Section 004, Instructor: Larry Dignan

Weekly Question #8: Complete by April 9 class start

Leave your response as a comment on this post by the beginning of class on April 9, 2018. 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!

Here is the question:

Once again, find another online article dated within last two weeks from a credible source that has something to do with data and is interesting and relevant to you. Copy and paste the URL directly into your response followed by a few sentences that explain what is interesting about it.

27 Responses to Weekly Question #8: Complete by April 9 class start

  • https://www.forbes.com/sites/johnnosta/2018/04/03/data-and-its-real-demons/#21d5c7472985

    This article is interesting because it recognizes that often data can be misused for the wrong reasons. Then, it shows the good sides to data. The article argues that the most important use of data is medical data. It has the ability to save lives, and the way we utilize the information to better our medical world.

  • https://www.forbes.com/sites/celiashatzman/2018/03/09/popsugar-is-launching-the-makeup-line-of-millennials-dreams/
    This article is about how a media and technology company, PopSugar, used data to create its own line of beauty products. Makeup is a passion of mine, and I never think of it as something that has to do with data but more as an art form. It will be interesting to see if this brand is successful.

  • https://www.economist.com/news/britain/21739993-despite-its-flaws-new-obligation-could-spark-change-employment-practices-forcing

    I think this article is interesting because of the way the way the data is presented. The article goes on to describe the difference in gender pay gap in the U.K. and illustrates a chart showing woman’s median earnings as a percentage of men’s median earnings. It then states that the data is not adjusted for different employee roles. A data set describing differences in pay gap can’t be taken seriously if it includes secretaries with executives.

  • https://www.forbes.com/sites/julianmitchell/2018/04/05/this-data-driven-rental-platform-makes-finding-the-perfect-apartment-quick-and-easy/#2903e4683ddc
    This article is interesting because it changes the way an agent personalized your apartment search to a machine personalizing your search with much more in-depth explanation than your typical agent. This app also utilized agents to help renters but it speed through the process with the help of the app’s in-depth data.

  • https://www.economist.com/news/science-and-technology/21739644-securing-data-networks-new-ways-trade-data

    According to Cisco, an American technology group, the amount of of data that passes through the internet amounts to more than a zettabyte each month. Usually, data deals are at between the holder of the information and those who want the infomation. Companies like Fetch, IOTA, and Uber are creating new ways to trade data safely. This article I found talks more about it, because I use these new applications to get information about where I am headed.

  • https://insidebigdata.com/2018/04/05/artificial-intelligence-machine-learning-awaken/

    Hal Lonas, the Chief Technology Officer at Webroot, goes into detail about how artificial intelligence and machine learning are being applied in the world today and how it will affect the future of data and businesses. The most interesting thing I found in the article talked about how AI and ML are nowhere close to taking a vast majority of human jobs do to the machine’s lack of adaptability. It can use probability and statistics to suggest an outcome, but these suggestions don’t work well for individual tasks.

  • This article is interesting because it asks if it matters that the 76ers best players have no playoff experience. Everything about this revolves around data. Based on rankings, teams are given a percentage of making finals/ winning the title. In the NBA, it is very unheard of the same team winning the title. Personally, to answer the question the article asks, I do not think it matters if their best players have playoff experience because if they average a certain amount of points/rebounds/assists/ etc etc, then they will probably perform the same way in the playoffs. In fact, only 10 teams total, including the sixers, have made the playoffs when their top players have had no playoff experience.

  • http://www.thedrum.com/news/2018/04/06/ibm-puts-smart-work-new-brand-platform-and-tailors-moments-the-masters-with-watson

    This article detailed a new marketing campaign by IBM for their Watson supercomputer. IBM is using Watson to create custom highlight packages based off each fan’s individual preferences, like their favorite player or hole. As an advertising student I always think critically about ads I come across online or on TV. I think, why am I seeing this? Who is this ad targeting? What do they want me to believe about their brand? When my buddies and I were watching the Masters today I noticed they were hammering the Watson ads, showing one almost every single commercial break. I think they were trying to target an affluent, well connected audience segment who is interested in the Masters. I always do kind of question the efficiency of advertising a B2B product during a very expensive TV program. I usually assume these large companies just have a lot of money to throw around.

  • I found this article interesting because I did not know that the worst thing you can do with data is simply just throwing it out. I also learned that the problem with that is that not all of the data can be stored. Organizations well outside the Fortune 500 realm that used to be gigabyte scale data storage shops are now petabyte-scale storage shops, facing challenges they never expected. More and more businesses will need high performing systems that will store and protect large quantities of data over long periods of time.
    http://www.dataversity.net/future-data-storage/

  • The article talks about the data breach of the nation’s 2nd biggest airline carrier, Delta. There was a cyber attack on a vendor that runs a chat function on the carrier’s website. This happened to the Sears as well. Delta responded that it would cover any unauthorized transactions resulting from the breach. It is highly possible that many incidents like this will happen often in the cyber era.

    source:
    https://www.wsj.com/articles/delta-says-hack-on-vendor-exposed-customer-credit-card-data-1522965773

  • https://www.cbssports.com/mlb/news/as-a-baseball-fan-gabe-kaplers-approach-presents-a-real-problem-to-me-and-heres-why/
    I am not a huge Philadelphia sports fan, but recent events regarding the Phillies have certainly caught my attention. Gabe Kapler, who I must admit, I was a huge fan of (considering he was an extremely successful Director of Player Development within the Dodgers organization, which is my favorite team), and I was rather optimistic of a marriage between Kapler and the Philadelphia organization. In the wake of his brain-gaffe in the opening series, I am much less optimistic. The article outlines Kapler’s analytical approach & style of management.

  • https://www.databreachtoday.com/200000-cisco-network-switches-reportedly-hacked-a-10788

    This article has to do with the recent hacking of Cisco. On Friday, over 200,000 of Cisco’s networks switches were hacked into worldwide. The result of this was an effect on large internet service providers and data centers. This article sparked some interest to me after recently studying the quantified self movement. After hearing of so many recent hackers online targeting personal information, it makes me more and more conscious about what I will share online in the future.

  • https://fivethirtyeight.com/features/a-fast-fastball-isnt-enough-anymore/

    This article looked at the evolution of hitting in major league baseball, and how hitters have become more adept at hitting fastballs clocked at over 95 mph. The article looks at data that looks at the annual amount of pitches thrown clocked at 95 mph and above since 2009, and the league-wide OPS (on-base percentage plus slugging percentage) in total and against pitches clocked at those speeds. It identifies a growing trend where players have grown more accustomed to facing higher velocity and adjusted to this trend. I found it interesting that OPS against pitches clocked at 95 mph+ grew .036 points since 2015 to .734 in 2017, and continues to grow. It also highlighted some notable transactions that took place this offseason that accounted for this growing trend and hitters ability to catch up with rising pitch velocity.

  • http://flowingdata.com/2018/04/09/datasets-for-teaching-data-science/
    I found this article interesting. Its a collection of data sets for teaching data science. I think I liked this article because I feel a connection since I am taking a data science course. The collector of the data for these data sets is Rafael Irizarry and he says, “my experience has been that finding examples that are both realistic, interesting, and appropriate for beginners is not easy.” Irizarry makes data science accessible to everyone by finding examples of data sets that accommodate mass consumption.

  • https://fivethirtyeight.com/features/just-how-much-does-tiger-affect-tv-ratings-for-the-masters/

    This article is interesting because at one point in time Tiger Woods was the greatest golfer in the world, due to injuries and other factors this was the first Masters he participated in since 2015. Every Masters Tiger has won has been the highest viewed final round by the Nielson rating scale. This is interesting because if
    Tiger made it to the last round (he did not) it would of also most likely been highly viewed. In summation, views can be skewed by one individual golfer attendance in the final round of the Masters.

  • This article talks about why so many data analytics projects fail. With many companies looking at the wrong data and not focusing on the main data. The articles also talks briefly on some of the reasons why data analytics fail such as Input, output, and analysis. This interesting to me because it relates to most of the material we covered in the semester. http://www.dataversity.net/many-data-analytics-projects-fail-save/

  • https://www.theguardian.com/lifeandstyle/datablog/2017/dec/24/most-pirated-christmas-movies-data-sketch

    I loved the topic of the article. It provided data on the most pirated Christmas movies. The copyright protection company did a research, in only a 4 day period (December 14-18), they searched 33 movies that are believed to be Christmas Classics and found out that “Home Alone” was the most pirated movie ever.
    I also found the visualization very cute – it was a bar chart executed in the shape/color of the Christmas tree.

  • https://insidebigdata.com/2018/04/07/data-analytics-contribute-business-growth/
    This article talks about how data analytics affect business growth. This article was interesting to me because it showed how analyzing data can improve the growth of a business. It first started off talking about having a plan on how the business will be able to grow and what opportunities will arise. Next, it talked about marketing and customer reach which is very important to grow a business. Data analytics can give a company certain numbers based off of their customers to improve their advertising and improve the business overall.

  • https://www.baseball-reference.com/teams/NYY/new-york-yankees-salaries-and-contracts.shtml

    This data shows the salaries and contracts of the New York Yankees. I am a big Yankees fan. This year, we are ranked #7 in highest salaries in the MLB and that is the lowest we have been in a while. Usually, we are #1. This means that we are not spending as much money on players especially since we are a younger team than we used to be.

  • https://blog.timescale.com/why-sql-beating-nosql-what-this-means-for-future-of-data-time-series-database-348b777b847a
    This article describes why SQL is re surging as a popular database choice. Relational database use had been decreasing since the advent of NoSQL databases(that use JSON format to store data), which offer a more convenient way to store unstructured data. It describes how new database management systems like ProsgreSQL played significant role in the comeback, by offering new features like JSON datatype for use by developers. SQL has advantages through the powerful query language and it’s ease to store, process, analyze and visualize data, along with it’s use by the business community.

  • http://www.dataversity.net/data-quality-data-governance-resurgence-interest-future-maturity/
    This article talks about the quality and governance of data. It goes in depth about ways we can improve the quality of our data and how it can possibly be detrimental to companies. It also supports the fact that in the past 20 years the consumption of data has increased exponentially due to the improvement of technology as well as data analytics tools that help us gather data and transform it to information we can use to improve.

  • https://www.infoworld.com/article/3267505/database/real-time-data-pipelines-pairing-message-queues-and-databases.html

    I find this article interesting because it stresses the importance of communication in data science. It speaks to the necessity of clear, set metadata. Without proper communication, data and databases are just meaningless (and expensive) numbers. The article also presents many new messaging queues and data pipelines that are becoming more and more relevant in today’s data collection.

  • https://fivethirtyeight.com/features/the-trouble-with-leaving-facebook-is-that-we-like-facebook/
    This article by FiveThirtyEight takes a look at the Facebook data scandal, and how people feel about their personal information. A survey collected that 91% of adults thought that consumers had lost control on how companies collect information. It would later show that information such as social security numbers and health care are data that people are most sensitive of getting taken. Amidst everything going on with Facebook, this article is interesting in looking at how users see the scandal despite staying on Facebook due to the Privacy Paradox.

  • https://www.cnbc.com/2018/04/09/googles-youtube-illegally-collects-childrens-data-privacy-groups-claim.html

    This article is interesting due to the escalating concern of social media data and what it is being used for. Youtube’s integrity is now being questioned because of its use of children’s data for profitability. It is concerning because Youtube has some barriers of age restriction; however, many children can go to the site and watch videos. It is concerning because children do not know what power of data collection can do, and parents do not know how the data is being used for their children.

  • http://www.sciencemag.org/news/2018/04/could-artificial-intelligence-get-depressed-and-have-hallucinations
    This article talks about that with more development, could artificial intelligence experience depression or hallucinations as humans do. It talks about how AI can release a similar chemical in themselves such as serotonin is released in a human being causing depression or hallucinations. I think this article is interesting because of how they are trying to make AI more into human beings.

  • This article is about the push to increase data literacy among diplomats and federal employees working for the State Department, Health and Human Services, and Department of Commerce. As the author explains, this push has risen from the demands of a more data-driven world in which numbers hold more value than words alone; diplomats have the ability to substantiate their claims, extend their influence, and justify their proposals when they are data literate which furthers their agendas. They learn these skills in newfound workshops, seminars, and courses.

    https://www.fedscoop.com/state-department-foreign-service-data-literacy-training/

  • https://iq.intel.com/crazy-for-march-madness-data/
    This article talks about all the different data that goes into March Madness. I found this very interesting because I am a huge basketball fan and I fill out a bracket every year and know every year there is basically no chance it will be perfect. It is something that has never been done and more than likely will never be done. Some of the big upsets ruined thousands of brackets alone which cost people a lot of money. I think it is very interesting to see how many different possibilities there are and people choosing them and no one will ever get a perfect.

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Office Hours
Larry Dignan lawrence.dignan@temple.edu Alter Hall 232 267.614.6467 Class time: 5:30-8pm, Mondays Office hours: Monday hour before class, half hour after class or by appointment.