Jeta Gjana

The most important takeaway I gained from this course is a clearer, more holistic understanding of data analysis, the tools used, and how data analysis permeates multiple aspects of our everyday lives. If I had to explain this course to a future scholar, I would say that MIS0855 focuses on methods of storing, organizing, analyzing, and interpreting data through many different methods. Students will also come to understand the importance of Data Science across numerous fields of study.

The most important takeway from this class in my opinion is the approach on how to write reports with tableau. The technical aspects in correcting data, creating new report with tableau and hands on approach into sentiment analysis has added much important skills. At work I learn quite a bit on the admin side of data analytical dealing with IBM Cognos and its nook and cranny. In this class, I actually learn on developing functional report.

The biggest takeaway from this course were the definitions of technology words I got to learn. Things like “big data”, “regression analysis”, “sentiment analysis”, and “hypothesis testing” are just a few. This course is really about a broad overview of the numerous trends and techniques going on in the data world. Additionally, it had a hands on work with tableau and excel and a few other programs.

The biggest takeaway from this course I notice is my new skills involving tableau. This course was the first time I was given the opportunity to be exposed to tableau. This course showed me how dynamic tableau is and how useful it can be in numerous amounts of situations. I’ve also noticed tableau a lot more in my internet searches and since I was exposed to it I can use it to its fullest potential.

The most important takeaway from this course is that we learned how to properly display data to readers. Using Tableau and Excel, we learned that there is much more to data displays that pie charts and pretty colors. The skills learned in this class can be applied to all majors when it comes to doing projects, not just business or tech people. This course gives you a solid intro to Excel and Tableau, two skills that you probably would not learn in other gen-ed courses.

My biggest take away from taking this course would probably be the ability to read and analyze data and learning to be able to make something out of data and comprehend it. Before this class, I had never heard of Tableau, but this course has given me the basic knowledge of how to maneuver Tableau if I ever needed to for a potential job in the future. Also in this course, I was able to explore all the different options in Excel that I didn’t know existed before.

The most important takeaway from this course to me is Tableau. I liked the hands-on aspect of the course because it allows you to get comfortable using other programs which we can use in our other courses and future jobs. If I had to explain to a future MIS0855 scholar what this course was about I would tell them it’s about learning what big data is and how to use all of this data by making reports, cleaning it etc.

What I found to be the most important takeaway from this course was learning that data is not always objective and accurate. As seen in the data cleaning exercises we did, sometimes just making sure the data is accurate and if not, fixing it, can take up as much time and effort as analyzing it. In explaining this course to a future MIS student, I would say that this class focuses on explaining how big data is essentially everywhere, and how you should approach it. I would also mention how you become familiarized with excel and tableau as they were significant programs in the course and obviously very valuable skills to learn.

I chose this course because I am thinking about majoring MIS. (I’m still business undecided. I haven’t decided my major yet) I thought it is a great chance to check I’m interested in this major or not and it’s really what I want. And my expectation was really right. Every ‘In-class exercise’, assignments, quizzes were really helpful and I could generally learn what MIS is. Moreover, the class was really well structured. Professor precisely tell us what we should do every week and give a lot of help doing homework. Sometimes, there were several tough questions on the assignments but activities in the class were really helpful. I really recommend this class to students who want to study MIS for the first time or who really want to know what MIS is.

The most important takeaway from this course is how I was taught real life applications to mining data, in which that is the industry I am immersing myself. Being able to use technologies like Tableau, which is used often in the real world, is invaluable experience to be able to learn in a class. I would absolutely recommend this course for anyone that wants to truly get something out of a class, and wants to make themselves a more valuable asset and boost your resume.

The most important takeaway from this class was learning piktochart while doing the Data Analytics Challenge. I have used piktochart ever since the challenge, and it has improved my presentations not only in MIS but other Fox classes. Being able to display data in a way that is understandable to the viewer, provides the presenter with more credibility because of the professionalism in the way it looks. I would recommend this course for students looking for an edge to set themselves apart from other students. It is not an easy course, but I believe the skills learned in Data Science can overall provide you with more opportunity than the other classes at this level.

The most important thing I have learned from this course is specially what data is & how to work better with excel. I feel as though I have a much better understanding at what data specially is than I have before. I would say this course is about learning how to handle data by doing things like cleaning it or being able to apply data to something like Tableau.

The most important takeaway I have is that data is everywhere. Everything is data, and different parallels and relationships can be drawn between seemingly unrelated factors. Additionally, I feel much more comfortable with Tableau, Excel and Piktochart. Overall this is a very beneficial course, I would recommend it to anyone who expects a future that involves any type of reading information. Even though its a GenEd, MIS0855 has tremendously helped prepare me for the real world.

The biggest takeaway that I have learned in this class is that the world has become technology and data dependent. Data analytics is resourceful in all industries, businesses, etc. If I were to explain MIS 0855 to a future student, I would explain that this class is the first step in learning how to understand, clean, and analyze data – things everybody will soon have to know how to do.

The most important takeaway that I have learned in this class is the usefulness of displaying data. We have learned that data can be found anywhere so it applies to every single major. But how the person chooses to display the data is important. There are so many ways to do so between Tableau and Excel. Displays of data can be useful in future business meetings or projects.

The most important thing that I will take away from this course is all of the new skills I learned with Microsoft Excel and Tableau. These two programs (especially Excel) are super useful tools to have knowledge of. Learning how to make data visualizations and charts and graphs through Tableau is such a great skill to have going forward. Also, just learning about how data is literally everywhere, and we have no idea just how much data is truly available to us.

The most important takeaway from this course is learning how to understand and work with data. I have never worked with the programs, or data in general until this class. So after learning how to use them, I can say that I have learned a lot about data. I would recommend this to students who are interested in gaining a skill on working with data using different types of programs.

The most important takeaway I got from this class is to look over your data. It is so easy to make a simple error when importing or recording data. This simple mistake could skew/ruin complete data sets. Going along these lines, having your data clean and organized is the best way to prevent or catch data errors. If you want to learn more about computer systems and how to use them properly, MIS 0855 is a great course to do so.

The most important takeaway that I’ve gotten from this course is how much better I’ve become at analyzing and interpreting data. With my newly acquired knowledge in Tableau, Piktochart, and even Excel, I feel more comfortable with my abilities to manipulate data, and draw more accurate predictions and conclusions from it. This course is all about getting more comfortable with data, and learning to analyze and manipulate it.

The most important take away I got from this course is the ability to get big sets of dirty data and to clean it sufficiently. Before this class I did not know there was dirty data everywhere such as, Facebook, Twitter, Yelp, etc.. If I had to explain this course to a student I would say this course is to help you get comfortable with recognizing data and viewing such.

The most important thing that I will take away from this course is how to clean up data. There are so many “dirty” data sets in the world and I believe that it is important to get the most out of a data set. If I had to explain this course to a student I would describe it as dealing with data. It is important to learn how to read data, write data, and interoperate data.

The most important takeaway from this course is how to analyze and interpret data. You can input data into programs such as Tableau or Excel and get results back from them. There are various ways to understand the data that you are reading, as well as different ways to show someone else who may not understand the data in a way that it clicks with them so to say. If I had to explain this class to a future student taking Data Science, I would have to say that taking this class will enable them to be prepared for future courses and a career. The programs they use will further expand their knowledge and can give them a competitive edge that others who don’t take the course won’t have.

The most important takeaway from this course in my opinion is the practical training on software that you may not have encountered before this class. They allow the user to not only recognize trends in data, but put them together in order to get a more complete story. The training in this class is generalized enough to be applied to just about any data set, and as a result students who take this course have a significant leg up against those who do not.

I believe that data analytics is an important skill to have in a business career. You will be able to work with data and be able to analyze data in order to make an informed decision. If you would like to succeed in your career, the more you know Excel, the more you practice daa analytics and Tableau, and other data analytics skills, the better it is for stepping up the ladder in your career.

This course has greatly developed my ability to analyze and visualize data properly through the cleaning of said data and the creation of graphics to communicate the patterns found in the data. Previous to this course I had no experience with Tableau, however now it is a tool I feel comfortable using when trying to visualize patterns in data. If I were to tell another student about this course I would tell them that this course will help them develop their analytics skills which has been cited as one of the major skill area’s employers are looking at today. After taking this course you will feel comfortable working with large data sets, visualizing trends, and leave with much better understanding of the science behind understanding big data.

I think the most important takeaway from this course would be how important data is and how data should be analyzed plus visualized. I think learning how to use Tableau was an important takeaway as it could be something I could offer to potential employers as a skill. If I had to explain to a future MIS0855 scholar what this course is about, I would say is that data is everywhere and in this class your learn why its so important. As an MIS major, I believe this course is a better introduction to MIS than MIS2101 and you actually learn more in a sense of using data to understand it and make decisions.

I think the most important takeaway from this course was learning that data is everywhere and is relevant to us in many ways. If I had to explain this course to someone else I would say it teaches students how to find, sort, and analyze data to make it resourceful for others. For example, using the data collected and putting it into Tableau tot create a visual representation of the data that makes it easier to understand. Another important part of this course was learning how to utilize data when making critical decisions.

Personally, the biggest takeaway from this class is how important data is. Data can be used in so many different ways for so many different things which is why it is necessary to have correct and clean data. MIS0855 is a course that teaches you some of the many things you can do with data. This class makes you familiar with excel and Tableau which is something that many people do not fully understand how to operate. This class is very hands on having in-class activities that help with assignments and projects that you have to do in class.

In my opinion, the most important takeaway from this course is learning how to analyze data. We must first be careful of what data we choose, know how to clean that data, and finally know how to derive information and knowledge from data. This course has taught me all of these steps, and how to use tools such as Tableau and Excel to do so. If I was explaining to a future student of the course, I would say this course is all about how we can extract useful information from data, and in doing so it teaches you how to use helpful tools including Tableau and Excel.

I think the most important takeaway from this course is the hands on experience of analyzing and cleaning data. The softwares we used in the course actually taught me how to make use of the topics we learned throughout the course and gave me the ability to apply the stuff we learned. I am now able to use Tableau, Excel, and Piktochart because this course taught me a lot about each of them.

The biggest takeaway from this course is how important it is to analyze data and finding errors in data. I would tell someone that this course teaches you how to sort, clean, and use data in Excel and Tableau. Also, how you would transform data into useful infographics.

I think what I learned the most from this course was how to properly clean data, analyze it, and effectively display it to an audience. There is a lot that goes into analyzing data and I believe the course taught me the basics of analyzing data. Although it is a very complicated process the course broke it down so that it was easy to learn and understand and I can confidently say I can clean, sort, and display data proficiently which is a valuable skill to have in 2017.

I think that the most important takeaway from MIS0855 is that data is everywhere. This data can be dirty data, also known as data that contains errors. Even though data can be dirty, it is still everywhere we look and affects everything we do. If I were to explain to a future MIS student what this course is about, I would say that the course is all about understand how to find data, understand it, and make further analysis on the data. As an MIS major, I would definitley recommend this course becuase I thought the class was very well taught with many hands-on, in-class activities which really emerges students into the world of data.

The most important takeaway for me from this class, is realizing that even things you don’t think are data, are in fact data and since we are surrounded by data, it is important to realize the good from the bad, and how to handle it. In addition, the course helped me figure out how to, not only realize data, but how to use and predict from data. If i had to describe the course to someone, I would say this course was about locating and using data in a way to benefit ones self, either by knowing how to formulate data for easy structure and visual, or to be able to use pass data to find correlation in order t predict a future outcome.

I think the most important takeaway for me from this course is that data is literally everywhere, and there are multiple different ways to fix, analyze, interpret, and visualize data. If I had to explain to someone what MIS 0855 was about, I’d tell them the course first introduces you to the different types of data and then continues to teach you how to interpret and manipulate data. You learn to differentiate between good and bad data, and then learn how to fix bad data, as well as how to put the data into visualizations for a better understanding of the story the data is trying to tell.

I believe the most important takeaway from this course is understanding how much data is out there flowing around. It is important for us to know what do to with all this raw data. Being able to analyze, interpret, and visualize data makes every possible thing easier in life. This class is about learning hands on experience with technology and data tools. You will learn how to make your life ten times easier if you have a handful of data.

The most important thing I took away from this course was the understanding that their is different types of data, and different ways in which data is handled. It is important to grasp the breakdown of analyzing, visualizing and clarifying data, because these steps allow people to better comprehend the data that is being presented to them. Prior to this course, I did not fully know what data science was. This class has taught me a great deal about the importance of data as well as the behind the scenes process in which data scientist go through to bring that data to life.

The most important takeaway from this course is that data is everywhere. Before really learning about data in depth, you don’t realize how much data surrounds you on a day-to-day basis, but it really is everywhere and people are always analyzing it whether they want to or not. In my opinion, gaining hard skills within actual data analysis/visualization programs like Tableau and Excel went along great with the course. It’s one thing to just understand what data is and the different types, but its better to be able to use tools to help you analyze it better and see what it means visually. If I had to explain the content of this course, I would say it is really learning about data in general including the different types, where you can find it, cleaning it and being able to figure out ways to visually represent it within programs like Excel and Tableau.

The most important takeaway from this course is that we can have insights about anything when we have data about it. We can do almost anything from data as long as we are using the right tools and the right techniques. The way I would explain what this course is about to future MIS0855 is that this course is teaching them how to work with raw data, how to make sense about them and how to benefits from the data.

I think the most important takeaway from this course is that data is literally everywhere and being able to actively sort and analyze data is something future employers are going to want from their employees/new hires. In this class, I learned that there are so many insights that you can pull from data and that those insights are crucial in any and every work environment. Before this class, I didn’t realize how dependent my future career path was in data analytics and how often I actually encounter and use data every day. For future students, this class essentially teaches you the importance of big data, why it’s relevant and applicable and how you can sort, analyze and display big data. It’s your first introductory course in properly sorting raw data and teaches you how to, essentially, read data to produce insights.

This biggest takeaway from this course, for me, is that data is everywhere, and is in every aspect of society. Every major should not how to find data, clean data, and analyze it. Having this skill set will come handy in your everyday life. If I were to explain this class to another student, I would tell them the course shows you data in its simplest and most complex forms, and by the end of the course, you will know how to handle both. It’s an introductory course that will prepare you for other courses, and not just MIS ones.

My biggest takeaway from this course is the importance of data. With us being a business school no matter what major, the one thing we all use and rely on is data, so it was very valuable to better understand the logic behind it and how to interpret it. I would say analyzing data is definitely a challenge for most people without a technological background. However, MIS 0855 broke it down so well into terms that I was able to enhance my prior knowledge to data. I learned so much more when I look at data from this course.

I think the most important takeaway from this class was how important data is and how to clean it properly and analyze it. Data can be viewed in so many different ways, so it’s really important to make sure the data is displayed correctly and shown to the audience in the proper way, whether it is in an infographic or a table or any other display. Also, it is really important to make sure the data is not dirty because that can skew all of the data and someone’s opinion of the data. In this case, the data will not be correctly displayed and the people looking at the data will be misinformed. I would say this course is about how to properly extract and analyze data and then how to use the data the display to our audience.

I think the most important takeaway for this class for me was the importance of cleaning data and using Tableau. So many companies have such an abundance of data out there that they don’t know what to do with. Taking the idea of cleaning the data and making it into useful information is something that many companies are looking for these days, and I think that skill will be very useful in the future. On top of that, I had no experience with Tableau so that is something I am going to take and use with my career in the future. Tableau is an excellent program to demonstrate how you can manipulate data into useful information, and I am happy to have learned the basics of it.

My most important takeaway from this class was just to see how much data affects our day to day lives more than i have ever imagined. Obviously i understand the huge part technology plays in our lives, especially when compared to other generations, but data can tell such a telling picture about our past, present and future. If i had to explain what this course was about, i would say it enlightens you on the future of companies and shows you realistic applications of what we are learning. Sometimes classes may seem dull and boring because we can never perceive to understand how this applies to our future, but with this we can see data being used in our everyday lives.

I think the most important takeaway from this course is how important data visualizations are. Not only is it important to gather and analyze data correctly, you must also represent the data properly. Data visualizations, through many different softwares, convey messages plain text simply cannot. This class showed me just how important data visualizations are and supplied me knowledge and skills I can use throughout my professional career.

I think the biggest takeaway from this course is just how quickly and drastically our world is moving toward data. Data is the future of not just the business world, but society at large, with large amounts of data being taken from social media, Google searches, reviews, etc. Data is an incredible indicator and predictor for success for companies. It’s more than a decision making tool, it’s the sole basis of most decisions in a successful work environment. Similarly, data is nothing unless interpreted in useful ways. Programs like Excel, Tableau, and many others provide us with interesting ways at looking at data and interpreting it. This course is really good at highlighting the importance of data visualization as not only a practical use for data, but also as a creative one too. I know that my career and many of my peers’ careers will be defined and shaped by data.

I think the biggest takeaway from this event is that data is the amount of ways that we can analyze data. Just by using Tableau and Excel, we were able to learn that there are many different ways that we can interpret the data, as well as visualizing it. Another thing I learned was how complicated data can get. The best example of this was the cleaning data assignment, how when the data set is too large to go through, there are many ways to manipulate the data to get more accurate answers. There are lots of people who look at a data set and do not know what to do with it, and this class does a terrific job on teaching students what you can do with a dataset.

I think the biggest take away from the course is different ways to analyze data. For me personally, I was able to work with excel more on the data side. There are other courses at Fox that introduce to excel, however this was honestly the most helpful course for what I am trying to accomplish in my career. I was introduced to Tableau, which is a very helpful application for analyzing data. I will definitely being using Tableau in the future. Honestly every business major should take this course as their Gen ED science class.

My most important takeaway from this course would definitely be being able to apply what we learn in class to topics that mean something to me personally. I feel like once you take what we learn in Data Science outside of the classroom and into real life with real life things, it shows that you truly understand the work. If I had to explain to a future MIS0855 scholar what this course is about, I would say that it’s about understanding everything about data: what data actually is, different types of data, what and how it can be used, and then applying all of that to real life things, because data is everywhere.

To me, the most important thing I have taken from this class was the ability to visualize data and present it in an effective way. This course should be viewed as not only being able to analyze data, but also being able to show it to an audience. This course also allows students to dive into current issues with data analysis and understand the slang behind some terms used by IT specialists. Finally, this course does a phenomenal job of breaking down terms and applications of big data and allows for a complete understanding of each element of data.

The most important thing that I can take away from this class was learning how to use Tableau and visualize data. Before this class I have never heard of the software Tableau. The only software that I used for data before this was Excel, and I must say Tableau is a much better way to display data. Now that I have learned about Tableau I can use it for other classes in the future to give my work a better appearance. This class allows students to understand everything about data, from what data is all the way to working with different types of data. It taught me how important data can be and how the smallest errors can give you bad data. This class taught me the data is all around us and everywhere you go there is some type of data.

I think that the most important takeaway from this class is learning how to analyze and visualize data using Tableau. Working with data an cleaning it is really important as well. If I had to explain this course to someone I would explain it as that this course is all about data. It allows students how to work with the data all the way from cleaning them till visualizing.

The most important takeaway from this class is how valuable data is for companies and how important insights can be made to benefit both the companies and consumers. The emphasis of utilizing programs to turn data into knowledge will be useful skills in the this age of big data and information overload. Tableau and excel were effective tools when analyzing data and obtaining key insights and it seems professionals are still reliant on these programs for data analysis based on the articles read throughout the class. Although qualitative analysis has it complexities, I wish the course focused more on it and went into deeper detail about qualitative analysis since it seems to be a skill high in demand.

I’m a psych student, and I know the data is very important part of the research study. and before this course, I had a statistic course, but there have some differences between those two courses. The most important thing I learned of this course is how to use Excel and Tableau. I will recommend this course to future students, I will say this course will help you not just in the college, but for the whole career after yours graduated.

The most important takeaway from this class was developing your data analysis skills to a software called Tableau. Being able to intergrade and certain data sets that may be dirty or clean into the program and finding different ways to look at it. Another big takeaway is, how much data is used in our everyday lives but we don’t realize it because it may not be in number sets.

This course taught me that data is everywhere and that are many different ways in which that data can be analyzed. One main takeaway with this is that when analyzing data it is important to make sure that the information within your data set is correct and that there are no mistakes. This ensures that the data does not become “dirty”. In addition, when displaying visuals about your data, for instance, using a pie chart or bar graph, it is important to use the appropriate visual. By doing this, the audience will be able to fully understand the message you are trying to convey with that data.

The biggest thing that I got from this class was the tableau skills. I do not have a lot of hard skills so this was a very important thing for me to pick up. I also just have a better understanding of data now an the role it plays in our daily lives. I think these two things combined have helped me prepare for the future even more.

The biggest take away I got from this course would be the lessons we learned about practical applications of data and how to use excel and tableau. I took the MIS class required for my major and hated the professor and subject and got a low grade, but I thought that it was a decent subject so I took this elective the next semester. I can honestly say I learned more useful tools in this class than I did in the big MIS class and the online Excel course we are forced to take. I would’ve taken this class just to learn tableau alone but ended up learning useful tips on how to be more efficient in Excel as well.

The most important takeaway from this course for me was the usage of Tableau. I heard a lot about this data visualization software but I never really used it. This class helped me learn this software. This course also helped me brush up my excel data manipulation skills.

Although this class was a gen ed for me I learned a lot of stuff that is important in my major. As a communications a major, we look at a lot of data when creating advertisements or when finding out information about a brand. The most important take away from this class is having clean data. Before this course I kind of just assumed that if data was created by a reputable source than it was correct. I now know how to go through any data set, small or large, and how to clean it and make it valid for use.

Although for me this class was a gen ed, I learned a far amount. I would say I improved my technical skills, I learned a lot about tableau and excel which are important skills to learn. That is what I would say as the most important takeaway from this class is the knowledge of how to use this programs. This programs are very useful skills to have in the business world and can help a lot on resumes.

I would have to say that the biggest takeaway from MIS0855 is the importance of data and its applications. For instance, raw data is useless unless you organize it, clean it, and make use of it. I learned how to display data in this class from using softwares such as Tableau and Excel.

The biggest take away i learned from MIS 0855 is using discovering another database application other than excel or acess
Tableu comes in handy and makes visual presentation looks better

I think learning how to use tableau was my best and most important takeaway. I am an MIS major, so i knew a lot of the topics that we discussed about data. However, I knew nothing about Tableau before this class and I learned that it is very useful.

The most important takeaway I received from this class is the importance of checking your data. There are several instances when data is dirty and it can make a large impact on the information someone is trying to develop. If I had to explain what the course was about to a future student I would tell them that it is about data, to say the least. You learn about the different ways in which data can be utilized and you learn how to actually utilize it in those ways.

The biggest takeaway from this class was how important it is to have clean data for a proper analysis. I think learning how to use tableau to create a visualization for the data is important and relevant to everyone regardless of what their majors are. This course taught me how to look at data and clean it so the results are not skewed, then turn it into visualizations that are easy for audiences to interpret.

The most important takeaway from this class would be how to analyze data and that data analyses can be skewed. How to clean data and look for errors was also useful. This class showed me that it is important to know how to view/analyze data no matter what field you go into.

I would say that the most important takeaway from this class is that, generally speaking,” it’s not all about the numbers” – meaning that while data in and of itself is powerful and plenty, the analysis of data is even more important. For data to be able to engage an audience and make persuasive arguments, it must be organized, clearly evaluated, and appealingly visualized with precision. I would say this class is all about understanding how to approach big data sets from the start. It is focused on learning: how to ensure the quality of data being used in analysis, how to best measure and compare specific pieces of data, and how to present findings in a way that fully explains the illustrated data and makes a coherent point by telling the data’s “story”.

I was really looking forward to working in a professional environment at Cross America. I knew that I would be able to expand my knowledge in business by actually being in a workplace/office opposed to a classroom or retail store. I realized that people working in my office were generally laid back and cool people. I think some classes paint the professional world as uptight and always formal, but this does not seem to always be the case. I learned to chat about everyday things with my superiors and co-workers in addition to discussing work. It was nice to actually be contributing to a company. Classes do not have a real world impact like working an internship does, and I liked that what I was doing mattered to the economy.

The one thing that you can never learn unless you are in the work environment is that you don’t always get recognized for every effort you make. Unlike in the classroom where you always get a grade as a reward for your hard work, in a professional setting you don’t always get that recognition. Sometimes even mid-project, the whole thing is cancelled or whatever you worked on is not even used and is thrown in the trash. The lesson is to get used to it, know that your work is valuable and keep getting better at your job.

Throughout my experience, I have learned that many tasks aren’t as simple with a direct answer. Many tasks required me to reach out to various members in order to retrieve data and get specific perspectives. These tasks are best performed through communication and working with others as a team. Next, we aren’t always given tasks we have done before, sometimes we are given new assignments that require us to learn new skills in order to achieve them. Next, time is another important thing to keep in mind, it is necessary to prioritize tasks depending on what is needed and when. Deadlines get pushed around a lot so you have to be ready to work on different projects at the same time or shifting between projects based on priority. Finally, the biggest difference between the textbook and actual experience is when you complete a project on the job it feels a lot better to accomplish knowing that you made a difference in a process or an actual outcome within a company.

In my internship something I learned is to get questions answered sometimes I had to be persistent. To solve problems it was not as simple as walking into office hours or asking a question during class. I had to understand first who would be able to help me and what I specifically needed from them. In the first few weeks of my internship I would go to meetings and leave realizing no one really gave me what I wanted. So I learned to have specific questions ready and different way to ask these questions. Most employees do not care about interns, but throughout the summer I learned how to make people value my time so I could complete tasks. This persistence is not something I could have learned in the class room.

Throughout my internship I have learned a lot of technical skills and soft skills that you cannot just learn in a classroom. Some of the technical skills I have learned are performing test execution audits and setting up databases in MS-Access. Audits would be very hard to teach effectively in class because its really something that you need to deal with real testers and situations for a period of time in order to learn. Creating databases in MS-Access you can learn to an extent in class but it was so much different doing it in the business world where many of your requirements are not ideal and theres no answer in a textbook to your specific problem, its a lot of learning on your own through trial and error. Some of the soft skills I have learned are effective communication, determining priority between multiple projects, and being a team player. For me working on the IT Governance team has provided an interesting team-environment where I work with QA, Change Management and Compliance daily and each group has different skill sets and needs. So determine how to communicate with each individual, who to help first and how to work everyone has been essential.

Throughout my internship as a software developer I have learned different coding languages and have learned to research on the web. In school everything is set up and we learn php as our main language. In the beginning of the project I was in, people were debating which language to develop in. Our team decided to code in a new rising coding language. I also became a better developer by learning how to research on the web. I have learned which key word to use when looking for different pre-written code. Also getting the experience in the working environment was something I was not able to pick up at school. Working in an open area with co workers right next to me was not a setting I have worked in.

The main skills I developed over my internship that weren’t learned in the classroom dealt with professional communication, and more specifically email etiquette. At Pfizer, the majority of people I interacted with were at least twice as old as me, so there was certainly a learning curve on how to effectively communicate with them in a professional manner. When I first started there, I would spend a lot of time editing and revising my emails in order to come off professionally and while it seemed tedious at first, it truly paid off. My sponsor and other colleagues took note of my email skills, and would frequently come to me to distribute large emails to members of the organization. While this may seem like a small thing, it was rewarding that higher-ups on my team noticed the effort I put in and this ultimately helped me get my name out there at Pfizer.

One of the many things I learned at my internship over the summer that I could not learn in the classroom is the importance of asking questions. During meetings with stakeholders or project sponsors I learned it was vital to ask questions to really dig down to the core of the problem or issue at hand. I also learned the importance of building relationships with those you work with. This is important so whenever you come to a roadblock or need help you can reach out to those you’ve built these relationships with, and they can help you with any issues. These two key learnings were vital throughout my internship at BD.

Facebook is the online data-driven service that I use most frequently. For Facebook, each row of the spreadsheet would represent a different person. The first column could show the first name of a person; the second column shows the middle name, and the third column shows the last name.. That way you could count how many people have similar names. Another column could show the number of friends a person has while the next column could show the number of photos the person has. Other potential columns include: number of posts, number of private messages sent/received, number of liked pages, high school name, college name, etc.

One data-driven service that I use quite frequently is Instagram. The rows would represent different Instagram accounts. Some of the columns would include: the person’s user name, the number of pictures, the number of followers, the number of people followed, average likes per picture, and the number of tagged photos.

One data-driven service that I use at work is HEDWIG. It is a service used by residence halls to log packages for students. One row could represent a student’s name or a package. The information in the columns would include a student’s TUID and room number. For the package the columns would include the carrier, where it’s shipping from, the date it was delivered, and the bar code we need to scan.

The data-driven service I use the most regularly is Blackboard. If I want to store the data in the spreadsheet,
1st row: Name of the Subject and subject code
2nd row: Name of Professor
3rd row: The name of the file(assignment) I uploaded on the blackboard
4th row: The date I uploaded my file
5th row: the score of each assignment
The other rows: The content of the assignment, The magnitude of the assignment(how important it is in %), The type of the file(ppt, word, pdf)
By using this spreadsheet, I can know how many files I uploaded in a certain period(1 day, 1 week, 1month), the average of my score, which subject has the most assignments and so on.

I use GroupMe, a group message app, very often. It would be interesting to break down everyone’s individual groupme data. One column would be name of the person, one would be how many groups they are a part of, one could be how many messages they send on average each day.

A data-driven service I use frequently is something called coriscahockey. Corsica hockey is a data base that shows detailed advance hockey statistics. A spreadsheet that would contain the data of this service would have rows such as: player name, player position, player team, and each individual row for different player statistics.

A data-driven service I use regularly is an app that logs my study hours. Each row could represent a week while the columns would include avg. study hours per day, study location, and how many hours left until the user reaches his or her weekly goal for hours studying.

One data driven service that I use regularly is blackboard. A row on a spreadsheet could represent each course that I’m taking. The different columns in the spreadsheet could contain information about the professor of the course, the data and time of the class, and different assignments for the class, as well as my grades on those assignments.

A data driven service that I use regularly is Apple Music. A row in the spreadsheet could represent each artist in Apple Music. The columns in the spreadsheet can be how many songs, how many albums, genre(s), rankings (ie #3 on the pop charts) and also how many total streams they have gotten.

I use Spotify everyday. If I wanted to analyze the data derived from this app, I would be most inclined to study the artists I listen to most often. Thus, each row could represent my 10 most listened-to artists. A column could be the song or album of that artist I listen to the most.

A data driven site/app that I use almost everyday is Apple music. If this data was transformed into a spreadsheet it would include things like genre, name of playlist, artist in the columns. Then in the rows it would include the name of the song.

Instagram is a data driven app that I use everyday. If the data was transformed into a spreadsheet it would be based off each user’s page. The row would be each Instagram user’s page and the columns would be based off the number of followers the page has, the posts of the user, as well as the likes and comments they get on each post.

I use Blackboard everyday as a data driven app. The data if made into a spreadsheet would have my classes, teachers, and grade in the columns. In the rows would be the full name of the class, who teachers that class, and the specific grade I have in that class.

A data-driven app I use on a regular basis is SnapChat. The row would contain the individual’s username, in the columns there would be the number of snaps they send in a day, how many streaks do they have, how many snap points they have, the number of snaps on their snap story, and the number of users they have on their “Best Friends” list.

A data-driven app I use everyday is Spotify. If Spotify’s data were to be transformed into a spreadsheet, it would report song titles, artists, albums, and the type of genre the song falls under. The row could represent its rating in your playlist or your most recent songs listened too.

A data-driven source I use every day is my Scottrade brokerage account. I use Scottrade to invest in many different stocks as well as researching other stock quotes for future stock purchases. Some columns I use in my excel spreadsheet to track my investments are stock price, stock quantity, gain/loss, dividend distributions per share, and total gain/loss. Each row lists the company’s name and ticker symbol.

I frequently use Spotify. A good way to organize a Spotify spreadsheet would be to make each row its own song. Columns would each be details about the song. For example, these could be things like artist, featured artist, producer, name of the song, duration, release date, album, genre, number of plays, stream or download etc.

Canvas is a data driven source that I use often. If it were in a spreadsheet, the first column could list the class, and the following columns could contain other information pertinent to each one. For example, due dates, grades, and assignments could all be listed in the following columns. This would be a great way of organizing an academic schedule.

A data driven service that I frequently use is Amazon. If I wanted to analyze Amazon data in a csv format, I would have the product name, product number, price list, reviews using 1-5 number. From this data, I would be able to analyze if certain products are most frequently purchased by customers.

A data driven service I would use would be Twitter. My data I would be storing would be, the time majority people tweet on the East Coast, the average likes or retweets they receive on post, the area in which the tweet the most. From this data I would be able to determine which States have the most twitter activity.

A data driven service that I would like to see in a spreadsheet would be Amazon. I would have rows for the product name, product description, and company that makes it. For columns I would like to see the price of the product, the SKU number, average star rating of the total reviews, and number of times that the product has been purchased. By having it in this format, I believe that the information would be keep in a clean matter, allowing the data to be easy to follow.

I use GrubHub service often times and I believe if I’d store their massive data in a spreadsheet would be:

Column 1: restaurant ID
Column 2: User ID
Column 3: Restaurant Name
Column 4: Restaurant Location by Zipcode
Column 5: Dynamic User ID Location
Column 6: OrderID

All the rows would be values of each specific column.

A data service I use regularly is Twitter. A spreadsheet for Twitter would include rows for the profile picture, tweets, likes, retweets, followers, and columns would include the number of tweets, likes, retweets and followers.

I use the ESPN app often to check scores of games which I’m interested in and check out specific stats of players I like. To make a spreadsheet I could make rows of the teams, players, positions, etc. and columns filled with things such as points per game, blocks, points allowed, passing yards, etc.. You could filter this by being able to minimize to specific positions of whichever league you’re looking at or on a certain team as well.

Twitter is a data driven service used daily by millions of people. Twitter stores posted tweets. A tweet would be a row in the spreadsheet. The columns in the spreadsheet would be the name of the person, the date, the time, and the number of characters.

Uber is a data driven service that many people use regularly. Uber stores uber rides. In a spreadsheet, a row would be an individual Uber ride and the columns would be how long the Uber ride was, the distance, the traffic involved, and the number of people riding.

Canvas is a data driven service used daily by Temple students. Each row in the spreadsheet would represent classes the student is enrolled in. Some of the data columns would be syllabus, schedule, grades, assignments, and announcements.

Google Drive is a file storage service developed by Google. Google Drive stores all kinds of files including Word documents and Powerpoints and allows users to collaborate on documents. A row in Google Drive’s database would be information on an individual file. Columns would include metadata on the file including the upload date, contributors, name, last edit date, size, and the actual data included in the file.

The grade center in Blackboard records the grades earned by each student. If put in to an Excel spreadsheet, the row would be the grade received, and the columns would include what class the grade was for, how heavily it is weighted overall, what kind of grade it was (quiz, exam, homework, etc.), who the professor of the class is, and date the grade was posted.

The data driven service I use everyday would have to be Canvas. If I were to make an Excel spreadsheet for the information that is stored on Canvas the rows would be all my different classes. The columns would represent professor name, my grades for each class, upcoming assignments, assignments completed, and dates for exams/projects.

Amazon stores information about different products for consumers to search and choose from. If the information was to go on a spreadsheet, the columns would be: Product name, Category, Price, Seller, Rating, Number Purchased.

A data driven service I use everyday would be snapchat since it’s used by millions of users every second. If I were to store the data for snapchat in a spreadsheet what each column in the spreadsheet represent would be the time I posted my snapchat story, how many people viewed it, and how many responded to it. The rows would be individual users I sent a snap too or users I got a snapchat from.

A data driven source I used regularly is Twitter. If data from Twitter were put into a spreadsheet, a row would be an individual’s Twitter handle, and the columns would be things like the individual’s total number of tweets, number of tweets on a specific day (or over a period of time), number of retweets, number of likes, number of media posted, number of followers, number of people the individual is following. Or, a row would be an individual tweet, and the columns could be the Twitter handle of the person who made the tweet, the number of characters, the time and date posted, how many likes and retweets the tweet got, and how many times the tweet was viewed.

Amazon is a data driven source used regularly by millions of people. If i were to use it and put it in a spreadsheet, some of the columns of data ratings would include product name, average rating, price, manufacturer and category. I could also put average shipping and handling if that is done through the individual seller or amazon and is a fixed price.

Instagram is a website and app for sharing photos and videos. One row could be for pictures and another row could be for videos posted. The columns could be how many likes, comments, and the date it was posted.

UberEats is an app I use, which is a data driven source. Rows would be location, restaurant, name of food, order time, delivery, and delivery driver. Columns would likes, dislikes, comments, and date.

YouTube is a website/app that millions of people use everyday to view videos about all different kinds of things. In Excel, a row would be a specific video and the columns could be the name of the video, the date posted, the genre of the video (music, sports, travel, etc.), the length of the video, the number of views it has, the number of likes/comments it has, whether the video has ads on it, and the name of the account posting it.

Amazon is an app I am constantly using to buy things on the go. I would put the items bought in the rows and in the columns I would put information such as: price, amount of time the item remained in the buyers cart, date of purchase, the delivery time, information on whether or not the buyer wrote a review, and if the item was kept or returned.

One of a data-driven service is the Linkedin, a professional social networking site for business community. Some of the column would be the LinkedinID, Experience, Skills, Accomplishments, Place of work/ Study, and Contact Information. The rows would be information of each person that create a profile in Linkedin.

Amazon is a service with inordinate amounts of data behind the scenes. I think if I had the data for Amazon it would likely include product names, price, customer rating, a short description, and seller. If the data was made available things like number of sales and number of returns or complaints would be extremely helpful to amazon and its sellers; with that information they could fix issues with their products and bolster their sales numbers.

An example of a data-driven service that I use regularly would be Amazon. If I were to store the data (of my purchases) for that service in a spreadsheet, the information would be formatted by rows = list of products and columns = product name, order date, shipped date, delivered date, delivery location, price, and average customer rating. We could also add a column titled “type of product.” This would be a cool way to analyze my shopping patterns of either house supplies, kitchen supplies, office supplies, etc.

A data driven service I use everyday is my Citi credit card application and the Citi credit card online banking. If I wanted to integrate the data into Microsoft Excel, the rows would be categories of the purchases. For example, the rows would be named entertainment, merchandise, restaurants, organizations, and vehicle services. On the other hands the columns would represent the time period such as November 2017, October 2017, September 1017, and so on. The cells would be the total amount of money spent on the purchase category in accordance with the time period accrued.

Netflix is a data-driven service that I use often. If I wanted to create a spreadsheet to store data each row would be the name of a movie/show and some examples of the columns would include genre, length, rating, actors, director, and Netflix category.

Snapchat is an example of a data-driven service that I use every single day. If I created a spreadsheet to show Snapchat’s data, I would make the rows be individual users. For the columns, I would put their snap score, how many snapchats they send per day, what filters they used, and how long their streaks are with other people/their highest snap streak.

Instagram is a data-driven service that I use everyday. If I wanted to store information into an Excel spreadsheet, I could do multiple things. One spreadsheet could include making the rows, the individual account’s username. In the columns, I could put the number of followers the account has, the number they are following, how many pictures have they posted, how many likes have they received, the average number of likes per a photo, and number of photos they have liked.

One data- driven service is black board. If I put blackboard’s data into a spreadsheet I would have many different columns. One would be courses so that the data in the other columns can be organized in rows by course. Then it would be assignments and grades. All the data would be filtered by courses.

rotten tomatoes stores movie reviews. the row will be short reviews, and columns will be the name of the movies, how many stars the movie got (0-5), the year of the movie produced, names of the director and main actors, which type the movie is, and who writes the reviews.

A data driven service that I use on a regular basis would be YouTube. Some examples of columns could be the YouTuber’s username, genre of video, and what is trending. The rows would include the information of these categories or a potential link to any given video.

An example of a data-driven service I use regularly is my bank account. And the spreadsheet would have different columns. That is my spendings like cash and different categories like food, entertainment, and transportation.

A data driven service that I use regularly is Facebook. On a spread sheet, each individual row would probably be a facebook page. Each column would then be an attribute of that facebook page. There are probably over 100 collumns per facebook page, however some of the columns would be, an Indentification number, the Page name, page type, Date created, Login email, login password, gender, description, etc.

One data driven service I use regularly is Amazon. This online retail site keeps record of every purchase I make. In a spread sheet the item I purchase would be in rows and the columns would include price, order number, seller information, and my method of payment.

I use Blackboard just about everyday, even if it is just to check if any grades have been entered, which they usually haven’t. If it were to be converted to excel, some rows could be grades, upcoming assignments and and the email address for the professor. The columns in this sheet would be the classes themselves, and with those rows showing everything about the classes that is necessary.

A data driven app that I use regularly is Serato, my personal database for music. If I were to make an Excel spreadsheet for the information that is stored on Serato the rows would be the different crates I’ve made. The columns would be for the song name, BPM (beats per measure), artist, album, and the year that the song came out.

A data-driven service that I use regularly is blackboard. The rows would represent each individual class. There could be a lot of columns. One could be the professor. Another would be the name of the course. The CRN for the course could be used as the id, or you could just assign an id to class. You could also have a column for my grade in the course. Lastly, there could be a column that is just a description of the course.

Ebay is a data driven source used for online shopping. Columns would be product type/category, price, sales, etc and rows would be product names, quantitative data, etc. Buying behavior and trends can be identified from the data to gain key marketing data for better overall market insights. This can include prediction of trends, pricing, promotion, etc.

A data driven service I use frequently is Amazon for online shopping. The row would be my my order number. And some columns could be the items I ordered, the price I paid, method of payment, shipping address, company the product is coming from.

A data-driven source that I use almost every day is Amazon. I buy multiple items from this company a week. if I was to put my order history into a spreadsheet I would put the products I bought into the rows and for the columns, I would put in details such as price, customer rating, and the category the product falls in and its shipping and arrival dates.

I use Twitter a lot and if the data used from Twitter was placed into a spread sheet the rows would most likely consist of trending topics, tweets per day, number of total tweets, and most used hashtags.

Twitter is a data driven service that I use regularly. If I put twitter data into a spreadsheet, one row could represent tweets that I compose myself. Another row could be tweets that I retweet. Some columns could be the time the tweet was composed, the date the tweet was composed, the number of likes that the tweet received, the number of retweets the tweet received, the amount of comments and some of the most popular ones.

Data Driven Service – Gmail

The columns will store the data like categories

Example:: NAME OF SENDER SUBJECT

The rows will have a more detailed fields following the column so for example

NAME OF SENDER. Subject
Joe MIS weekly questions

Data Driven service : Stats.nba
In an excel spreadsheet, the NBA stats per player would be listed. Player/Team names would be in columns and the individual statistics would be in rows. Statistics used in our previous in class exercise for NCCA such as field goal percentage, etc. An additional row that could be added that wasn’t included in the in class exercise could be forecasts for players in future games.

Instagram is a data driven service that I use everyday. I could have the rows be the usernames. The columns could include things like number of followers, posts, likes, and comments.

DARS is a data-driven service that I regularly visit. Rows could be individual courses, while the columns would consist of all of the descriptive information and student data; these would include fields such as Course Location, Semester/Year, Subject, Final Grade, Grade Point Earned, Number of Attempts.

1. The subject of our group project is “University Data Analysis”.
We feel data from universities is easily accessible because these businesses tend to brag a lot with statistics such as job placement rates, acceptance rates, retention rates, etc. Therefore, an in-depth analysis of such data will be possible and effective.

2. Group members: Dan Moy, Anne Lin, Jeevan Jaganath, Henry Fok

1.) The subject of our group project is about how women’s and men’s professional soccer varies in popularity and why this is the case.
2.) Group members: Caroline Doyle, Graceanne LeNoir, Tom Hess, and Alexa Lessard.

The subject of our project is looking at NBA allstars, like over the past few years, and looking at those allstars measurement at there rookie predraft combine and seeing if certain factors in measurements can predetermine an all star, or at least boost their chances.

Group Members: Myself (Julien Bombara), Sayem Rahman, Kaoi Peixoto, and Nicholas Napolitan

1. Relationship between police positioning with the crime rate
2. Kendall Jones, Devisha Walia, Nalah Clark

1. Our subject will be a comparison between the 2008 Philadelphia Phillies and 2008 Tampa Bay Rays
2. Joseph Benvenuto, Nick Tarducci, Joseph Rovnan, Ryan Stifnell and Will McAndrews

1. Are NFL pocket quarterbacks more successful than NFL running quarterbacks?
2. Alex Brennan, Zachary Kressler, Robert Snyder, Jonathan Ganon

1. Social media trends over time
2. Brianna Morales, Michael Vidra, Grace Stuart, Mariah Tulaney, Hussain Alshola

1. Our subject is Health/Wellness across different neighborhoods in Philadelphia
2. Kacie Rettew, Cassidy Lorenz, Dalton Veight, Nick Thull

1. Our subject will be the comparison between the different type of crimes people are jailed for in Philadelphia.
2. Jose Gil, Chongxin Zhao, Amanda Barnabie, Dmitriy Summovskiy, Justin Waters.

1. Our subject is the success of different Philadelphia stadiums.
2. Briana Vetter, Jillian Thompson, Glen Diener, Josh Ogg

1. For our subject we will be looking at the Indego bike share trips and comparing the usage of the bikes in the summer months compared to the winter months.
2. Danielle Redman, Summer Holmes, Xiaoyu Liang, Hasan Husain

1. Our subject is comparing the in-game performance of the Cleveland cavaliers vs the golden state warriors.
2. Zeke Menke, Bob McPeake, Nadir Munir, Joseph Pavelick