Instructor: David Schuff, Section 001

Weekly Question #2: Complete by January 28, 2016

Leave your response as a comment on this post by the beginning of class on Janaury 28, 2016. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your opinions, not so much particular “facts” from the class!

If you sign in using your AccessNet ID and password you won’t have to fill in the name, email and captcha fields when you leave your comment.

Here is the question (well, it’s not really a question):

Find a online article dated within last two weeks from a credible source that has something to do with data. It can be about the role of data or an interesting data-driven analysis. It should also be relevant to your major and of interest to you. Copy and paste the URL directly into your response followed by a few sentences that explain what is interesting about it.

You can use any of the sources under the “Great Data Sites” menu on the right sidebar of this page, or you can use any online news or magazine site.

59 Responses to Weekly Question #2: Complete by January 28, 2016

  • Link- http://www.shrm.org/hrdisciplines/staffingmanagement/articles/pages/protecting-candidate-data.aspx

    In class we talked about how millions of people have had their personal information compromised and exposed due to hackers. In the article, Your Candidate Data, it discusses the steps and measures that HR professional should take to protect employee and candidate information. It also discusses different systems that HR professionals should use to protect employee’s and candidate’s personal information.

  • http://fivethirtyeight.com/features/why-isnt-anyone-talking-about-the-deficit-anymore/

    This is an article talking about how politicians barely mention the deficit anymore. This interests me because the deficit still exists and could cause a financial crisis to our country even though it shrank a little. Why isn’t it a hot topic and being spoken about in the 2016 election like it was back in the 2012 election?

  • http://www.pewsocialtrends.org/2013/12/11/on-pay-gap-millennial-women-near-parity-for-now/

    According to data analyzed by the Pew Research Center, the gender pay gap for millennials is narrowing sharply. Among workers ages 25 to 34, women’s hourly earnings were 93% those of men. Despite this trend, significantly less women report being interested in top management positions than their male colleagues. This difference is greatest among working adults in their 30’s and 40’s, the age at which many women face the trade-offs that go with work and motherhood. I chose this article because as a psychology major, studying organizational behavior, I am interested in the decisions people make concerning work and the environmental factors that shape those decisions.

  • The article I found from Business Insurance is about the role of big data in improving the way insurers do business. As my major is Actuarial Science, I find this article interesting because it explains the importance of big data in being able to more accurately price insurance, which is a job I could be doing. Larger insurance companies that compile big data could actually use it to personalize insurance plans for individual customers. This would virtually eliminate competitive pricing, making insurance more affordable for the general public.
    http://www.businessinsurance.com/article/99999999/NEWS040105/399999705

  • http://www.forbes.com/sites/bernardmarr/2016/01/20/how-big-data-is-disrupting-law-firms-and-the-legal-profession/#61910c135ed6

    The Article I found on Forbes, “How Big Data is Disrupting Law Firms and the Legal Profession”, is not about big data being disruptive at all. Instead, big data has positively impacted lawyers. When lawyers prep their cases, they look back at previous cases to better estimate how their case might be ruled. With 350,000 court cases in the U.S. just per year, it is difficult for lawyers to find exactly what they are looking for. Advanced analytical algorithms are making the jobs of lawyers easier. For example, Ravel Law allows lawyers to explore every decision a judge has made to find out which judges would be most biased towards their arguments. It is interesting to see how technology could impact and be helpful to my possible future career.

  • http://www.forbes.com/sites/toddhixon/2016/01/04/the-venture-investment-outlook-for-2016-discontinuity-and-new-beginnings/#5ffa66fe43cb
    This article is about investing and how 2016 brought in a discontinuity instead of a balance. I am an actuarial science major and since my major relates to the risk associated with doing anything in the world, I decided to choose this article. This data can be used to study the pattern in digital health funding and how technology has brought in a lot of changes. This data can also be used by people who are thinking of investing in new stocks, so that they know where to invest. I found it interesting because I am still an AS freshman and reading about investing brings a new edge to the way I see my major and this article surely helped me to understand how investing works in the mind of an investor.

  • http://www.informationweek.com/big-data/big-data-analytics/8-ways-to-monetize-data/d/d-id/1323932

    “Where knowledge is power, data is wealth.” This article about monetizing data is about how most companies in today’s society have an abundance of data but have little understanding or scarce resources to use it for their benefit. By “monetizing”, the author means using it for the company’s advantage and expanding or changing their business model because of it. The author of this article believes that if data is used more efficiently and effectively, fraud and piracy will be easily detected before large damage is done and more positive things may also occur such as being able calculate customer satisfaction with properly designed surveys. Being a Risk Management major, I found this to be very interesting because if secure data can be used more effectively, it can greatly reduce risk organizations face in all aspects.

  • http://fivethirtyeight.com/features/cavs-fire-coach-david-blatt/
    I chose this article because I’m interested in majoring in sports management and very interested in sports. This article that is about the dismissal of the Cavaliers’ head coach is very interesting since the data in the table shows that the team did a good job in the season. The data explains that with a 30-11 record he is the best coach ever who got fired. Also, the team is a little bit better than their preseason win total that was 56.5 wins. Now the prediction is that they would have finished the season with a 61-21 record with their fired head coach.

  • I found this article interesting because it shows pretty clear data who will play in the Championship games as well as how well these four teams have played and how they will play. This article speaks about these two games being the NFL’s best final four defensive teams to play in the championship game. Neil Paine shows us in this article how the statistics of these four teams are calculated and explains to us why these two games will be very exciting and great games. One reason I found his article interesting is because I actually got the jift of why these two games are going to be very well played. Also I understood how the data of their season record played a big part in showing that these four teams are very well rounded teams and are very well more than equip and prepared to play these games.

  • http://phys.org/news/2016-01-big-parties-voters.html
    This article talks about how big data has now allowed U.S. parties to know who all the voters are in the United States. Political parties use this data to better target potential voters and they also can use this data to figure out voters who will not vote for them, allowing the candidates to reduce their campaign expenses. The data that parties collect include voter’s age, address, and election participation history. This is just another example of how big data can be used to separate information and allow people to use it. This gives parties the opportunity to see kout possible voters and distinguish those who will not vote.

  • http://www.accountingtoday.com/news/tax-practice/taxact-detects-data-breach-and-suspends-customer-accounts-76985-1.html

    This article is about a data breach regarding an accounting software that had the personal information of many customers stored in the software’s database. TaxAct is the name of the software that was breached. I found this article interesting because a) it has to do with accounting software (accounting is my major), and b) the article ties together cybercrime, something we just discussed in my risk management course, as well as data breaches, which we had just discussed in our MIS 0855 course last week.

  • http://www.wsj.com/articles/global-stocks-fall-on-oil-and-china-woes-1452850130
    This article on The Wall Street Journal uses various sets of data such as oil price in the last few months and during 2008 and how they correlated with some of the indexes such as the S&P 500, DJIA or Shanghai Composite. I find it interesting because people are saying that the market is down marking a sign it’s 2008 again and this article uses data to decide if that’s true or not.

  • Link: http://www.wkyc.com/sports/nfl/browns/cleveland-browns-feel-analytics-are-not-new-to-nfl/21131641
    This article is about the Cleveland Browns new Chief Strategy Officer, Paul DePodesta. Paul is one of the main characters from the hit novel and film, Moneyball. The article discusses how even though DePodesta will be bringing new analytics strategy to the organization, the use of analytics is not new to the NFL or the Browns organization. NFL teams have been using analytics to decide which player to draft or what play to call on third down. DePodesta highlighted the importance of using information to make better decisions, and as we learned in class information is a product of data. He also mentioned the importance of seeking not only information, but better information. DePodesta will help the Browns turn that better information into knowledge to make better decisions. As a Management Information Systems major with a minor in Business Analytics, I plan to use data to help an organization make better decisions.

  • http://ww2.cfo.com/management-accounting/2014/03/accountings-big-data-problem/

    This article was interesting because it talks about the problem with big data and how it affects accountants. This article goes into detail about how accountants are not able to process the data nowadays to understand how a company is really doing, since they only do financial statements and audits for companies. The problem with big data, however, is that nobody knows how to interpret data, and accountants are always interpreting data. A possible solution to interpreting the data is having accountants try to dismantle the meaning behind data and apply that to how well a company is doing through customer service.

  • In this article, author Dennis Hung talks about the importance of big data in relation to social media marketing strategies. One of his first points is that social media is a part of big data. Things such as likes, shares, and retweets are data that companies can now use to help gauge consumers’ opinions and brand awareness. He also talks about how big data adds a more accurate way to predict customer behavior and will thus help companies formulate more refined and effective marketing strategies based of off this data.

    Link: http://tech.co/impact-big-data-social-media-marketing-strategies-2016-01

  • http://fivethirtyeight.com/features/tom-brady-couldnt-take-the-pressure/
    This article was interesting because of the relevance it had to the AFC Championship game from Sunday. In this article, the data shows that Tom Brady has a drop in his QBR of 75 points when he is under pressure, which is the 3rd biggest drop off in the league. This is interesting because if you watched the game on Sunday, you would have notice the Broncos pressuring almost on every down. Not only did the Patriots lose the game, Tom Brady did not play well.

  • http://nymag.com/thecut/2016/01/pretty-girls-get-higher-grades-and-lifes-unfair.html?mid=huffpost_women-pubexchange_facebook
    This article talks about the relationship between “pretty girls” and getting good grades. The study done here shows that female students people generally found attractive, had higher grades than other students. I thought this was interesting because I’ve sometimes heard that teachers favor more attractive students, thus resulting in better grades. Although this article doesn’t explicitly say that teachers favor more attractive students, I do think that is correlated to more attractive female students getting higher grades. Attractiveness alone isn’t statistically related to getting better grades, as far as I’m concerned, so I think that teachers favoring more attractive students has to be related to why “pretty girls” get better grades, in terms of this article.

  • http://fivethirtyeight.com/features/december-jobs-report/
    This article is interesting because the job market is something that affects all students because we are all future perspective employees. A students worst nightmare is to graduate from college with a hard earned degree, and there is no lucky pot of gold for them at the end of the rainbow. There were 292,000 jobs added by American employers, and this was the biggest gain of the year. If this trend continues, the economy will continue to improve, and create even more jobs. This brings a smile to my face because I am a Human Resource major, so the more jobs there are, the more in demand I will be.

  • http://espn.go.com/nfl/story/_/id/14609505/an-average-nfl-quarterback-now-stats-great-quarterbacks-years-achieve-nfl
    This article is interesting because it take statistics of NFL QBs from the last few decades and compares them to the NFL QBs of today. In the comparison, they highlight what stats were seen as average back then, and what QB stats are seen as average today. It’s interesting to see how much the game has changed offensively because what was expected from an average QB in previous decades is now seen as poor if you look at the expectations of todays QBs.

  • http://flowingdata.com/2016/01/19/how-you-will-die/
    This is an article explaining the types of deaths that claim the most people in today’s society. They measure their information on victims of all ages, and how they died, like for example by external causes or an infection. You can pause the simulation at any time with your age, gender and race to receive an accurate description. The most prominent cause of an adult’s death is cancer.

  • http://flowingdata.com/2014/05/29/bars-versus-grocery-stores-around-the-world/
    This article is about Bars Outnumber Grocery Stores in domestic and in foreign countries, it’s interesting because the food is fuel for the human bodies whether you walked on the land or swimming in the ocean food source is needed. “Google Places API” supplied most of the date and Google map directory give a visual view of a data collection, and it collected from the various part of the world. This data showed the world map of Bars (alcohol) verse Grocer stores (food). In some counties, Bars is out numbers grocery store, such as United Kingdom (58%), Italy (73%), France (81%), and Spain (303%). They have enormous ratio gap between bars and grocery stores; maybe they are high because Europeans likes to drink, or maybe is high dense populated business areas. When it compares to the United States, bars verse grocery store surprisingly grocery store out numbers bars, the data showed a correlation in the density demographic of the population. It showed Wisconsin’s bar ratio of are 2.7% than compare to rest of the United States (1.5 bars per 10,000 people).

  • http://www.scmp.com/tech/innovation/article/1903491/alicloud-launches-big-data-platform-alibaba-subsidiary-aims-make-new

    This article talks about the most big Chinese Ecommerce company Alibaba launched big data platform. It offers 20 solutions including processing, analysis, computing engine, machine learning and data application. The most interesting to me is that Alibaba company also announced a strategic partnership with US technology company Nvidia. They will develop a GPU-based, high performance computing cloud platform. For a student who major in international business just like me. I see a bright future in Chinese internet market, more and more domestic internet company would seek this kind of international cooperation with high-tech company in the U.S.

  • Link: http://www.slate.com/blogs/future_tense/2016/01/13/researchers_use_smartwatch_accelerometer_and_gyroscope_data_to_keylog_pins.html

    This article struck a chord in me by showing the important role of data nowadays. In fact, there is an undergoing research using a Recurrent Neural Network-Long Short –Term Memory system in order to determine how accurately a person debit card PIN can be retrieve just by analyzing data from a smartwatch. Consequently, a smartwatch app was used to send motion data, including data from different number pads in diverse conditions to a server via Bluetooth for analysis. Moreover, an algorithm was created to identify the keystrokes Seventy-Three percent of the time; compared to an ATM number pad, the algorithm was Fifty-Nine percent accurate. I believe this data analysis will put in question the security vulnerabilities of the model’s performance in the real world.

  • https://www.fbi.gov/news/stories/2016/january/countering-the-growing-intellectual-property-theft-threat
    The FBI and other law enforcement agencies have always relied on information from sources as a method for determining where crimes are happening. The advent of the internet and the increasing interconnectivity of the world has created a suite of new problems and new solutions for the country’s federal law enforcement agency. In this article, the Bureau talks about the ways they are using data from online businesses to help reduce intellectual property theft. Additionally, they discuss some of the improvements they’ve made in their infrastructure. Up until recently, the different Divisions with in the FBI operated a bit like individual fiefdoms: the special agents in charge of each section worked their cases with their teams with limited information sharing. By enhancing the relationships between sections, and other agencies, as well as increasing awareness of crimes and increasing data collection on related incidents, the FBI is taking steps forward to better protecting intellectual property.

  • http://www.motherjones.com/kevin-drum/2016/01/raw-data-how-white-are-academy-awards-anyway

    I found this data set to be very interesting, especially in the present time when there is much criticism of the Oscars for being “too white”. It is becoming widely believed that the Oscars don’t allow very much African-American representation when it comes to their awards given for acting, and this data set gives a very effective insight to the exact numbers. The graph on this website shows that the amount of black nominees in every decade since 1936-1945, save for 1976-1985 (when the amount of black nominees from the prior decade dropped ever-so-slightly; about one half of a percent). Since 1936-1945, when just one half of a percent of Oscar nominees were black, the number has risen to about 9%, which is still rather low, but rising nonetheless.

  • http://www.adweek.com/socialtimes/how-are-people-really-using-snapchat-infographic/633305

    This link leads to an infographic displaying how users spend their time on Snapchat. It is interesting because Snapchat seems to be on of the most popular social media apps right now. Some interesting statistics: users are 9x more likely to watch Snapchat ads in full than on other platforms. Additionally, almost no one spends money on Snapchat, with only 13% sometimes or rarely making purchases.

  • http://technical.ly/delaware/2016/01/26/go-something-cool-delaware-snow-plow-data/
    Former Philadelphia Chief Data Officer, Mark Headd, posted DelDOT’s plow locations during this weekend’s snow storm. The data showed how many plows were active during a given period and which locations were plowed at what time. It’s interesting to see because my family has a house in Delaware and I wanted to see if Delaware was more efficient than Philadelphia. Using the data, I saw that my Delaware house was plowed a day before my house in Philadelphia.

  • http://fivethirtyeight.com/features/tom-brady-couldnt-take-the-pressure/
    This article was published after the AFC championship game when many fans saw Tom Brady struggle against the Broncos pass rush. The article talked about a quarterback’s qbr rating in respect to the amount of pressure that they receive from the opponent’s defense. It has been a known fact for years that Tom Brady struggles when he gets pressured heavily. His qbr dips about 75 points (which is a very significant amount) which puts him in the same tier as some of the league’s worst starting quarterbacks such as Blaine Gabbert.

  • http://www.forbes.com/sites/bernardmarr/2016/01/26/how-big-data-and-analytics-changing-hotels-and-the-hospitality-industry/#6c4aa7e4b399
    This article talks about how Hotels collect data to try and better the stay of its customers. Hotel chains all over are using whatever they can to try and make there hotel more appealing. For example Marriott uses data sets like weather reports and local events to see how busy they might be during that time, which allows them to set prices with optimum efficiency. I find it interesting because I enjoy traveling very much and with the hotels using reviews to better their hotels and using future events to account for a busy period and lowering the prices help me find one that fits my budget.

  • http://www.pewinternet.org/2016/01/14/privacy-and-information-sharing/
    The article I found highlights privacy issues within stores and other public environments. People are becoming more aware of this, and though some consumers are still willing to give up information for the product they wish to buy, it is increasingly becoming an issue of losing trust. The rising issues of privacy range from video camera installation to monitor theft, to exchange for personal information for store customized credit cards.According to Pew’s article, 32% of consumers find these tactics “unacceptable.” As a marketing major, this is so important. I constantly need to be researching what makes a consumer loyal to a business, and if this is breaking trust, it needs to be monitored and adjusted. As far as what we’ve discussed in class, I can relate it back to the article about the government monitoring our phone activity. As we increase the amount of data we have access to, our privacy is being threatened more and more.

  • http://www.businessnewsdaily.com/8739-entrepreneurs-financial-risk.html
    I’m an entrepreneurship and innovation management major in the Fox Honors program, and people can’t help but asking the question ” What kind of job can you get with that?” or “How do you plan on financing your own business without a real job?” among other fairly insulting inquiries. This article was a pleasant affirmation for me, citing statistical research of both failing and successful proprietors. The article stated that professionals who started a new venture and failed within two years did not take great losses, and can easily return to the salaried workforce. It also noted that successful business owners make about 10% more in their careers than their salaried peers with equal qualification. I honestly did not expect to find a positive article about my field of study, and it is good to know that the numbers should fall in my favor regardless of where I choose to take my career out of school.

  • http://newpittsburghcourieronline.com/2016/01/25/pa-unemployment-rates-dip-below-national-average/ This article shows data about unemployment. This is helpful to me because it shows my likelihood of getting a job and the range of unemployment by jobs in Pennsylvania.

  • http://www.pewresearch.org/fact-tank/2015/12/14/americas-middle-class-is-shrinking-so-whos-leaving-it/

    My article is about the shrinking middle class and what job industry are moving toward the upper middle class or higher and what jobs are closer to the lower middle class or lower. In the article, finance, real estate and insurance qualified as upper class where as sales and retail had the smallest growth and also represent a large portion of the lower income class. This article is relevant to me because as a business major, it is good for me to see where my job will place me in our economy.

  • http://medcitynews.com/2016/01/limelight-health-aggregated-insurance-data-update/ . A lot of the data sets we talk about and look at in our in class examples are data sets thats focus is on convenience, and helping people make decisions more easily based off of convenient and easily accessible data. In this article, Limelight health, which is a health insurance agency, developed a tool, a web application that aggregates insurance data to make it easier for employees to compare benefit options. This type of data set helps save a lot of time, and work on the insurance company itself.

  • http://www.forbes.com/sites/louiscolumbus/2016/01/24/89-of-b2b-marketers-have-predictive-analytics-on-their-roadmaps-for-2016/#10264d5cd291
    I found this article interesting in that so many companies already implement analytics. 49% of companies already use it and another 40% plan to implement it in the next 12 months. This means that within a year 89% of companies will be using some form of data analytics. This just goes to show how important data is to companies.

  • http://www.entrepreneur.com/article/253837
    This article is explaining how many franchises have been using “big data” in recent years to help with customer satisfaction against competitor companies. It goes on in detail how Dominos Pizza is one of the most advanced companies in the business when it comes to collecting and using “big data”. Dominos has been collecting data since the late 80’s and early 90’s whenever a customer would order and have been using it to their advantages today. By using the data they have been collecting they can predict things like, “Ms. Smith on Oak Lane is a vegetarian and will respond to discounts on veggie pies. And you’ll figure out that on game days, the high school students in the 68022 ZIP code inexplicably crave pineapple on their pizzas”. Not only have Dominos taken advantage of collecting raw data and analyzing it, but other franchises such as Great Clips, Marco’s Pizza, and many other companies saw the advantages of it as well. Overall, as collecting data becomes easier in todays technological advances, more businesses are seeking this route to gain the upper hand on their competition.

  • http://insidebigdata.com/2016/01/27/top-12-explanations-youll-hear-in-2016-for-why-big-data-isnt-paying-off/

    This article is amazing. We, as of business students, all understand how valuable and potential big data is. However, this article stated otherwise. The author – Daniel Gutierrez claims that there are various reasons why big data is not much of a good investment. Some of the main reasons are: There are not enough data scientist out there. Which is, indeed, quite true. How to solve big data relies a lot on creativity; thus, the more available it is to individuals like us, not only the scientist, the faster those data would be transferred to information. Or another problem is the amount of data out there, what he sarcastically called data-lake scale, is humongous, there are not enough computers or devices (well, if there are any) that has the capacity to work on these data. Overall, this is not a rejection to big data, but more like a wake up call for us to the reality of how big big data really is.

  • http://diginomica.com/2016/01/25/what-we-should-really-be-watching-financeaccounting/#.VqlfZ5Nri9Y
    This article discusses how big data helps accountants (my major) ensure that P&L documents are accurate as well as find fraud in firms operating activities. Instead of auditing annually, accountants are able to audit companies year round. This continual evaluation of big data that shows financial positions of various companies help these same companies maximize their profits. This article shows clear connections between the use of big data and a firm’s success.

  • http://www.datasciencecentral.com/profiles/blogs/data-science-uber-for-law

    This articles interest me because it was about lawyers charging an expensive rate for service and comparing the price of service to Uber prices using data science. Stating the inefficiencies of law would require data science. A lawyer doing such will be know as a “Algorithmic Lawyer”. Inventing this kind of mechanized processes are non existent in the law world and consumers can bid on cheaper charges from lawyers. Also allowing lawyers to learn and practice using data analytics assuming it would make a more well rounded law profession.

  • http://fivethirtyeight.com/features/how-much-do-we-need-to-know-to-predict-the-oscars/
    The title of this article is “How Much Do We Need to Know to Predict the Oscars.” I was interested in this article because I think FiveThirtyEight is a fascinating website. I was impressed that they were able to accurately predict the presidential elections using data, so I have no doubt that they will be able to predict Oscar winners as well. The premise of the article was interviewing the people responsible for two vastly different data models: one very simplistic with only two inputs (how much money the movie made and its score on Rotten Tomatoes) and one which used dozens of sources to predict multiple categories. However, the two models ended up being vastly similar in their results even though they used different methods of achieving them. For example, they both agree that it would be very shocking if Leonardo DiCaprio did not win best actor for The Revenant. I am curious to see how their other predictions pan out.

  • http://fivethirtyeight.com/features/is-pre-k-all-its-cracked-up-to-be/
    Pre- K is a growing instituion in the unites states. Notable figures such as President Obama have made increasing the spread early education policy. Recently however, a study by Vanderbilt University has found that children who participate in pre-k faired worse academically in their later years. This has ruffled quite a few feathers in academia, particularly the feathers of the University of Chicago. The University of Chicago are now in quasi-feud with Vandy, bringing a smorgasbord of arguments criticizing the reliability of the study and its methods.

  • http://fivethirtyeight.com/features/the-republican-party-may-be-failing/

    This article interests me because this election is very prominent regarding my life. As a 1st semester senior, whoever is elected president in this election will impact the world i live in as a young professional. Further, as an Econ major, I have gotten into the politics of this election period. The statistics included regarding the probability each candidate has to win the election are further interesting because typically the only measure of success the public sees are the polls the media release, which are often wrong due to sample size and other errors we discuss in class.

  • http://fivethirtyeight.com/features/the-stock-market-is-not-the-economy/
    I found and article titled, “The Stock Market is Not the Economy” where a lot of important issues were discussed about the economy. The article uses data to support certain claims by the author, for example, one piece of data was used to determine how many job postings on Indeed.com were still posted after a certain period of time. The data was used to assess employment information in regards to our economy. As a finance major, I found this article interesting because many people believe that if the stock market is down, our economy is down. This article helped to prove otherwise.

  • http://motherboard.vice.com/read/what-happens-to-the-data-collected-on-us-while-we-sleep
    The vice article here is about the possibilities that come from the data from wearable health and fitness trackers being leaked or otherwise sold. It really stresses the importance of health data, and especially how valuable it is. The focus is on the value of that data to a huge variety of outside buyers. Whether the company that receives consumer data is selling the data or not, it is at risk of being distributed. It”s really interesting to me, because while I wouldn’t mind some of that data being available, the idea of all of it being available is enough to make me have no interest in the devices. It is related to my major, MIS, because it involves data in business.

  • http://www.dataversity.net/2016-trends-in-data-analytics-more-hands-take-hold-of-the-power/
    This article is discussing in 2016 how data has become more prominent in the business field. I am an international business major, reading this article made me realize that even though I don’t have a major such as MIS or data related I realize that I still will be incorporating in data in many ways I never thought I would have before.

  • This article was interesting to me because it is about how insurance carriers are using big data to deliver highly customized and versatile insurance plans. I am a risk management major in the employee benefits tack, and one of the major goals is to gear benefit packages to meet each employees needs. Every employee has different needs based on their stage in the life cycle, and the use of big data could help better meet these.

  • http://www.wsj.com/articles/the-data-breach-you-havent-heard-about-1453853742
    This article, by the wall street journal, is about a data breach of the US government by foreign hackers. This has been happening for three years, and this has gone largely unnoticed due to the nature of the breach. This is interesting to me because its unfathomable that this could be happening for so long and has just been discovered.

  • http://www.wired.com/2016/01/in-a-huge-breakthrough-googles-ai-beats-a-top-player-at-the-game-of-go/
    This is a pretty interesting article about the Google AI system named AlphaGO beating the top players in the game of GO, this article really shows the importance and power of data.
    This system is developed by analyzing large amounts of data to learn, not only from every possible outcome by professional players also from its own experiences generating its own data.
    In the game, Alpha Go can process large volume of data and figure out the insight of human experts or more efficient way that human experts don’t even know.
    It also mentioned that online services like Google, Facebook, Twitter are keep “learning” from all the data they can access with the technology of reinforcement learning.

  • http://customerthink.com/big-datas-impact-on-content-marketing/
    This article was really interesting to me as an international business major with a concentration in marketing. Content marketing is a huge topic recently because it has the potential to to boost brand image and get across important messages to users in a way that is either visually pleasing or has great content. Before reading this article, I was unaware that big data even played a role in content marketing, until I read about the potential it could bring to a company like boosting traffic, increasing visibility, establishing an industry voice,and promoting transparency for an organization’s. By collecting big data, a company is able to gear their content marketing directly towards the customers they want to retain, a great example of a company who already took a jump into big data and it’s possibilities for content marketing is Kickstarter. Kickstarted had posted a special report that included detailed statistics from data that they collected and it draws in their users because it’s a collection of data that they can’t get anywhere else.

  • http://newsroom.kpmg.com.au/?p=3053

    In this article titled “Star Wars: using data analytics, the force is revealed” author and KPMG’s Data & Analytics Leader, Anthony Coops, explains how three data engineers from KPMG were able to predict emotions of characters, future plots and common themes by analyzing data, aka the script. By partaking in language processing and text mining of unstructured data, the engineers were able to find the underlying associations, structures, patterns, and most importantly meaning within texts. The fascinating part, for a Finance student especially, is if unstructured data such as movie scripts can correctly predict future scenes within a movie, then what can business data predict for major corporations?

  • https://medium.com/steam-spy/understanding-your-game-through-data-8b09ca93ec11#.3x0laosbv
    To be honest, while this isn’t something while I’m technically in the major of, it’s an article about my main interests, which is video games. Steam Spy is an entire gaming website about collecting data on the Steam digital distribution platform, and this is their most recent article, which is about analyzing data itself. Some points that Steam Spy makes
    -You’re doing research and analytics to make informed decisions about your game.
    -Data doesn’t “tell” anything, nor it is “good” or “bad”. You’re the one interpreting it. (Very important)
    -A single day spent doing the research could save a month in development later.
    The rest of the article goes on to talk about demographic information and whatnot – what genre should you make your game, given what’s selling right now, how have other developers taken advantage of the current mood in life, and so on. It’s very interesting.

  • http://fivethirtyeight.com/features/sabermetrics-is-killing-bad-dugout-decisions/

    This article is very related to what I wrote about last week. In baseball there has been a lot of data used and embraced recently that has changed the game in many ways. This article highlights how the information taken from using data has reduced the amount of “old school” strategies that managers have used that have really been shown to be not worth it. Things like bunting (sacrificing your at bat to move a runner) and pitchouts (a pitcher throwing the ball out of the strike zone purposely to try give the catcher more of an advantage in throwing out a baserunner who might be stealing) happened way less often over the last 20 years or so, mostly because data has shown that while these strategies are affective when done right they are so often done wrong and in the end not worth doing for the most part.

  • http://www.onlinefinancedegree.org/top-resources/

    This article on the website gives great tools for finance majors allowing them to further research their field. Since I am planning on becoming a finance major I found this website very interesting and useful because it shows the top resources for finance majors. This article provides valuable links to sites such as “The Economist”, and “The Wall Street Journal”. After clicking on these links it brings you to articles published on these credible pages giving you vital resources and information about finance. How this website ranked the list of websites I do not know, but the website uses data in order to rank them in order of most valuable.

  • http://fivethirtyeight.com/features/the-panthers-first-half-blowouts-are-unprecedented/
    This article is really interesting me as a sports fan as well as because of the timing of the article, with the Super Bowl taking place in less than two weeks. This article analyzes the first quarter performances of 20 teams that have appeared or are set to appear in the Super Bowl, one of them being the Carolina Panthers. According to the data, the Carolina Panthers have the best starts in playoff history heading into the Super Bowl. Assuming that each team has a 50% chance to win before the game starts, the Panthers increase their chances of winning to 91% by the end of the first quarter, which is remarkable. The interesting piece to this article is that the top 6 teams according to chances of winning after the first quarter, excluding this year’s Panthers team, have all gone on to lose the Super Bowl. This data shows that even though a team has been starting their games in a dominant manner leading up to the Super Bowl, it is still possible for the other team to win against all odds.

  • http://www.entrepreneur.com/article/253837
    This article discusses the use of big data in franchises and how they would benefit if more franchisors paid attention to the data. This is interesting because a lot of business owners can be stuck in their ways and only use their own methods of data collection or even none at all to improve business. Domino’s is directly benefiting in many ways from using big data and you can see how they have been implementing these big data analysis to their stores. For example they removed “Pizza” from their name and now are just Domino’s, which makes sense now that they are serving more than just pizza.

  • http://www.forbes.com/sites/tykiisel/2013/03/20/you-are-judged-by-your-appearance/#3bb216d130f0
    This article looks at whether or not our appearance changes the way people think about you. Ultimately the article concludes that you are in fact judged based on looks, but I found it interesting how it looked at statistics such as, “tall people get paid more” and “Fat people get paid less”. I think it is necessary to know these things because often people believe that appearance doesn’t matter in the real world, when it actually does.

  • http://www.theguardian.com/business/2016/jan/25/mcdonalds-fourth-quarter-sales-all-day-breakfast
    This article is about how McDonald’s new addition of “all-day breakfast” has led to a significant boost in sales. As an all-day breakfast enthusiast and marketing major, this interested me because the fast food industry’s sales have been declining in recent years, and the concept “all-day breakfast” is seemingly reviving sales for McDonald’s.

  • http://tech.co/impact-big-data-social-media-marketing-strategies-2016-01
    This article discusses how using social media as a source of big data for company analyses is now a requisite for fully understanding consumers. According to the article, 90% of available data was collected in the past 2 years and 80% of that data has been extracted from unstructured sources like social media sites. I found this article interesting because I am currently a Senior Business Intelligence intern at a Marketing company and we are working on a social media related project. We are trying to find the best source of intel in order to understand our consumers interests and behaviors. Our initial thought was to extract as much social media data as possible, so this article simply solidified my belief that our current technique for data collection is a good start.

  • http://fivethirtyeight.com/features/were-there-6-percent-more-murders-last-year-or-16-percent/

    This article was interesting because it shows how data can be looked at differently. There were more murders last year than in 2014, but when you look at the data the increase ranges from 6 percent to 16 percent. Nationally the rate was up 6 percent, but in the most populated cities it was up 16 percent.

Leave a Reply

Your email address will not be published. Required fields are marked *