Instructor: David Schuff, Section 001

Weekly Question #4: Complete by February 11, 2016

Leave your response as a comment on this post by the beginning of class on February 11, 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!

Here is the question:

Take a look at the Hoven article from this week (“Stephen Few on Data Visualization: 8 Core Principles”). Which one of the eight principles do you think is most important? Why?

55 Responses to Weekly Question #4: Complete by February 11, 2016

  • I think that the Attend Principle is the most important since Data Visualization is all about taking the effort off of the brain an putting it on your eyes. The visualizer needs to be able to pay attention to the important data and relevant details because it is pointless to look at something that you aren’t even focused on. To compare, explore, view diversity, and ask why, one must first be attentive to the data.

  • From the article, I think the “Explore” principle is the most important. With some basic knowledge and training, almost anyone can make a data visualization that is attractive to look at. Possibly even some other principles may be present, such as simplicity; however, it takes a lot of thought to make a graphic that is simply visually appealing and is able to be comprehended solely by the data it presents. The data visualization should also inform viewers of its purpose while encouraging the search for other questions through the data. Making a graphic that can be explored is critical.

  • I think the “explore”principle is most important because it suggests that we should questions the data before we accept it as valid and this can lead to a revelation within the data that we did not see before. It also suggests that before we publish at a we should make sure it makes sense and can be interpreted by the majority of people.

  • I believe the simplify principle is the most important. I think it is the most important because when making a data visualization you want it to be simple and easy to read. If it is too complex people will skip right over it because it will be hard to understand.

  • Out of all the principles, I give my approval to “Simplify”. Simplicity has always been generally favorable. Pure purpose of millions of API created was to simplify the massive & complicated data down to something that everyone should be able to use and understand. Same thing with data, when the creator decided to make a data visualization, doesn’t he/she want to simplify the data into something understandable to the audience? Something that tell one story, right to the point, with minimized text and maximized visual comprehension. If one finds himself/herself incompetent of doing such a thing with the data, it’s better of just to put the table of data out there instead.

  • I would say that being skeptical is the most important principle. Data is easy to misrepresent and misconstrue if presented or analyzed with an anchoring bias. In other words, it is easy to be comfortable with accepting the data that is presented first without question. Being skeptical and constantly wondering if the data is accurate will force us to dig deeper into the sources of the data to search for accuracy in the data and in the representation.

  • I think Simplicity is the most important principle because you can spend a bunch of time and resources on making your data over complicating which will be a waste of time and money if the audience doesn’t understand the focus of the data. I feel like this is the most overlooked concept in data because people are too wrapped up in using technical words to make their research sound legit when really they just have to get their point across as quickly and clearly as possible. Simplicity isn’t always simple.

  • I think simple to understand is the most important factor. Data visualization is not only designed for experts but for all the people who want to understand something, the visualization should be clear and simple to read and understand what it is talking about.
    Also it is the visualization of the data and research not the simple presentation for long paragraphs of words to describe the problem and research behind. It only needs several lines and words to describe the overall situation, while the details should be explained by the visualization itself.

  • I believe that the simplicity principle is the most important because it is an important strategy in getting your point across. If the data is simple to read, more people will take the time to use it instead of figuring out complicated models. Also the easier it is to understand, the more the data can be used by all demographics of people. Younger children may be able to research them, and people without a very high knowledge of the subject will be able to decode the data and use it for research.

  • I believe that the “Ask why” principle is the most important of the 8 core principles. Although the other 7 are all very important, if we don’t understand why the data is giving us the results that they are, we won’t be able to apply those results appropriate. If we get our data results but don’t understand why the data responded in this way, we can’t make any adjustments in an attempt to improve the results next time. In other words, we have data results that we can’t utilize, which would make the other 7 core principles essentially useless.

  • In my opinion, being skeptical is the most important core principle. With all the open data we have out there today, it is safe to say that there is more inaccurate/irrelevant data that we are presented with on a daily basis. Even for something like our first assignment in this class, I found 5 good, reliable sources, and about 100 horrible ones. I needed to be skeptical of each source to extract only the valuable data for my project.

  • I believe that compare principle is the most important because the good data is comparable. For the data visualization, we should not only focus on the veracity of our data, but also pick up all data to compare with in order to have more veracious data. Last week I tried the tableau, the one difference between excel is tableau could include more data, in this case, compare data become more important, because we don’t want to misguide people.

  • In my opinion the most essential principle according to Hoven is Simplify. Too often have I been looking at data for things in this class and other classes and found a lot of it difficult to understand. I see graphs that could’ve been made easy to understand by using a standard view but instead were presented in a complex 3D view for a “wow” factor and eded up making it useless to me. By simplifying the data, it makes it easy for the average person to understand and use.

  • I think that the most important element was “compare”. Having data portrayed in text with no visualization would be hard to understand the differences between two sets that could be described in an article. By having a visualization and having the ability to compare data sets, it would make it easier for the reader to see what the author is trying to say. Graphics can sometimes lead to a deeper understanding of information and can be an asset when used correctly.

  • I think the “Explore” principle of the model sticks out to me the most. More specifically the fact that it encourages you to explore data within a visualization chart and challenge it makes for a very compelling end result.This to me could prove to be very absorbing see as though that is the best way to learn in my opinion. Doing research on any subject/data that can keep my attention is always a good time. The fact that I’ll be learning how to find answers to data or create data models on a given subject is always cool and the best part is I get to be creative with how I explore to find answers for the data given.

  • I think that the “Ask Why” principle is the most important out of the eight principles. It is easy for anyone to create an infographic that simply tells the viewer what is happening, but that doesn’t really help anyone. It’s not until the infographic is made in a way that allows us to tell why something is happening that we are able to make comparisons of any kind or draw conclusions from the data. Also, knowing why something is happening allows data scientists to expand upon an infographic’s data to further explore the subject.

  • Of the eight principles of the Hoven article, I think the most important is to Simplify the data. Hoven says that it’s important to make sure the data isn’t oversimplified and I think that’s interesting because when talking about data, I would think that people would make it too complicated to the point where people couldn’t interpret the data. I think simplification is the most important principle because if you’re going to collect data people have to be able to interpret it and understand what it means, so it can be put to good use.

  • I believe that simplify is the most important principle of the eight. Without simplification, people would not be able to understand the data in question. Communication is key to knowledge, and if the data graphic does not communicate effectively, it is useless to readers. Simplification is the connection between data scientists and the public.

  • I believe that “simplify” is the most important principle for data visualization. Simplifying the data allows the reader to easily understand the data. Many times visualizations are created that are too complex and are hard to grasp. This often leads readers to have a hard time understanding what the visualizations is trying to convey. This is the most important principle because you want your reader to understand the essence of the data and interpret what it means, without having trouble.

  • The combination of explore and skepticism are most important. Explore is a practical application of the basic curiosity which fuels the discovery of new knowledge and solutions. The ability to answer not only the question at hand, but to look at the data in new ways and ask new questions is crucial to both science and business. At the same time, the principle of explore must be tempered by an attitude of skepticism. No data set or data visualization is perfect. We must work to understand the limitations of the data visualizations that are developed by us and others. Without the principle of explore our focus can become too narrow. Without skepticism we can be too easily fooled. We do best with a combination of the two.

  • The principle that I think is most important in Stephen Few’s article is the “ask why” part of the article. The main reason I think that asking why is the most important principle is because without knowing why you are doing something, there’s no point in doing it. Let me explain, if you were given a task to do something out of nowhere, and there is no reason you were given this task then of course you would want to know why the heck you are doing this task. For me personally I like to ask why for everything. No matter what it is, i like to ask why. The reason why I like to ask why is because i like to be informed of everything. Also i am a very nosy person and like to know everything that is going on. Overall I think that asking why and knowing why you are doing something is the most important principle in Few’s article.

  • Of the eight principles in the Hoven article, I think the most important principles is to Simplify the data. If you have a lot of data that you have to present you don’t want your viewers being confused you want it to be easily understood. People try to make their graphs look fancy but end up making it more complex then it has to be. This to me is the most important principle because you want your reader to understand the idea of the data and understand what it means, without having any trouble.

  • I think the simplify principle is the most important because viewers prefer data visualization that are simple and easy to understand. Data visualization that have too many details or technical terms tend to lose the attention of the audience. By keeping it simple, viewers can continue to pay attention and are going to continue to be interested in the presentation.

  • I think that the most important principle is ask why. I believe this is true because he says this is where actionable results come from. If we only know what’s happening and not why it’s happening, we are unable to draw conclusions and determine results. With out asking why, we are just staring at a data and seeing what’s going on. This has to be taken a step further by asking the question why.

  • I believe that “Simplify” is the most important aspect of data visualization. I think the whole point of visualizing data in the first place is to make the data simpler for the audience so that they can grasp the essence of the data among the jungle of data out there.

  • I believe that being skeptical would be the most important principle to follow when comprehending data. If one wasn’t following this principle, the results that came out of the data could be false, or misleading, and basically ruin the entire operation. The more questions asked about the data, the higher chance of success and powerful data that can be trusted in the long run. A thorough investigation on where the data came from and why it is present aids the data visualization.

  • The most important to principle in Hoven’s article is to be skeptical. Data scientists must strive to ensure validity of their data sources as well as the eventual presentation and display of it. Without trust between the viewer and the creator of an infographic, there is nothing. Thus as Maurice Whetsone from QVC said, “trust, but verify” rings true yet again.

  • “Be skeptical” is the most important core principle because like everything, data is biased. Depending on the values and beliefs of the person(s) that created the visualization, the bias can skew one way or the other. It’s important to take everything you see with a grain of salt, go the extra mile to do research, and not blindly agree with the data presented.

  • In the Hoven article, the most important principle to me is the first step, simplify. I find this principle the most important because first off, if you don’t understand what the data visualization is showing, then it is useless. Most of the viewers of a data visualization are not as data savy as those who created it, so they need to make sure it is understandable to the general public. Also, the simpler the better because the viewer will have to spend less time grasping the concept behind it, and more time soaking in the data.

  • In my opinion, “simplify” is most important because it does not matter how good you complete the seven other parts, if you are not able to understand the data visualization. That is why it is important to keep it simple. Also, if it does not seem simple to understand, a lot of people do not pay attention to it because they think they will not understand it anyway. People are interested in it when it is simple and understandable, that is why “simplify” is most important to me.

  • After reading Hoven’s article, i would have to say the most important principle is to simply the data. There is nothing worst then attempting to analyze data visualizations that you have to do further research to interpret the data. The visualization should put ease and reassurance to the mind, and also enlighten you on something that you previously were unaware of. A simplified visualization set is a work of art that takes complex ideas and puts them in to context for the audience.

  • I think “simplify” is the most important principal. So many times when seeing data visualizations the first problem that sticks out with many of them is that just too much is going on. I should be able to tell with every data visualization what the point of all of this is and when theres too much going on that can be very hard to do.

  • I think that the principle “be skeptical” is the most important. It’s easy to accept the first answer you’re given, but data can be biased and asking further questions to uncover more detail is important.

  • In my opinion, simplifying the data is the most crucial step. This is because if the data is too complicated for you to understand, you will not be able to conduct an effective analysis and could possibly provide false information based on a misunderstanding. Also, if the data is simplified, it is easier to draw conclusions and see the bigger picture that the data is portraying.

  • I think of the eight principles, the first one discussed, simplify is the most important principle. I think it is important to simplify because many times visualizations can contain too much data that can be confusing. The simpler the data, the easier it will be to read and understand. Simplifying can allow data users to read a visualization quickly and efficiently.

  • I believe that the “explore” principle is the most important. It is key to not only see the data but to explore it and learn what more the data can bring you. Just looking at the data is not always useful, you need to explore what certain data means and try to understand it at a deeper level.

  • I think “ask why” is the most important of Few’s principles because it’s where we get actionable insight from. The point of business analytics is to make recommendations and uncover opportunities. Knowing how many widgets were sold in May 2013 is useless if you can’t take any action based on that insight.

  • I think that the most important of Few’s 8 principles is explore. Too often in searching for examples of data visualization for this class I have found visualizations that require some sort of user entry to yield results. What if I don’t know what I’m looking for exactly? Viewers need to be able to explore the data to really get the full value out of it. I think this is probably the most neglected of the principles, as we live in a world where simplicity is everything and tools like Siri give us anything we want to know, if we know what to ask.

  • I believe the most important principle Hoven discusses on data visualization is Simplicity. Sometimes data can present many complications when trying to compare multiple subjects, so being straight to the point is the best. When comparing data I often find it very distracting when there are many things going on in the visualization, although sometimes it can be interesting to look at, it more often just creates problems and an unclear sense of what is actually going on. So, by accentuating key data points it allows viewers to analyze data without any previous knowledge to the subject and do it more efficiently.

  • In Hoven’s article, I think his most important step is to be skeptical. It’s so easy to fall into the trap of believing everything, especially when it’s presented in a clear and organized way. But that doesn’t necessarily mean it’s true, or that it’s your best source of data. Trusting data is natural, but being skeptical helps remind you that there might not be as much truth as it necessarily shows.

  • In my opinion, the ‘simplify’ core principle is very important, and might be the most important. I believe this to be true because if the data visualization is overcomplicated and only understood by a specific audience, then it becomes very ineffective. It takes real skill to make a visualization taking something complicated into making it something that a more general, and wide audience could understand. However, when that is accomplished you are left with a very good piece of data visualization that says a lot, but could be understood by a large audience. Finally, being able to deliver a complicated message to many people can be very important in many different situations such as presenting information to your boss, or employees. Another example could be a financial advisor putting together a simplified data visualization so that his clients/investors ca be well informed, and confident.

  • One should agree that the most important core principle, when talking about visualization, is Simplify. In fact, the analysis and communication of information through perfectly designed data graphics can only be done with the simplest way possible in order to convey a story. At the same moment, the audience is better informed using less time to process the information they just visualized.

  • I think that exploring data is one of the most important in data visualization. In-class exercises lately were about which data we found bad or good and I would judge a set of data to be good or bad depending on whether I could extract a lot of data from it, while the data visualization grabs the attention and makes the information interactive. There must be something in the data visualization that pushes the user to explore and find data. Exploring is an important part; the data will seem useful or not depending on how it was made if ‘exploring’ was taken in consideration since the beginning.

  • In my opinion, simplify is the most important principle of data visualization. From the experience that I’ve had working with data, the hardest part is preparing the data, such as gathering, cleaning, making statistical adjustments, etc. If you are not able to simplify your data into a cohesive data set, then essentially you have nothing of value. The same goes for the visual. If you represent the data in a poor way which leaves the reader confused, you are no longer telling a story. The visualization loses its impact and appeal if there is complex detail, verbose legends, or paragraph labels. Relying on simplification in this process is not an easy feat, but when this is done well it makes a lasting impression.

  • To me I believe that “being skeptical” is the most important principle. I believe this because there is so much data and open data out there that people can easily get the wrong kind. Being skeptical and knowing that not all data is “good” or accurate allows you to be smarter while obtaining and searching for your data. It also leads to more accurate data in the long run.

  • I agree with the majority of the class that good data visualization captures the essence of the data. It doesn’t present you with too complex of a data tool. I do think that “view diversely” is also a very important principle because it allows for various assumptions to be made. Just like a good piece of writing (an article, an essay, a novel) leaves you with different insights, good data visualization should do the same. If we can see how various variables fit together, we can make new assumptions using the same data.

  • I would say that each one could be the “most important” depending on what you are trying to achieve. To me, I believe the most important is to “Ask Why.” I say that because you could have the most meaningful visualization but if you can not explain why there seem to be correlations or patterns, you may look like a fool when trying to explain it to someone.Another reason this is important to me is because once you realize why things are happening within your visualization, it may lead you to another discovery or realization. This idea also stands true outside of Tableau.

  • I think being skeptical is the most important principle. I believe this because there is so much open data available that conclusions may be drawn that aren’t actually correct. It is important to be skeptical so that meaningless connections aren’t made through data.

  • I find the most important of the 8 principles to be “ask why.” Asking why takes the level of thinking when viewing data to the next level. Taking data at face value is a disservice to ones self. When information is accepted at face value without the question why, it demonstrates that the data is not being comprehended. “Why” takes analysis to the next level and provides channels for further decision making based on data provided.

  • I feel like asking why is one of the most important core principles. You can look at a data visualization or results but if you don’t understand why something is happening then there’s nothing you can do about it. You want to use the data visualization to recognize what’s going on in the first place but to test a hypothesis you need to dig deeper into the data to find trends. At this point you’ll be able to create further hypothesis’s to test out.

  • I think simplify is the most important step. If a data visualization has too much going on, it becomes hard to understand and fails at its point of getting the message across to the viewers. By simplifying your information, you also make sure that only the most important stuff is being portrayed and not information that has little to no effect on the viewers experience.

  • Simplify is one of the most importing on Steve Few’’s list because data sounds complicated to most parts of the society, and when most people hear the word Data, they would just lose all interest in related topic. However, when the date becomes simple infographics that displays with picture and color or sometimes movements than people are intrigued by it. Use charts and picture images to translate data makes it easy to understand the contents of the data. Simplicity does capture humans’ eye in seconds because the majority of us humans like simple things they want the information quick and easy and simple does that.

  • I think asking why is easily the most important of the 8 core principles of data visualization. Without asking why, we just have a set of data that means nothing to us. We must ask why the data portrays certain patterns, as well as why those patterns could solve a problem. In order to draw the all-important conclusions from the data we have, we must first ask why.

  • I think the most important core principle from Stephen Few’s article on Data visualization is the simplify step. The simplify step is the most important because no matter how you present the data, if it is too detailed it will be still as difficult to understand as the raw data itself. He mentions it is important not to oversimplify and I think that is a huge part as well because if you simplify too much you are not accurately presenting the data. Without simplifying the data it would be difficult to compare, explore or even view the data diversely. Asking why would also be difficult if you can’t understand the data due to the lack of simplification,

  • In my opinion ” Simplicity” is the most important principle of data visualization. If the presentation of the data is overcomplicated, if the direction of the research is overextended, if the explanation of the visualization is over-worded the whole visualization, in all aspects is lost on the audience. In class excercises have illustrated the importance of concise and clear data. Complex visualizations distract from the point the data is trying to make, and can skew the audience’s interpretation of the data itself. Drawn out explantations lose the audience’s interest. Complex thesises dilute the point of the research.

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