for the 2016 Season

http://www.si.com/article-list/2016-mlb-season-team-previews/philadelphia-phillies-season-preview

This article features the 2015 data of the Phillies record, what the record balances out to, and their projected 2016 record. This projected record is based off of 2015 performance for the team as a whole, and each player individually to identify where they could potentially land in terms of the finish of the 2016. Because of their recent struggles, obviously we are not projected to reach the playoffs, but as a Phillies fan, we are rebuilding our team for the future.

https://www.ama.org/publications/MarketingInsights/Pages/data-drives-trend-forecasting.aspx
I read an article about how marketers need to use data to create models for trends. Before, we used past data and now we need to incorporate forecasters, trend spotters and customer data as well. Another thing we need to do is use real time customer databases like Twitter to see what is trending right now or what will become trending before it is just the fad du jour. If we had the technology we have now, we may have been able to predict the exponential growth of whole foods and gluten free options.

http://fivethirtyeight.com/features/how-fivethirtyeight-is-forecasting-the-2016-ncaa-tournament/
I saw this article on five thirty eight when the ncaa brackets started to fill themselves out. It’s interesting to see how they use different metrics like strength of schedule and BPI to determine probabilities for each team winning all the way through the final 4. Most of the time I use my own intuition and limited knowledge when I pick out teams to win, so seeing it from a data backed perspective is interesting when comparing to my own picks.

http://fivethirtyeight.com/features/how-fivethirtyeight-is-forecasting-the-2016-ncaa-tournament/
I saw this article on five thirty eight when the ncaa brackets started to fill themselves out. It’s interesting to see how they use different metrics like strength of schedule and BPI to determine probabilities for each team winning all the way through the final 4. Most of the time I use my own intuition and limited knowledge when I pick out teams to win, so seeing it from a data backed perspective is interesting when comparing to my own picks…

Jacob, where is the link? Please post for credit.

Kenneth, where is the link to your article? Please post for credit.

I constantly use the KPI of how much time/work I am putting into my coursework, such as study/homework time. It is specific, measurable, and time-variant, as I can count the hours/minutes/ and it I were to set a timer, even seconds I spend. It is achievable, as I can adjust my schedule to alter the time I spend studying. And it is relevant because the amount of time and work I put into my courses, the better my grades are and it increases my understanding of the material so that I can implement the knowledge in the future.

I use KPI by seeing how much battery percentage is remaining on my phone. It is specific and measurable because you can measure the remaining battery percentage on the phone. It is achievable because there are ways to increase battery life such as turning down the brightness of the screen and placing it on airplane mode. It is relevant because everyone uses their phone and people need to see how much longer their phone will last. It is time variant because I can look at the average battery usage over the course of a day, week, or month

I use KPI by seeing how much time I am putting into my classwork and homework. It is specific and measurable because I can see how much time I am working on my work. Also, it is achievable because I can choose how I make my schedule in order to have some time to work. It is relevant because everyone spends time working in order to pass classes and do good in those classes. It is time-variant because I can choose the amount of time I spend working and take breaks in between.

I use KPI to see how much time it takes me to complete a given assignment. By this point in the semester, I know which types of assignments take longer for me to complete than others. This KPI is specific as I can apply it to a specific set of coursework. It is measurable by noting the amount of time it takes for me to complete my homework. It is achievable as my homework is able to be completed in a timely manner. It is relevant because it pertains to my success at school, and it is time-based by having deadlines for each assignment. By using this KPI, I can prioritize and better parse-out my work to get it done in the most efficient way possible.

I use the KPI of how many steps I take per day using the health app on my phone. This is specific and measurable as steps per day is a simple quantitative measure. It is achievable as I can work harder to take more steps per day in order to promote a healthier lifestyle (10,000 is usually the goal). It is relevant because it affects my personal health! It is time variant because I can measure my steps per day over time (week/month/year).

I use the KPI of how much time I spend studying for tests. This is specific and measurable because I can easily time how long I spend studying the material. It is also achievable because I can compare the time I spent studying to the score I get on the test to determine if I need to study the material more or if the amount I’m doing now is fine. Its time variant because I’m measuring the how long (minutes or hours) unspent studying. This KPI is also relevant because I take tests almost every week and always study for them.

I use KPI in managing my social and academic activities. There are set numbers of homework and social events on campus every week, which is specific and measurable because I can calculate how much work I do or how many events I go per week. It is achievable because I can adjust social events attendance according to my workload and vice versa in order to fit the time frame/deadline of a week, and relevant if I want to do well in school and find future work opportunities at the same time.

A common KPI I use is the amount of calories I burn in a day using my Android phone. The application I use takes into account the type of action I take during the day, whether it is walking, running, jogging, or bicycling, which is pretty impressive. It gives me an aggregate estimate of the amount of calories I burn daily as a result of my physical activity. This KPI is both Measurable and Time-Related since it measures activity performed as calories burned, andgives those results daily so it is timed.

A KPI that I use on a regular basis is how long I’m able to run on a treadmill while at the gym. It’s specific because it provides me with a time for how long I’m able to run, and it’s measurable because the treadmill keeps track of the distance I ran as well as how long it took me to run that distance. It is achievable because my using that information, I am able to constantly try to improve myself and see whether or not I can run a longer distance, or even the same distance but in a quicker time. It’s relevant because I’m currently training for the Broad Street Run in May, which is 10 miles. By monitoring this information I can see how well I’m improving in time and try to work my way to the 10 mile goal. It’s time-related because I’m able to check how long it takes me to run a certain distance and then I can try to improve my time.

I use the KPI of how much time I spend on studying and school work while still being able to maintain a social life. This is specific and measurable in accordance to what classes are easier for me or ones that I have trouble with. Since I know that I struggle with math I will take more time to complete that work during the week instead of pushing it off until the weekend. This is achievable with the help of time management. The larger my work load is for my courses the more time I will set out during the week in order to maintain time for the weekend. It is relevant in order to stay on top of my work, maintain good grades, and reduce stress. It is time variant for I can refer to a syllabus to check for deadlines.

KPI that I can use is the KPI of tasks I get completed in order to determine how productive I am. I use Microsoft Outlook to list all of my school assignments and tasks. The specific idea to measure is my productivity. It is measurable because I check off the tasks that I complete and can see how many tasks I completed on what days. This KPI is achievable because all the information is stored within the software. It is relevant because I base my productivity on tasks completed. The more tasks I complete on one day the more I was productive that day. Lastly, it is timely because I can see the tasks I complete on time and tasks I did not complete, which means I was unproductive.

A KPI that I use in everyday life is calorie intake and burned. Its specific and measureable because I can count how many calories I have eaten and how many I have burned with exercise. Its Achievable because working harder and eating better can help me achieve it. It is relevant because it has to do with my personal health and wellbeing. It is time-variant because I can measure it over the course of a minute/hour/day and so on.

A simple KPI is time. Whether its walking to class, working, studying etc. time is essential and it is a KPI we come into contact with everyday. Evaluating a KPI can help show you where you are excelling at and where you may be struggling at. For example the more I focus on social media during work time, my work progress slips because more time is focused on social media than working. Helping to separate work from social media can increase my work performance and limit my time using my phone during working hours.

As a commuter, I use a time KPI measuring how on time my train normally is to get to campus from my house. It is specific for obvious reasons, measureable in regards to whether or not they hit the achieved time, achievable due to the fact that if they arrive at the scheduled time then they achieved the goal, and I achieved my analysis. It is also relevant because I need to be on time to get to class, as well as time variant due to the fact that my KPI is completely measured on on time performance.

A KPI that I use in everyday life is time spent working out weekly. It is specific to time spent working out and measurable in minutes. It is also achievable because I can work harder to spend more hours in the gym in order to get into top shape, and stay active. It is relevant because it affects my health and overall wellness. Finally, it is time variant because I can measure the amount of time spent working out weekly.

One KPI I regularly use is amount of time allocated when studying. It is specific and measurable because I calculate every minute spent and minutes are measurable. It is achievable because I control how I spend my time. Time spent studying is (usually) relevant to the grades I earn. Lastly, it is time variant because I can compare time spent studying over the course of a semester.

A KPI I use often is the features in Mint. Mint a finance Application on my phone that keeps track of your spending. It tells me when i’m approaching my budget and where exactly I am spending my money. Mint can also keep track of your monthly bill payment and uses that data to remind you when your bill whether it be phone or utility, is approaching. I can adjust my budget by amount and allocation. For example, I set my weekly coffee spending to be $15. When I approach this it warns me. This is a great app for people like me who is almost always obvious to her spending track and is a caffeine addict.

A KPI i constantly use is time.
S: Although it is used for no specific purpose, time can used as a measurement for a wide variety of activities such as how you split your time between projects, or how many days does it take on average for a group to complete this project.
M: Can be measured in seconds, minutes hours and days.
A: All you need to measure time is a timer.
R: The amount of time one spends on something can directly correlate to ones success in that activity depending on the activity.
T: Time is time-phased.

A KPI I use is the distance tracker app on my phone when I go running. It is specific and measurable because it measures the exact distance that I go. The distance goals I set are achievable each time I go running and relevant to my workout plan. It is time-phased because I can look at the distances I have gone over any time period (I usually use a week).

A KPI that I have used through college is how many hours I work per week at my job. It is specific and measurable through how many shifts I do and how many hours they are. It is achievable because I can take more shifts if I need more money and relevant to success again because it is the source of income I use to pay for my rent. Lastly, it is time-phased in weeks.

The KPI that I use everyday right now is how much time I walk my dog.

This is specific because my dog need to lost at least 10 pounds weight.
This is measurable, I use my phone to measure how much time I spend.
It is achievable, I believe it is achievable… She already lost 4.4 pounds.
It’s relevant, more walking can result more calorie burning.
it’s time-variant, I check my god’s weight at least once a month.

I work as a waiter at a restaurant. My KPI is tip percentage. Basically, at the end of each shift, I review my sales summary and divide my total amount of tips by my total amount of sales. Generally, if someone who eats at a restaurant feels that the service was good, it is common to leave a gratuity that is 20% of the bill. Therefore, if my tip percentage is above 20%, it tells me that my performance was good for that day. This is specific and measurable because a percentage is precise. It is achievable because I can try to be more pleasant and efficient to raise the percentage. It is relevant because my whole job depends on the quality of my service. Finally, it is time-variant because I come out of each day with a different total and I can compare it to other days to see if I am maintaining and improving my service.

A KPI that I use daily is the number of steps that my VivoFit records per 3 hours of gymnastics practice. I use this to see how efficient my practice was for that day. It is Specific & Measurable because it is a very clear indicator and can be expressed by a number. It is Attainable because the watch counts how many steps I have during the time zone. It is Relevant to the work because the more steps I have, the better workout I get. It is Time-Variant because I can measure it in a certain amount of time.

As a commuter, I use a time KPI measuring how on time my train normally gets to campus from my house. It is specific for obvious reasons are measureable regards to whether or not they hit the achieved time. It is also relevant because I need to be on time to get to class. My KPI is completely measured on time performance

I use the KPI of how long it takes my team to warm up before tournaments. It is specific and measurable because we have a set number of golf balls we hit and a set number of time we hit each club. It is attainable because we record this to better schedule our travel. It is relevant because in college golf, the practice areas are hectic, so having a routine adds structure. It is time variant because we can allow ourselves the same amount of time each week.

A KPI I use regularly is the percentage battery my laptop and phone. It is a specific and measurable because it gives a numerical value to show exactly what percentage your device is on. It is achievable because you can take your device off the charger when you reach the percentage you want it to be on.

I like to go to the gym daily and while I am there, I like to keep track of my progress. I do this by processing what the machines tell me. They help me track my calories burned, miles ran, and my heart rate. From this information, I decide if I need to increase my level or keep my level constant. This is specific because it is measuring just only my performance. It is measurable because all of the recordings are in numerical form and the metrics are clarified. This is easily attainable, no matter how much or how little work I put in, the machine will still track my progress. It is relevant to me since I am trying to live a healthier lifestyle and it is time bound because my progress will be tracked for the amount of time I spend on the machine.

A KPI that I use daily is the amount of time I spend exercising each week. It is specific and measurable because there are certain exercises I do each day for a certain number of minutes. It is achievable because I can work to achieve whatever goals I set for myself each week. It is relevant because it helps me stay in shape and makes me healthier overall. It is time-phased because I can measure how much time I spend exercising each week.

A KPI that I use on a regular basis is time spent working out each week. This is specific and measurable because I can do different exercises everyday for a specific amount of time. It is achievable because I can complete my workouts in the amount of time that I want. It is relevant to me because working out helps me stay in shape and have a healthy physique. It is time-phased because I work out on a weekly basis and all my sessions can be measured for time it takes to complete the workout.

I use the KPI of how much water I drink per day by using a bottle with 16oz capacity. This is specific and measurable because I can use the number of bottles I drink per day times 16oz to calculate my water intake. It is achievable because I can compare my water intake with the standard of healthy water intake per day and see if I need drink more. It is variant relevant because water is important for my health. It is time-variant I wants to make sure I drink enough water and I calculate this around noon every day.

As a business student, one of the most important and obvious KPIs is profit. Profit is the value taken from the costs subtracted from revenues. That value is specific, it comes out to be one number and it is measurable using the formula for it. It is achievable, you can alter your costs and revenue to get more profit. It is relevant because everyone needs to know this, everyone uses money and this is how much you have left after spending. It is essential to keep track of this to know you have enough for your expenses plus extra. Finally, it is time specific because you can track your profit within a certain day, week, month, or year.

I use the KPI of the number minutes it takes me to walk from my apartment to class. This is specific and measurable- minutes and distance is a precise measurement. This is achievable- I can walk faster or slower to alter my results. Its relevant- the number of minutes has an impact on the amount of time I allow myself to get to class. It’s time-variant- I can take an average of the time over a week or month.

A KPI that I use on a daily basis is how much time I spend preparing for each course. This measurement allows me to see what classes i.m performing well in, and what classes i’m not. This KPI helps me manage my time better as well because i can evaluate my performance and see what classes i need to focus on more, and what classes i can focus on less. For example, In STAT 1102, i currently have a grade average of 97, and in MicroEconomics, i have an 80. This KPI will tell me to focus less on STAT and more on Micro.

A KPI I use at work is the number of patrons in the fitness facilities. Everyone has to swipe their ID to get into the facilities, so we can gather name and ID# and also how many times they swipe their idea. However, for my position, we solely look at the number of patrons, not who is coming in or how many times. It is specific and measurable because the swipe machines read each individual swipe (or tap, some IDs tap and swipe but they are only counted as one). It is achievable, because each calendar year we gather academic-year-end-numbers. We, of course, would like to see a gradual rise in numbers each year-end. It is relevant because as a department, we get more funding per rise in our departmental numbers. It is timely because we can measure by the hour, by the day, by the specified days of the week, by the month, and by the year, depending on what data we need.

A KPI that I often use is the time is takes me to drive from the Temple campus to my work (King of Prussia). This is specific and measurable because I am only timing how long it takes to get from Temple to work using a timer. It is achievable because I can try different routes to get to work faster. It’s relevant because being on time to work is important so I need to know an approximate travel time period to give myself in order to not be late to work. And it’s time-variant because I can measure how long it takes to get to work at different times of the day, and using different measurements of time (minutes, hours, etc.)

I have made one of those mistakes before. One mistake I made was number 1, Open a CSV file in Excel. I just clicked the CSV file and it wouldn’t open correctly so I asked a friend how to open it and he told me that I should open the CSV file in Excel.

I have not personally made one of these mistakes but the most important on to avoid is not knowing what system you are logged into. If you are not aware of the software and the capability of the program, you are more likely going to make more mistakes than expected. Also, if you are working with other people, there is more of a chance your errors will spill over to their work as well and make the whole project and task more complicated. This is so dangerous because it can go undetected for a period of time and the root cause can be hidden and not realized which magnifies the problem.

I have worked in Excel on many different occasions, but I have never made any of these mistakes. However, I would say that the mistake that everyone should try to avoid is starting to work on a database without doing a full backup first. It is good to periodically save what you are working on, so you do not lose it especially if it is for work and there is a deadline on it. Some vendors do say that they have free backup, but they may charge you when you want to retrieve it later. It is important to save your work that way you do not have to do it all over again. That is why starting to work on a database without doing a full backup is a mistake that everyone should try to avoid at all costs.

I do recall some of these happening, however I do not remember specific events and they were also very minor situations, therefore I am going to answer question number two. I think that #6, Missing the Data type, is a huge one to stay on top of. If you have the wrong data type, the data is basically useless. Excel sometimes tends to recognize the wrong type and it can throw off your whole project. A good example is a also mentioned in the article, and is when a date is recognized as an integer. Rather than a specific time, it recognizes it as a value, and this could mess up an entire analysis because rather than looking at the time as a specific time, it provides it as a numerical value, which in turn could go much higher than 12/24 for hours (depends if talking about military time or not) and for 60 with minutes.

I believe the biggest mistake to avoid is the leaving out of columns. The data entered into the excel spreadsheet is there because it is of significant value. To accidentally leave out columns, means the person interpreting the data will have false, or not entirely accurate, data. As a result, the actions taken based on the data given in the spreadsheet could lead to a disaster.

Since this class started I have made a few of these mistakes while working in Excel. In my opinion, the biggest mistake you can make is number three. When you start working on the database without doing a full backup first, you risk the chance that the work you did will get deleted or erased due to a computer malfunction or your carelessness.

Personally, I have never made any of the mistakes listed in the article, or at least I have not worked with data enough to make such an egregious mistake. I think the problem that is the most important to avoid, and easiest to avoid, is #3, or working on the database without doing a full backup. I think this mistake is applicable to the world outside of data, and it is always important to either save versions of your work progressively as separate files to ensure checkpoints of progress. It is an easy habit to get into, and if something were to happen, you would never lose ALL of your work, only the incremental progress you have made since your last save.

I downloaded CSV files when I was doing assignment one for this class. I did not open the file by the recommended way, but instead I just double clicked on the CSV files to open it with excel. I did not know that it would cause any errors. I was ignorant about this common mistake to I took it as granted and developed my hypotheses for the assignment. The data was converted into excel file but I never knew if it converted it properly or not.

I’ve never run into any of the problems listed in the article because I don’t really use Excel too much, but I think the most important is obviously not making a backup of a file. Computers and technology as a whole can have problems all the time and you may very well run into a problem in the middle of nowhere that ends up either corrupting your file or shuts down your computer. Without having the backup, you’d lose all your work and start back from absolutely nothing again.

I have never experienced any of these problems while working in Excel. I think the most important mistake to avoid is starting to work on the database without doing a full backup first. Without a full backup you can easily lose your data. The continuous backups should not be the only thing you rely on.

I’ve made mistake number 9: copy formulas that use relative coordinates. Doing so provided the wrong calculation for that cell, and then upon copying the formula down, it caused every subsequent cell to be incorrect as well. Unfortunately, it is difficult to detect such an error since excel will simply recognize and assume the formula entered is the intention, unless the prior cell contains a different formula.

I think mistake 3 is an important error to avoid. This error is starting to work on the database without doing a full backup first. While the other mistakes can seriously effect your results, nothing can effect your results more than not having anything because it is all lost. Like all important documents and information, it is important to backup your work as you go.

I haven’t made any of these mistakes because I’ve never worked with excel before. From reading the ones listed #2 “What System Am I Logged Into?” is a problem that would be extremely frustrating. This problem reminds me of playing a video game for a long time and neglecting to hit save before the game unexpectedly shuts down. With this problem, not only would you lose all the work that you have been doing on a clients project, but you’ve also created another problem by changing data that wasn’t supposed to be changed in the first place. One would then have to fix the incorrect updates, then go back in and make the correct updates to the other clients data.

I have tried to open CSV files in Excel for the first assignment in this class – the result was a mix of mistakes #6 and #9. The data were all messed up and compressed together because of the tiny allocated space in a typical cell, phone numbers and coordinates were auto-corrected to integers and because there was no data dictionary, neither the headers nor the data themselves made any sense. For #9, there are programs that can relatively deal with *.csv file types, but I would like to avoid #6 as much as possible because auto-correction of data types is not only a common problem, it is also very varied, hard to spot and clean efficiently.

I think the most important mistake to avoid has to be Number 3, “Start working on the database without doing a full backup first.” One may forget to backup the original data and if a mistake is made during the analysis then the data can be corrupted for good. By keeping the original one can have a backup in case a mistake is made.

The one mistake that I made was to work on a database without doing a full backup first. After making changes, I saved the new draft but realized I was missing some numbers that I needed because I deleted it. Now, I was stuck with a full analysis with incorrect data because of the fact that I did not save the first draft. If I had the first draft, I would have been able to look at the numbers and place it back within my saved copy.

I have made mistakes with number 3 the most. For whatever reason, there have often been power outages in Pearson and McGonigle Halls, and these power outages have occurred when I was working with data and Excel. Each time, I never seem to learn my lesson, however, and rarely save frequently.

In my experience with working with data I have not made any of these mistakes or I had possibly fixed them before they became relevant. Out of all of these I believe #3: Start working on a data base without doing full backup first is most important. Saving frequently is a habit I have began to form since high school. The computers were not always reliable and could crash at a random moment and I could have lost all my work before previously saving. It has become almost a fear to have completed hours of work that could disappear in seconds because of a crash, power outage, or other issue.

I have not personally experienced any of the specific mistakes listed in the article, however I definitely feel like the mistake that could be the hardest to “recover” from would be working on the database before doing a full backup first. All of the other mistakes can be remedied in some manner, and if not, you can always begin again if you have that full backup. Working on the spreadsheet after you’ve done a full backup can also allow you to try things with the data even if it may not work, because you know you have that backup just in case. Also, it’s important to have the original file untouched if you need to refer back to it for some reason along the way.

Since I do not work with Excel very often, I have not made any of these mistakes before. However, I do think that an important step to make sure you do not do is Miss the Data Type. There are many things that can go wrong with your spreadsheet if the program confuses a certain data type with another.

Because I don’t have much experience using Excel, I can’t recall an instance in which I made one of these mistakes. In my opinion, the most important mistake to avoid is number 3, “Start working on the database without doing a full backup first.” I think this is the most important because by not saving your data beforehand, you are taking the risk of making a critical mistake and not being able to refer to the original document in order to correct it. You are also in danger of losing all your work if something unexpected happens to your computer.

Throughout my schooling I have been required to take a computer class that is heavily based on Excel. In working with Excel I recall having problems with formulas and figuring out certain calculations, such as the number 7 mistake. I do not remember specifically the issues I have had, but I have become more careful in dealing with formulas to ensure there are no errors present. I believe the most important mistake to avoid is number 3. Without a backup you cannot have an original to look back to after a mistake or have the data if there is technology failure and things get deleted. There is a large risk of losing everything if you do not have a backup in place.

Although I have not made one of these mistakes, I think it is most important to do a full back up of the database. I always save a copy of my work be safe. It is very easy to make a mistake or to accidentally lose the work you have completed. It is also important to remember to save as you go so that way you do not need to worry about losing your work.

I have never personally made one of those mistakes. I think the most important problem to avoid would be to start working on the database but without doing a full backup first, because other problems on the list are the errors that people would make in excel, which means people can fix it as soon as they found them. However, if you don’t have a backup, once your computer breaks down or you forget to save your work before you close excel, you will lose your entire work and you will have to do it again.

I have made one of these mistakes in the past. I have clicked “yes” without carefully evaluating the message that says “do you want to remove this from the server?” I was working on an assignment when I did that and it deleted some of the data that I needed. Thankfully, I noticed the mistake towards the end of the assignment. I did it because I assumed that it was something that I was supposed to do because it popped up on my screen. I am now careful about reading and figuring out if I should click on things like that.

I have made one of those mistakes before, and it happens to be mistake number 10. It happened in our class in fact. When the class was assigned to look up data from the open data sites provided I downloaded a CSV file that had contained all of the Farmer’s market locations in Philadelphia. I had assumed that just because it had excel icon that it was able to be opened on Microsoft Excel but instead when I opened it, all I saw was lines of code and script. This is what I assume to be the large integers that Excel turns into scientific notation upon opening the file.

Two years ago, in my junior year of high school, I had an accounting course. In that class, I learned about and went through excel. I remeber the several mistakes the system can make. One mistake I remembered when reading this article was number six, miss the data type. Excel can misrepresent dates put in cells with integers, causing confusion. All of the mistakes listed are very important to avoid, but in my opinion, the most important are number six and number three, start working on the database without doing a full backup first. Not backing up your file at first and having the wrong data in cells from the integers can be a disaster for some users and cause them to restart.

I have not yet made any of these mistakes when using excel however I believe that number 3, start working on data without backing it up, is the most important problem to avoid when dealing with data. Starting work with data before a backup could be very dangerous if mistakes are made and it would save a lot of time to make a backup if a mistake is made. Also, people that forget to save or people who have computers that could crash when dealing with data would be thankful if they did create a backup.

I have worked in excel on my different occasions, but I have never made any of these mistake.However, I would say that the most common mistake people should try to avoid is to work on a database without doing a full backup first. It is important to save your work that way you do not have to do it all over again.

I think that the worst problem on the list to occur would be Number 3, failing to use a backup server. This problem stands out because it is common to many forms of technology, but could have especially bad consequences when one is dealing with large, organized data sets. It also seems like it could affect a wide range of people who work with data because it does not necessarily depend on the user’s skill. Even automatic backups fail to save some data, so it is important to ensure that everything is backed up before working with a database.

Clicking ‘yes’ without carefully evaluating the message that says “do you want to remove this from your server?” is a mistake I make most often when working with data. I am the farthest thing from computer savy, so I usually don’t just click “yes” or “no’ and hope for the best. I have most recently been coming across this issue in this class, because it is a computer based course. I have gotten better, but when working with anything other than the basic computer tasks, I blank.

I have never made any of these mistakes but I think that the most important mistake would be not knowing what system you are logged onto. This mistake can be very time consuming and can get you really confused. It can ultimately corrupt data and cause you to have to take several steps back in your process.

Although I have not personally made any of these mistakes myself, I believe that the most important mistake to avoid is not including all of the columns when sorting your datasheet (#4). Making this mistake would corrupt the entire datasheet making this variation useless. Hopefully you have a back up or 2 of a datasheet when you make this mistake because if you don’t, its not gonna be a lot of fun.

I have never really used Excel before in depth, but when i have, i have always worked with a lot of data. Because of that, i think one of the most important mistakes to avoid is not backing up your work. Saving the original work before you make changes is smart because if you make a mistake in your changes, you can always just reopen the original document and start over. Computers are not always reliable, so saving your work periodically is important so the data doesn’t get lost or rearranged in any way.

The main mistake I make out of the ten listed is number seven which is putting values in fields that are suppose to be pointers or references. When I was messing around with Tableau trying to figure out how everything worked, I was just adding whatever I could into any field and I thought it was weird that after I had put in so much information that I didn’t really have any graphs I could use. After realizing that I can’t just put anything anywhere, it became easier for me to distinguish what needs to go where so I could make relevant infographics.

Missing the Data type has been a big one for me. At work when Im working with dates and grades, EXCEL sometimes will have some trouble differentiating numbers as dates and numbers as grades. This, ultimately, leads to some confusion as there are a lot of questions in the office with some of the grades and what each numerical value inputted represents. I never was too good in EXCEL, which is why i hope the course will help teach me to avoid those costly mistakes.

I have made at least one of those mistakes in the article. More specifically, I have make the mistake mentioned in number 4. I have sorted a spreadsheet, and forgot to include all the columns. At work, I create a decent amount of spreadsheets to analyze and keep track of data. Every day a list of “New Hire” people is sent out. We have to put those people on the older spreadsheet and put it in alphabetical order. One time I sorted it alphabetically and realized that the new employees name did not match the other information because I did not sort it correctly. Luckily all I had to do was undo it to correct it.

I made mistake like miss data type. I did not know what to do with those data after that. I will pay more attention about this.

I have never made any of these mistakes on excel before, but the most important mistake to avoid when working with excel is to make sure your data is backed up before you start working. If you are working ad your worksheet fall apart you will lose all of your data. I don’t think I have to say how detrimental that will be if you lose all your data.

I think problem number 9 happened to me a few times. I would use try to use the formula on the whole row by highlighting one of the cell and scrolling down to the end. Instead of having the formula be used to calculate the data for the rest of the row, the data in the cell I highlighted is just copied all the way down. If I didn’t pay attention and catch the mistakes this dumb error may be quite “insidious”.

This data is interesting because we are all college students right now. Basically everyone that goes to college is trying to get a degree so they can get a job once they graduate. With all the money that goes into that degree, a lot of students are starting to wonder if it’s even worth it. This data proves that it’s worth it considering the fact that people with a four-year degree made 98% more money than people without one in 2013. This article also states that it was calculated, roughly, that college actually costs negative $500,000 in the long-run, not going to college according to the data collected would cost someone about $500,000.

http://www.wsj.com/articles/bosses-harness-big-data-to-predict-which-workers-might-get-sick-1455664940

These days companies are trying to help employees and keep them in good shape. This article is talking about how companies are gathering data from various wellness firms and insurers. They are using that data to see how many people get sick and get prescribed medications. For example, in the article it says that Wal-Mart is gathering data to see how many people are about to get diabetes. That way they can help treat their employees and prevent them from getting sick. The data they are gathering is kept confidential. They are gathering the data to help their employees and keep them safe.

http://fortune.com/2016/02/17/castlight-pregnancy-data/

This article is interesting because companies and employers can now use data to predict if someone is pregnant before she is ready to disclose that information. They are able to do this by accessing worker’s medical claims, pharmacy claims, and search queries to figure out if a person is pregnant. It just shows that data is in our everyday life and its kind of impossible to hide from it because there are so many different way to access it. It also showed me that employers might know more about me then what I imagine and that can change my thought process or attitude while I am working.

http://www.theactuary.com/news/2016/02/life-expectancy-for-pensioners-highest-ever/

As an actuary, we use prior data to “predict” future outcomes. As I prepare to enter the insurance industry specific to retirement, it is interesting to see how prior data is used to predict that future lifetimes are increasing. This is important to me because as future lifetimes increase, future pension payouts will be greater. Therefore, this data is very important in considering how much money needs to be reserved for retirement, both for others and for myself.

As an aspiring actuary*

http://www.cnbc.com/2016/02/19/us-consumer-price-index-jan-2016.html
As a business major, this article in particular interested me as it’s about our economy in general. This article mentions that how in January of this year, many costs for things such as rent and medical necessities are beginning to rise. The U.S. Consumer Price Index has risen the most that it has since August 2011, so four and a half years. While gasoline prices have managed to fall, medical costs such as prescription drugs, doctor visits, and hospital costs have all slowly risen. It’s interesting to see this information because the rise of prices is also being used in order to predict whether or not the Federal Government will raise interest rates later this year too.

Zika Emergency Puts Open Data Policies to the Test

I have always been interested in Public Health and even considered it for one of my majors. I found this article interesting because it explains how the spread of the Zika virus could be stopped with the help of Open Data. It explains how the World Health Organizations is calling for Health journals to share the information that they have collected concerning the virus. They take it further that they should share information concerning any public health emergency. The International Committee of Medical Journal Editors has made available all data they have over the virus and they urge other journals to do the same.

http://www.sacbee.com/news/local/education/article61424987.html

This article is interesting because it shows how much of a gray area data privacy is. Cyberlaw is a fairly recent area of the law, and it shows. This is why data is such a controversy every time it is brought to court – nobody knows what to do about it. Yet the consequences are huge; just in this case, private school records of 10 million students up to 25 years old could be released. If such data were to be leaked, collateral damage would reach millions of dollars. There has been harassment and petitions thrown around and not nearly enough security to assure people that the data would actually be safe. After all, if a Twitter hacker could steal 20,000 employee records from FBI earlier this month, no data is going to actually be safe. The age of data is moving entirely too fast, and everyone else is struggling to catch up with the times through trial and error – and judging from this article, that is a whole lot of errors we have coming.

http://www.businessinsider.com/after-stock-crash-tableau-cfo-digs-in-2016-2

Business Insider emphasized on how tableau stock dropped 50% in a single day.They have a $2.2 billion loss in market capitalization. It was beating its 4th quarter expectations. The massive loss seems to stem from earnings expectations for the year ahead.

http://fivethirtyeight.com/features/to-kill-a-mockingbird-author-harper-lee-dies/
This article notes the permanence of Harper Lee’s posthumous influence on American culture. “Mockingbird” is taught by more high school teachers (35%) than any other fiction book. “Mockingbird” is also widely taught on college campuses as well, ranking 255 on a list of books mandated by syllabi, which also include various textbooks for a variety of studies. To me this was interesting because I also read this book in middle school, and was curious to see how large of an influence this text has nation-wide.

http://fivethirtyeight.com/features/not-all-privacy-policies-are-created-equal/
This article elaborates on how there are differences in privacy policies. I had found this data interesting since our class discussions on privacy breaches and the filter bubble. This data was interesting because I had never realizes that the policies are actually stating how they will be violating our privacy rather than protecting it. They focus on companies such as Google and Facebook which leads back to our class discussions, they only invade our privacy in order to personalize the content we view on their websites. This is relevant to me from the use of both of these sites and know having the knowledge to delete my search history in attempts to combat this and have some form of privacy on the internet.

http://fivethirtyeight.com/features/the-golden-state-warriors-odds-of-going-73-9/

One major story in the sports world is with Steph Curry and the Golden State Warriors basketball team. They are cruising through the NBA regular season, preparing to make a run at consecutive championships, but they also have an opportunity to break the season record mark of 72-10 set by Michael Jordan’s Chicago Bulls in 1996. It’s interesting just following the team because they are so fun but history is currently being made. The article talks about their odds to win and includes many stats and days visualizations to show their greatness. Fivethirtyeight currently gives the Warriors a 54 percent chance of getting to 73 wins. Regardless, of whether or not they get there, this brings excitement to basketball fans and this article wraps up what they bring into data.

Can Big Data Analytics Save Billions in Healthcare Costs?
by Christine Donato
Specializing in SAP HANA and healthcare technology, Christine has extensive background in sales enablement, social media marketing, and digital writing. She is a strong proponent of the positive impact big data analytics can have on personalized medicine and preventative care. Christine is local to the Philadelphia area yet has a strong passion for travel and adventure.

http://www.forbes.com/sites/sap/2016/02/22/can-big-data-analytics-save-billions-in-healthcare-costs/#4b87d56ff625

This article is very appealing to me as it describes how data can transform and revolutionize Healthcare system once it gets organized. Working with data in Healthcare system could be very difficult because of various inconsistent definitions and terms used by different doctors and used to explain patients. The inconsistency and unstructured data can be hard to aggregate, so Organizations like HISSS (Healthcare Information and Management Systems Society) are coming up with conferences that can help IT professionals, clinicians, executives, and vendors from around the world and show them different ways to improve the quality, cost-effectiveness, access, and value of healthcare through information technology. Digital transformation and usage of data is helping doctors to come up with unique treatment tactics which are different for each patient. This can provide personalized and precise and paced treatment to patients. Donato mentions that the usage of data and technology is increasing rapidly for personal health concerns via mobile apps and wearable devices that can keep track of every activity of a person. She describes how non profit societies like the American Society of Clinical Oncology (ASCO) can help doctors create treatments tailored down to a micro bucket and/or individual level and the way it will affect different people with different genes. Analyzing data of 97% of the cancer patients will allow societies like HISSS to acknowledge patterns and treatment effects by enabling better, more data-driven decision making. Usage and improvement of data in healthcare can provide proper treatment by analyzing patterns and cases that involve people with similar problems and at the same time get personalized treatment according to genes and resistance of a patient.

This article recaps some of the newest tech innovations that was shown at the recent Mobile World Congress (MWC). This year there was a common theme of using data to make urban cities run more efficiently. For example data from cars are being recorded transmitted to big data repositories. Analysis can use data from car crashes to quicken emergency response. As a big player in this field AT&T has invested in tracking sensors on pedestrians and office workers in their move to space planning. A few smart cities examples that was show cased at the show include a solar power pedestrian sized parking meter in Paris where the display give users information on nearby shopping and points of interest. It can be programmed to accept payments for train tickets as well. In Australia, some meters along the beaches even gives surfer insight on the day’s waves.

http://fivethirtyeight.com/features/the-same-four-operas-are-performed-over-and-over/
Although I know virtually nothing about operas and am not very interested in them, this article caught my attention. I found it interesting that the same four operas were being performed over and over again. This article discusses how the Metropolitan Opera will be including four very common operas in its 2016-17 schedule. These four operas are Aida, La Boheme, Carmen, and La Traviata. There is a visualization showing these four operas with three other operas that will be performed next season. This visualization shows how frequently these operas have been performed since 1883. There are very few years where none of the four common operas were performed. There are also large spans where those operas were performed in consecutive years. The article shows that the Met is struggling to make new operas for new opera goers, while trying to maintain its current audience of opera lovers. The article also stated that opera houses have experienced a decrease in attendance over the past few seasons. Even though I am not that interested in opera, I would like to see how they progress over the next few years.

http://fivethirtyeight.com/features/the-golden-state-warriors-odds-of-going-73-9/
This article is interesting to me because I am a huge basketball and a fan of Golden State Warriors’ star Steph Curry. I think the article does a great job of pointing to several different sets of data that add to the original topic of the team’s odds to break the record for most wins in a season. From the data presented, it seems like they do have a pretty good chance! It’s been interesting to see how data analytics has become such an important part of professional sports, and I’m curious to see how its role changes in the future.

http://www.wsj.com/articles/trump-cruz-make-final-stops-in-nevada-before-caucuses-1456257635?cb=logged0.40556541783735156

http://www.wsj.com/articles/trump-cruz-make-final-stops-in-nevada-before-caucuses-1456257635?cb=logged0.40556541783735156

The obvious choice for an article about data in recent news is an article about the presidential race. This article discusses Cruz and Trump putting more focus on their “offensive” ad campaigns, which is due partially to the results, or data, of the primary state elections. The candidates use this data to know whether they are the front runner of the race or a straggler.

http://www.nasdaq.com/article/bosses-harness-big-data-to-predict-which-workers-might-get-sick-20160216-01321
This article is explaining how companies are using data such as where people shop, whether they vote, and credit score to make predictions about employees’ health. I find this article extremely interesting because these factors seem unrelated to a person’s health. Employers are using these tactics to minimize the costs of medical care and reach their employees about improving their health before it becomes a serious problem. It allows employers to reach their employees and try and help them in a different way than has been used before. It is also a quite controversial topic. A question of privacy comes up because some individuals may not be comfortable with an employer accessing their private information and records. This is a very interesting technique used by employers and I am interested in how it will continue to be used (or not) by companies.

http://blogs.wsj.com/digits/2016/02/22/most-americans-say-apple-should-help-unlock-terror-suspects-iphone/?mod=ST1
This article talks about America’s opinion on the FBI’s attempts to have Apple create a backdoor that they can use to access IOS allowing them a more effective means to track down terrorists. This interesting part about this article is not the subject but that 51% of the people surveyed said that Apple should create the backdoor. If this policy were to come to fruition, it would pave the way for a whole new set of policies that would limiting our privacy rights. Another situation that can arise from this is if someone got access to the backdoor who shouldn’t. IOS is one of the most used software in the world and if a hacker were to find a way to get access to that back door it could lead to a lever of cyber crime that we have never seen before. Worst case scenario a terrorist organization could gain access to it. This leads me to wounder what percentage of the surveyed population have any kind of knowledge into these types of matters or if they are the typical american who thinks that anything that can fight terrorism is immediately a good thing for everybody.

http://money.usnews.com/careers/best-jobs/financial-adviser
This website was very useful for me because I am pursuing the career of a financial advisor. This website gave me the necessary data to further increase my interest in the financial advising career. It gave me the median, high, and low salary; unemployment rate; and number of jobs. It also gave me a scorecard on future growth, stress, work life balance, and job market. Lastly, it gave me the ranking compared to other occupations. These are all useful information for me and helped me decide to continue to pursue my career.

http://www.pgatour.com/statsreport/2016/02/22/strokes-gained-northern-trust-open-riviera.html My article is the strokes gained data from last week’s PGA Tour event in Los Angeles at Riviera Country Club. As a college golfer, I am always trying to use professional data to understand the best way to shoot low scores. I can look at numbers from different situations and players and use them to make myself better when I am in the same position. I use stats such as strokes gained to know percentages and to make risk/reward decisions on the course.

http://fivethirtyeight.com/features/republican-leaning-cities-are-at-greater-risk-of-job-automation/

I title of this article immediately caught my attention because I am a Republican. In addition, anything about job industry growth catches my attention because in a few short years, I will be entering the work force as a college educated professional. The facts in this article directly relate to me. For example, it states that jobs, such as cashiers, will most likely be replaced by machines. I am currently a cashier at my one job. I found this article interesting. It says that Republicans should fear for their economy more than Democrats, but my hypothesis would probably be the other way around. I wonder why Republicans have more jobs that can be replaced than Democrats.

http://www.wsj.com/articles/justice-department-seeks-to-force-apple-to-extract-data-from-about-12-other-iphones-1456202213

The government is currently in the process of taking Apple to court. The government wants access to extract data from iPhones, however, Apple’s CEO Tim Cook is refusing. Apple is arguing that helping the FBI could endanger Apple’s users, therefore threatening the trust between Apple and its customers. As an Apple user, I find this whole situation very interesting. I can understand the situation from both sides. The FBI wants the data to help solve a terrorist case, but Apple wants to protect and respect its customers. I personally like that Apple is resisting. It shows that they truly care about their customers’ safety and privacy. We should not have to worry about the FBI being able to hack into the data on our devices.

http://aiddata.org/subnational-geospatial-research-datasets
I found this open data for international development. I am interested because I learned what open data is from class. This article is about sub-national, geospatial research datasets. This article introduce what benefits open data are and how thing is going in AirData. There are so many date in it, and I am so excited about open data.