Lawrence Dignan

  • Some quick instructions:

    You must complete the quiz by the start of class on February 13, 2017.
    When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to […]

  • NYC Cab Viz

    Telling story with Data

    Cool infographics Chapter 1 and Chapter 6

     

  • Here is the exercise.

    Before you start, save this Tableau file and the studentloans2013 Excel workbook to your computer. Remember, to save the file right-click on the link and choose “Save As…” (don’ […]

  • Here’s a good read on Pew on AI and bias. It’s going to be an ongoing topic in your careers well beyond this class.

  • Here is the exercise.

    And here is the spreadsheet you’ll need to complete the exercise [In-Class Exercise 4.2 – FoodAtlas.xlsx].

    Make sure you right-click on the Excel file link and select “Sa […]

  • Some quick instructions:

    You must complete the quiz by the start of class on February 13, 2017.  The quiz is based on the readings for the whole week.

    When you click on the link, you may […]

  • Session 4.1:

    Chapter 2: Good Graphics? Handbook of Data Visualization (Unwin—-pages 57-77)

    Session 4.2:

    Stephen Few on Data Visualization: 8 Core Principles (Hoven)
    Watch out, Terrorists: Big […]

  • Leave your response as a comment on this post by the beginning of class on February 16, 2017. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your o […]

    • Although the hospitality and gaming industry may not be the most affected industry by data, the field uses a lot of data to keep customers satisfied and make money. Data is constantly being processed in real time from the floors of the casino into the databases, allowing the casino to individualize their offers to each customer. An example of this is server-based slot machines, which can alter the game based on the player and the amount of money put into play. It is like the Netflix example shared in class, where the game is matched to the individual to create an individualized experience. Although I am not in the hospitality and gaming industry, my field of music therapy relates to the entertainment aspect as well as the individualized treatment of each client. I will use the cues given to me (verbally and non-verbally) as my data to change the way the session is going.

    • Data science has revolutionized the online retail shopping industry. Data science has allowed company’s to customize the online shopping experience through predictive analytics. Online retail sites have the predictive power to make product suggestions based on previous purchases and browsing history. Companies also use data science to communicate via emails that are targeted directly to what you were browsing for or about abandoning your shopping cart. Online retail also customizes the marketing experience by filtering banner ads by browsing history on social media and search engines. Since all marketing is done online or through emails, companies can use data to track conversions to see if marketing campaigns were successful at making a sale.

    • I see the healthcare industry being entirely disrupted by data science in regards to cyber-security, patient data to determine the effectiveness of medicines, and rating systems for specific surgeons and practices. Personally, I see data science playing a big part in my career because I plan to go into data analysis, where I will be aiding corporations regarding future decisions by creating clairvoyance through data. The downside is that the data I use for future endeavors may be biased depending on how it was recorded and the motive of the creator, unless the data is vetted properly prior to usage.

    • As an Accounting Major, I can see big data influencing Auditing the most. The ability to hide bad data could be affected by the right auditor who has an emphasis on data analysis. This may make it more difficult for companies to be unethical. Tax accounting may not be as affected, although it would be helpful to see who is lying in their tax filing by comparing old data to new. These two areas seem to be the most affected by data science.
      In my previous life at Whole Foods, data science was becoming a part of our ordering and shopping process. The company had just begun a card system similar to the ones offered at conventional stores, but it collected data from people’s receipts and sent it to the buyer to give better information about sales and what needed to be purchased that week. In addition, it created coupons for each indidvidual customer based on their previous purchases. It also gave points for purchases similar to Starbucks, but instead of getting a general free item, they received periodic coupons for free items that they purchased often. This personalized shopping experience really seemed to appeal to customers.

    • As an advertising student, I’ve gradually learned more about how this industry works. The advertising business is continually using data to analyze its consumers and keep track of their spending. There are numerous reasons for the advertising industry to keep track of data which includes: tracking the companies success and growth or decline, tracking product sales and seeing which product are doing well or need to be improved, and most importantly finding out what consumers are interested in purchasing. As discussed in class, the “filter bubble” and web personalization is what allows these large corporations to keep tabs on their customers and take advantage of their data to manipulate these consumers to keep coming back. I see data science playing a role in my career because all large corporations are using this strategy today and it seems in order to be a successful company, data must be kept track of to understand how to sell more products.

    • Personally I’ve seen data analytics affect the professional sports industry the most, with a particular emphasis on professional baseball. The “analytics age” has seen professional teams rely on data more and more than traditional human scouting. Whether or not this is a good thing is purely an opinion, but with books/movies like 2011’s “Moneyball” you can begin to see how trends in data are being used to predict which players will be more essential to a team’s success. I most likely won’t end up in the professional sports industry, but as an MIS major I know data science and data analytics will be influential throughout my career.

    • Like some of my classmates, I see the sports industry being the most affected by big data, but more along the lines of sports gambling. I personally do not gamble or bet on sports, but I know a lot of individuals who do. Though there may be some casual fantasy gamblers who aren’t necessarily strategic their methods, I believe that the use of big data will help to drive the demand for gambling, especially since the market seems to be increasing its popularity over the years. I plan on working in the insurance industry when I graduate, and big data and data analytics will greatly assist in the efficiency in which insurance companies operate. For instance, if an underwriter has more information on the business or client that he or she is underwriting, then they are able to generate a more adequate premium price for the insured. Hypothetically speaking, more adequate premiums will mean that the insurer will generate more profits because portions of the premium are increased due to the expected risk that the insured will bring to the company.

    • I believe the sports industry is rather heavily affected by data, but the healthcare industry would more than likely be the most disrupted by data. The healthcare industry relies heavily on data to analyze and properly care for patients. Sports analysts rely on data to accurately report statistics about teams, players, and coaches. Data science will affect my career because I will be working in the sports industry. If I am a cap analyst for a professional team or work in the player personnel department I will need to know the statistics about different players. Teams rely heavily on analytics when drafting players or discussing contracts during free agency.

    • Two industries come to mind when talking about big data defining the future. Those two industries are education and the healthcare. In terms of education, I think that predictive analytics could be leveraged in many incredible ways to foster better learning and life outcomes for children. IBM already has a platform that develops pre-tests for students based off of teacher’s inputted lesson plans. Then, when a teacher plugs in each student’s grade on the pre-test, the platform is able to identify which specific learning activities each student needs to master in order to score “highly satisfactory” on the post-test. It’s very powerful. However, one issue with this is ensuring costs stay low enough and that the technology is affordable enough that not only the wealthier school districts have access to this intelligence. Technology in education must always be equally distributed. In terms of healthcare, there is a really good book called “The Patient Will See You Now”. It’s pretty cool because it talks about how we are entering a world where so much of our health data is becoming accessible to us, as the patients, that this data is really changing the anatomy of the doctor’s appointment. It will be very interesting to see how doctors’ roles change as patients become more informed about their health without needing to visit an office.

    • Data Science has been changing many components in our lives. Automating business processes is viewed as gaining a competitive advantage over industry rivals by freeing up resources but later implementing a headcount reduction. Loans are authorized or denied within seconds, shipping orders are completed effortlessly and corporations are able to complete large transaction via an ACH. Watson is moving into a space that offers medical advice. It seems that Data Science has offered the ability to automate our entire lives. With advancing technology in A.I and machine learning, most industries are being threatened. There isn’t a specific industry that is disrupted but an entire cultural shift. For now people with technical skills and the ability to solve complex problems are on the right side of the digital divide. To pick an industry for dramatic change: Healthcare/Medical industry.

    • The most important takeaway I learned is that data is important in any business. I understand that data will play a very important role in the future because how data has revolutionized businesses today. Like for instance, Macy’s announced closing hundreds of store, if it wasn’t for the evolution of data, those stores wouldn’t have been close. The use of data is crucial for up and coming companies to survive. It was very interesting to learn about all the different ways that QVC uses data to enhance their customer experience and boost sales. I liked learning about how to use data to figure out why a product was not selling well.

    • I think the healthcare industry is affected greatly by data science. Through different tests and studies, they are able to get a lot of data that can help with many patients find the right treatments in the future. Data can also distinguish which hospitals are better for certain reasons. On the other hand, there are also ways that it can disrupt the healthcare industry. Too much data might make it difficult to find a cure for certain diseases and also everyones body might react differently to treatments. As a finance major, I know I will be using data science and it will impact me greatly. It is important for all businesses if they want to succeed.

    • I think data science can affect food industry, and data can either make it better or make it worse. For the good side, because there are data websites in which customers can rate, restaustants will make more efforts to preserve their business images and improve their foods and services. For the bad side, because of the easy access to these websites, anyone can rate a restaurant for any reasons. Bad comments would convey a bad image of the restaurants to the public, no matter whether the comments were true or not.

    • I think that data science has greatly affected the advertisement industry. The insight that big data has given to corporations and other businesses about their customers has allowed them to change the way that they create advertisements and who they show their advertisements. I dont see myself having a career in a field like advertising however I will definitely feel the effects of the changes that data science has made to the industry. Data science will cause me to see many more advertisements that are tailor made to make me want to buy a product.

    • In my opinion, the industry that is affected and disrupted the most by big data, data science, and analytics is the advertising industry. As an advertising major on the account management and media planning track, I realize that data and analytics possesses a large role when it comes to advertising and marketing. As digital advertising continues to grow and expand, the importance of data begins to increase. With traditional media, advertisers were able to give you an estimate reach, but with digital advertising, you can find out who clicked on your ad, where they were when they clicked on it, and you can even track that person so they can be later retargeted. There is one major issue when it comes to digital advertising: click fraud. Click fraud is defined as “the practice of repeatedly clicking on an advertisement hosted on a website with the intention of generating revenue for the host site or draining revenue from the advertiser.” Essentially, when advertisers pay per click, companies are handing over money for falsified clicks causing advertisers to believe they are driving more traffic than they actually are. Going into a career as either a media planner or account manager, data will have a large impact on my future endeavors. Whether it is researching consumer statistics to devise a strategic media plan or discussing key performance indicators with a client, I will be faced with data on a daily bases.

    • Data Science has had a large impact on Social Media platforms, which have been able to aggregate and analyze user data to gain insight into knowledge about individual users, their preferences and who they are. This has many effects, including the perpetuation of the filter bubble (i.e. Facebook which caters your newsfeed to your preferences and shows you ads based on that). Something I find interesting is that Facebook’s Data Analytics Team has partnered with the social sciences department in many universities to help answer questions about human relations and society; perhaps this is a field of study that will be greatly disrupted as a result of data analytics.

    • I think the industry that is most effected by bug data is financial industry such as Banks and Securities. With analyzing big data, early warnings can be sent out for securities fraud and trade visibility whenever there is a suspicious activity. Banks can use big data to track their customers and detect possible card fraud and audit trials. With all types of data and analytics, it also can monitor and catch illegal trading activities in the financial markets.

    • As many others have stated, the sporting industry will be affected by data science. The existence of big data can help sport teams notice trends that can help the team. Teams can use big data to help with the process of recruiting players and scouting them. Relating to the sporting industry, fantasy football or betting on specific sports team will be affected as well, because people who bet can use big data to help increase their percentage of winning by noticing trends or patterns. Data science will affect my career because analyzing and being able to display the information in a simple manner will be a crucial skill. As big data gets bigger and bigger, the skill of analyzing big data will be important.

    • The industry that has most been affected (either positively or negatively) by big data is the sporting industry. Not only has the data enabled teams to more accurately evaluate their own players and opponents, but has also allowed the networks who put the games on television the viewing data to maximize their profits with advertisements. In addition, teams are able to use big data to utilize price discrimination (selling similar tickets for higher prices to those willing to pay more) which is either a positive or a negative depending on whether you are the one making the profit or paying extra. Big data will be vital in my career in order to model the most utility maximizing decisions that I have to make in my work as well as personal life.

    • The insurance industry is most affected by data science in my opinion, because it changes the ways that how the insurance company prices their policy. Insurance industry heavily depends on data collection to calculate the pricing of the policy, in today’s insurers have an enormous advantage through a judicious analysis of big data. Insurance companies have been empowered to improve their pricing accuracy, create customized products and services.

    • I can see the pharmaceutical industry being largely affected by data science. With a lot of research in this industry, there is a lot of data to keep up with. In the future, I plan on going into data analysis so data science is going to play a huge role in my career. Earlier in class we learned a lot about how data analysis can be biased. This can affect the company I will work for because the biased data will affect future decisions.

  • Here is the exercise

    Here are the links in case you cannot click from the document.

    History, Economics and Social Issues

    Science and Health

    English, Fine Arts and Entertainment

    Remember to […]

  • Here is the assignment.

    Here is the worksheet as a Word document to make it easy to fill in and submit (along with your Tableau file).

    And here is the data file you will need to complete the assignment […]

  • There are recordings of what we went over in class so bookmark this link. The recording is on autopilot, but gives you a gist of what transpired.

  • Some quick instructions:

    You must complete the quiz by the start of class on February 6, 2017.  The quiz is based on the readings for the whole week.

    When you click on the link, you may see […]

  • In class we talked about a few examples of open data. Here are some others:

    Business: data.gov’s “Impact” section
    Science: The Genomes Unzipped project
    Government: New York City parking viola […]

  • Leave your response as a comment on this post by the beginning of class on February 6, 2017. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your o […]

    • From an MIS perspective, I found an article that talks about how to truly delete data in today’s technological age. All data is stored on a physical device so you can erase data that you have control over. This fact-checking story by the Washington Post regarding President Donald Trump’s immigration ban on seven countries is very interesting. The story uses the data provided by the President and believes it “old,” adding new and more exact figures of how many people — upwards of over 90,000 people — that have been affected by the ban. The data surrounding these people is filtered from several different places, like government agencies such as the Department of Homeland Security or even an open-data Google spreadsheet keeping track of over 300 Iranians’ journey to the U.S In addition, data sanitization is also an option to wipe drives through overwriting them enough times. But the major point that I learned is that data is always easier to make than it is to delete.

      https://fivethirtyeight.com/features/what-it-takes-to-truly-delete-data/

    • http://www.forbes.com/sites/danielnewman/2017/01/31/realizing-the-potential-of-big-data-and-analytics/#50b01f951c66

      The article above explains the potential of data analysis, and “potential” is used because it is heavily underutilized in today’s business process, according to a Harvard Business Review. Another great point surfaced in the article is that data analysis involves every member of the organization, up to and including the C-Suite; a great way to get noticed. In order for change to be successfully embraced, you MUST support it with data. No more using intuition in big business decisions.

    • http://rdcu.be/oXBE
      The study above explains how the effects of music therapy can aid symptom management and quality of life for both hospice patients and family members. Most other studies of this sort only focus on how the music can help the patient, but do not focus on the family members. To complete the study, therapists had the patient and the family members rate their symptoms of pain, anxiety, depression, shortness of breath, and mood, before and after the therapy sessions. The results showed that, of the 50 pairs of participants, 82% showed improvement of quality of life, 80% rated the session as helpful, and 100% recommended further music therapy sessions. As a music therapy student, it is uplifting to see these positive results, and it shows me that there is data to back up my field of study. Additionally, this article was interesting to me because the study was done at the Cleveland Music Settlement, in which I intern during the summers.

    • http://tucson.com/news/data/bing-predicts-super-bowl-li/article_7fe8e4b6-4113-5d84-86a3-b7b1def74667.html

      I think this article is very interesting because it is data in sports. Sports are the perfect example of why we analyze data. This article breaks down the super bowl odds of the Falcons and the Patriots. What is unique is how they use advanced stats and analytics to break down their predictions for what is going to happen. My personal hobby is being a sports analysis. I love to break down data and talk about football and basketball and how data affects the game.

    • This particular article focuses on injuries in sports, specifically the NFL. In a recent press conference, the NFL prided itself that the amount of concussions reported this season were less than last season. While this piece of data may seem positive at first, it is only because the amount of reported concussions was an all time league high. The article also discussed that the amount of ACL injuries were minimized, but the amount of MCL injuries increased this season. I find this particularly interesting because the NFL decided that the evaluation of Miami Dolphins’ quarterback, Matt Moore, was not properly evaluated for a concussion in the playoff game against the Steelers. I’m curious to see if the league will look into any other incorrectly evaluated concussions. Data such as this has been influential in the NFL admitting that concussion are a large problem and need to be taken very seriously in the sport.

    • I read an article entitled “The Changing Nature of Accounting” by Mike Galarza.The article addresses the impact that Big Data is having on the Accounting field. The author explains how Accountants once needed to be experts at all aspects of the field; however, Big Data, the internet, and the increasingly complicated tax code is changing the way Accountants work. The author suggests that the future of the field is similar to that of Lawyers: find a niche market and serve that market well. Big Data is both a hindrance and a saving grace to the Accounting field. On one hand, sifting through all of that information can be a real challenge. On the other hand, it is almost impossible to automate data analysis, because it requires thought processes that a computer simply doesn’t have. This may end up being the thing that saves Accounting from a future of total automation.

      The Changing Nature of Accounting

    • How You Can Protect Customer Data and Keep Customers Safe

      This is an interesting article because it discusses the moral obligation of businesses to protect customer data. Data protection is a hot topic nowadays because of the increasing risk of a customer’s personal information being stolen by hackers. The article discusses though that not only are companies responsible for abiding by regulatory procedures to protect data, but that the companies also have a moral responsibility to want to protect their customer data to the best of their abilities, giving an example of how a financial planning company has taken steps to acknowledge that when clients choose to do business with them it is the firms responsibility to protect the customers financial data. The article then goes on to list measures a company can take to better protect its customer’s data.

    • https://www.forbes.com/sites/robsalkowitz/2017/02/03/super-bowl-ad-showdown-in-the-new-age-of-media-metrics-tv-watches-you/#2db4e8ec486c

      I found this article interesting, because it shows how the evolution of data is enhancing our ability to track how successful advertisements are. Advertisers spend billions on Superbowl ads, but until now could not determine the real reach of the ads. Current media metric platforms will now allow for a clearer audience picture by collecting data directly from the viewing devices themselves and analyzing it using machine learning. Once trends or patterns are recognized, they will be visualized on a web based dashboard. This could be a start for marketing departments being able to justify the cost of expensive advertisements with statistics.


    • The article above writes about an application of big data to college-level education, which should be relatable to not just me or anyone in our class, but every college student. I found this article interesting because it demonstrates the use of data analysis to evaluate college students’ performance, predict their ability to graduate in time and alert educators and students alike to take actions if needed. Big data reveals that a good standing in foundation courses often indicates a higher chance of graduation, which is actually a very interesting point to me. This is a clear example of how data has permeated the very most important aspects of our lives, and how we can utilize it for betterment of performance.

    • https://www.datanami.com/this-just-in/attunity-signs-agreement-global-insurance-company-enable-new-data-lake-initiative/
      This article describes how a global insurance company is now employing a “leading provider of data integration and Big Data management software solutions” called Attunity Ltd. Attunity will give real-time data to the insurance company and provide support for quick data integration for acquisitions that will be useful for the insurance company’s a strategic advantage in the business. Though the insurance company is not named, and referred to as simply, “the Customer,” they are a company who mainly acquires other insurance companies, so Attunity’s services will be well utilized.

    • With the increase in credit card fraud, banks and other financial institutions are trying to protect their consumers. To protect the consumer, card companies started to use a chip that encrypts information to help increase data security when a transaction takes place. The problem that has occurred is consumers shopping behavior has change, as more people are shopping online and not using retail stores as frequently. Since October 1, 2015, when implemented, e-commerce fraud in the U.S. has jumped 42% in the fourth quarter of 2016.
      In the U.S. there were 15.4 million victims in 2016 and losses from fraud have hit $16 billion. Hackers are using using Botnets, and they have techniques to intercept codes by email or even a text. Is there too much data “Out There” ? Are you safe?
      CIO Matt hamblen. Feb.3, 2017;
      http://www.cio.com/article/3165417/security/online-card-fraud-up-as-thieves-avoid-more-secure-chip-cards-for-in-store-payments.html

    • https://fivethirtyeight.com/features/trump-could-really-mess-up-mexicos-economy/
      This article talks about how Trump would affect Mexicos’ economy. A series of anti-Mexico policies that Trump has made would cause a great loss to Mexico’s GDP. The policies include limiting the flow of remittances to Mexico, increasing tariffs, stopping free trade agreement. However, in this article, the author points out that these policies would not only affect Mexicos’ economy, but also make America loses a large number of skilled but cheap labor.

    • https://fivethirtyeight.com/features/strong-hiring-greets-the-trump-era/
      This article discusses the increase in hiring and the unemployment rate since the beginning of January. Almost a quarter of a million jobs were created by US employers in January. This is the highest job creation rate since September. This is a sign of confidence in the economy considering Donald Trump was not in office for most of the month. The article also mentioned the effect unemployment rate has on the economy and they explain why Trump may be misinterpreting the impact of unemployment within the US. I think it is interesting how economists can draw different conclusions from the same data depending on how they think the economy works.

    • http://www.economist.com/blogs/graphicdetail/2017/02/daily-chart-0

      This article, “What defines a nation’s identity,” used survey data from Pew Research Center to try to define what it means to have a national identity. The survey asked respondents from 15 countries a variety of categories about the makeup of a national identity, such as “being able to speak the national language” and “sharing national customs and traditions.” It then used a chart to highlight what percent of each country found these categories very important in determining a national identity. I thought this article was interesting because populism and nationalism is on the rise around the world, and it was neat to compare how different countries view what it means to have a national identity. You can see some countries (Hungary) demand cultural homogeneity more than others (Canada).

    • https://projects.fivethirtyeight.com/complete-history-of-the-nba/#sixers

      This article demonstrates a method called “Elo” that can help rate an NBA team across the decades. The most interesting part of the “Elo” method is that you can pick a specific team from any era and it can calculate their ratings.The main components of the ratings are gathered from the final score of the game, when and where the game is played, winning or losing, and if the game is an upset or won by a huge margin. It is interesting how the “Elo” method is able to figure out a rating system that can accurately portray how good/bad the NBA teams are across the decades.

    • https://www.forbes.com/sites/bernardmarr/2017/02/01/what-really-happens-to-your-big-data-after-you-die/2/#4ca86cd199c1
      I found this article is interesting is because now we all think how the big data can benefit us. And all kinds of issues with privacy, rights, etc. This article talks about what happens with our data after we die from different fields. He makes a good point is that regulatory is not keeping up the pace with technology, there is no clear rules about how the data can be used after people die.

    • http://www.forbes.com/sites/danielnewman/2017/01/31/realizing-the-potential-of-big-data-and-analytics/#1c151c31c66c
      I found this article interesting because it looks into how big data can, and will, be used by companies in a variety of ways. The companies will use big data to “adopt and adapt” new services and products that big data shows to be on an upward trend. The article also makes a point showing that if the data is either not used correctly or is not properly collected than it may mislead companies.

    • https://webapps.philasd.org/news/display/articles/2364

      This article is a press release from the School District of Philadelphia’s Communications Office. The release discusses the recently announced School Progress Report, which is an annual report card published for each school in the school district. I find this release interesting because of the calculation methods behind the metrics that comprise the School Progress Report. For each school, a number of different metrics are measured including, but not limited to: school safety measures, attendance, and test scores. In order to receive any “points” on a metric, each school must earn at least the floor score for that metric to get points. So, for example, let’s say the floor score for attendance is 60%. In order to get any points at all, a school must have attendance of at least 60%. If they get below that, they get no points. If they get above that, they get a portion of the points. I say all this because what I find interesting is that the school district does not make the rationale for each chosen floor or target score public. I am not implying they are hiding anything or have anything to hide. However, in order to get a true and transparent insight on school progress, it would really be helpful for the public to know why District leadership is making decisions the way they are in regards to this very important annual report.

    • http://www.forbes.com/sites/bernardmarr/2015/09/08/4-ways-big-data-will-change-every-business/#7c4cf17a7900
      As a business major, I found this article about Big Data very interesting. It shows how important big data is to companies and how it helps them each improve from it. Data will help companies improve different aspects in a positive way. If something doesn’t seem to be going right, they could collect data to see if there is something that they could change. No matter what company I decide to work for in the future, I believe that big data will definitely be useful for it to succeed and result in excellent customer experiences.

    • https://fivethirtyeight.com/features/trump-could-really-mess-up-mexicos-economy/

      This article is very interesting to me because it breaks down the economic impact that the Trump presidency could have on the Mexican economy due to his proposed trade restrictions. As economists have known for hundreds of years, trade between countries helps both countries involved due to comparative advantages. While President Trump believes that he will be helping create more jobs in the US by restricting trade with Mexico, the overall economy will be hurt in both countries because goods will now be more expensive in the US which will have a greater magnitude effect on both the US and Mexican economies than the job increases in the US.

    • https://www.wsj.com/articles/facebook-and-google-step-up-efforts-to-combat-fake-news-1486396476?mod=e2fb

      Google and Facebook are working to take down fake new on the internet. With European countries heading into pivotal election campaigns in coming months, Facebook and Google are rolling out initiatives and tools aimed at slowing the spread of online misinformation. They also changed their policies to block many publishers of fake news as well as tech firms added new tool to filter out false content.

    • http://www.itproportal.com/news/data-analysis-most-sought-after-skill/

      In a new report, marketers found that data analysis is the most important skill a person can learn within the next few years. With social media, web development, and graphic design behind it data analysis is the most sought after skill these days. With the emergence of big data, marketers can truly understand what their consumers want. However, most marketers do not have to time or skills required for data analysis so they hand over the work to the IT department.

  • Some of you noted you have a focus communication, PR, advertising and marketing. Here’s an IAB report/outlook on emerging data trends in advertising (as it applies to digital media).

     

     

  • Bias in big data
    In data we trust
    Filter bubble

  • And you’ve just won the most interesting and possible fun experiment award.

  • Very interesting. I don’t think it’s lazy as much as knowing what to delegate and building a team that you can hand off to. Delegation is an important skill. I think the conventional wisdom comes from a few dolts that delegate everything and do little. Given we’re all bound by KPIs and data I’m not sure how long a lazy leader can hide.

  • Generally speaking I think it’s more true than not. The bigger question is what dues are paid, how fast and what projects you ran to get you someplace. You make your own luck in many cases and a contact only gets you so far. Most of the time you have to deliver the goods once the who you know plays out.

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