Amy Lavin

I found a combination of 2 two facts very interesting. Even though we are teaching ahead of the curve by educating people for jobs that aren’t yet a reality, the possibility still exists that freshman year studies may be obsolete by the time junior year rolls around. I found this reality staggering, that in spite of our best efforts to stay on the forefront of technology, our advances are moving exponentially faster. The curve to stay ahead of is like trying to reach a distant horizon that seems to stay eternally well beyond the reach of our grasp.

I found really interesting the fact that information I really accessible to anyone. This is the first time in history in which it do not matter were you are in the world, you can search something with a click. On the other hand, being in the information age, we are really more richer in knowledge that any generation in the past, technology will have a strong influence in the future generations, therefore learning new skills and always looking to improve is essential, since if we do not we will have a hard time understanding and growing the the future.

I thought the fact that India and China have more honor kids than we (United States) have kids was a very interesting fact. Its crazy to think that we might one day be competing for jobs and various other things with these children from those countries and that they are already a step ahead of us in education. It really brings to light how important it is to keep pushing yourself with education.

I would say the most surprising fact is that a week’s worth of new york times contains more information than a person lived in 18 century would come across. The complexity of the world and the development of the world is much more rapid than before. Also, nowadays, the information in one week, which is contains in the New York Times, even exceeds a person’s life experience. That definitely shows how strong the ability to gather information and data we own today. Both technology and the velocity that world changes are faster than anyone’s imagination.

As the technology gets developed on and on, we live in the space that can be connected to all the people in the world. It means that everyone can get and access data/information they want by just one click. Each information is being counted and gathered through the technology without one’s permission. I think it is great for collecting, organizing, and generating data/information, however, it seems a little scary that one’s information is being transferred so easily to the world.

The most interesting fact to me is that YouTube is the largest search engine in the world. I actually use YouTube as a search engine now and the amount of information on the platform is incredible. I used YouTube to research complex accounting problems last semester, and I discovered that even with a specific question YouTube will have relevant information most of the time. There are many academic content creators that post high level information on YouTube for anyone to find. I knew YouTube could be used as a search engine but I did not know that it is the largest in world.

One interesting fact that stuck out to me was that today’s learner will have 10-14 jobs by the age of 38. To me, that is unbelievable. The rate in which people change jobs is crazy. Another fact that ties into finding a job is that we are preparing students now for jobs that don’t even exist yet. Preparing students for jobs and problems that don’t exist yet will make them prepared for when it does. Technology just keeps developing and we need to keep up with the changes and what it could possibility become later on.

The one fact I thought was the most interesting was that 1 in 5 divorces are blamed on Facebook. Facebook seems to be a double edge sword making it easy to connect to friends and stay in contact, however gives it incentive to cheating allowing for married individuals to conceal affairs through online social media and its direct messaging functions. I wonder whether or not those individuals who have linked up with those they have cheated with would have done so without Facebook. Technology allows for individuals to establish conversations that may not be possible in person because of the fear or rejection or embarrassment, instead online messaging softens conversations and these fears allowing for mutual comfortability and a more likelihood to establish relations that may not occur in person.

I believe the most startling fact in this video is that 100 billion searches are done on Google every month. This perfectly shows how reliant our society is today on technology. People use Google every day for directions, recipes, job searches, general information, and so much more. I never realized just how integral a part of our every day lives that Google plays. No matter where you go you see people on their phones searching google, playing games, going on facebook and not paying attention to the world around them. I try my hardest everyday to stay off of my phone for as much as possible but it is difficult with how accustom I have become to having the world of information in my palms.

There are two points that continue to hold my interest, after allowing some time to think about the video’s overall message. In fact, the two points are one-in-the-same, in that they both deal with the point that 25% of China’s population with the highest IQ, is greater than the total population of North America. With the other point being, India’s statistic of 28% of it’s populations highest IQ individuals outnumbering the population of our country. Not withstanding other factors, such as our own population growth and advancements, as well the standards of these two countries IQ standards; the prospect of a superior intelligent upper-echelon of another society outnumbering our society as a whole is daunting and challenging. It is daunting because of the fact that we as a society, I believe, will be eager to compete for the fear of losing our global-leader position. It is also challenging because of the various socio-economic challenges we are currently facing, as well as the continuing difficulties we seem to be having in the STEM subjects. The video as a whole is honestly not what capture my thinking, it is rather that simple statistic and it’s many implications.

85% of the video was interesting and some facts slightly disturbing, for example, the first mobile phone call took place in 1973, the same year I was born, and my children all thought that was SUPER LONG AGO.
I did find it interesting that the 25% of people in China who have the highest IQ’s are greater than the entire population of North America, which consists of 23 countries. So basically, there isn’t one person to be found in 23 countries that is smarter than the person who ranks the lowest in the 25th percentile of high IQ’s in China. I wonder is it because we tend to focus more on social media and new trends than putting the greater emphasis on education in ourselves and our children.

This was a very interesting video that provided a lot of information. The fact that for the first time in history there are four generations working side by side. The traditionalist, boomer, Gen X and millennial. This made me think of my place of employment and how the Gen X and Millennials often get upset with the operations of the traditionalist and boomer. Often I will hear a millennial state that a traditionalist needs to get up to date with technology, but after watching this video it is safe to say that with the way technology is growing the boomer and millennial will not be within the standard of technology for long.

The fact that we are preparing students for jobs that don’t exist yet with technologies that don’t exist is very interesting but also exciting. As we move on there are new revolutionary ideas that bring up new jobs and yet somehow most people don’t have jobs that they can apply for. I think that by preparing students for future jobs is not only a way of expanding our knowledge as a species but also helps with people to actually find jobs and not be unemployed. If 30 years ago people were aware of such technologies existing today and if they could’ve been prepared by learning about it then there wouldn’t be as much unemployment and it would’ve in turn created more jobs in my opinion.

I thought it was very interesting that despite the total world population being 7.3 billion, there are only +3 billion using the internet. Granted that a portion of the total population is too young to begin using technologies yet, this number still seemed surprisingly low to me… so I thought I’d do some digging ;). According to an article from Digital Trends in September 2015, the “United Nations’ Broadband Commission estimates that 4.2 billion people, or three-fifths of the global population, do not have regular access to the Internet”. The limited access for much of this population is due to country specific regulations and censorship (up to and including complete banning of internet access). With so many countries banning or censoring internet access, I can only imagine the further capabilities and advancements in technologies we will experience as these bans begin to lift!

What I found interesting is that there are no longer secrets. Technology is now our way of living. Everything that we do is recorded and documented in “cyberspace”. Companies have been able to store our personal information which reaches companies or organizations all over the country. Where we live or what we eat is no longer a secret, just log on into any computer system or phone device and your favorite foods, clothes, or car will upload as an advertisement. Also, the fact that we will be using technology that have not yet been invented ponders me, simply because life is so unpredictable. A situation or crisis could occur without a moment’s notice and we, as a country, may not be prepared for it, but life goes on and I look forward to new inventions.

I found the availability of knowledge to not only be vast but incredibly easy to access. What amazed me the most was the ratio’s involving both China and India and how they have a multitude of honor students compared to the United states. Also, I found it interesting that there are four different generations amongst the workforce for the first time. Not really something I would have thought about. All around this video was incredibly insightful and definitely helped put technologies influence into perspective.

I found 2 facts very interesting. One of which being that China and India both have more honor roll kids that we have kids in North America, and a week worth of New York Times contains more information than a person in the 18th century was likely to come across. These facts tell me that even with the abundance of information that we can take in, there really is no competition when it comes to the job market including people from countries such as China and India. In order to even have a chance, we would have to be 3 steps ahead of the curve at all times. This entire video however was very interesting. It really showed how advancement in technology is rapidly changing society everyday.

The one fact i found to grab my attention most was that this is the first time in history were 4 different generations co-existed together, while also having each a different preferred way of communication. It brings to mind that technology has increased so drastically within the past few decades that we’ve gone from messaging someone within 1-2 weeks to 1-2 minutes. It only goes to show how much further we can go in even just our lifetime, and makes us wonder what will come next in the way of communicating with one another and bringing our world ever slightly closer together.

The video is short but taught me a lot information that I don’t know before. It was really surprised me that a week’s worth of New York Times contains more information than a person was likely to come across in a lifetime in 18th century. Although I know that we are starting living in an age of big data, it still shocked me that there are 8 zettabytes of new unique new data created worldwide in 2015. I can’t even image how fast the world is changing as well as the new technologies are inventing every single day.

I found 2 most interesting facts after watching the video.One is how Facebook has over 1.55 billion active users monthly and if Facebook were a country, it will be the world’s largest. I can’t never imagine that many active users just in one social media, even larger than China population. The second interesting fact I found is how Candy Crush is still popular to this day with 7.6 million users per day and 225 million users per month. I thought Candy Crush is out of date but seeing that many users is surprising me.

The one fact that really resonated with me was the way the four different generations preferred communication methods (Traditionalist, Baby Boomer, Gen X, Millennial). It is evident in my relationships with co-workers and my parents. I work alongside my father (baby boomer) who prefers using the phone as a means of communication while protesting text messages. My mother would be considered a “silver surfer” who has abandoned certain baby boomer characteristics in favor of texting and has adapted to technology. The advancement in technology has showed how some older generations are able to easily adapt and some struggle to adapt. Given the rapid development of technology, it will be imperative for all generations to adapt our developing technology.

There are a few facts that are interesting to me, First, how far behind American children are from other countries. Although the other countries population is way more than America, the number of honor students is disturbingly small. Another interesting thing is that Facebook would be the largest country if it were a country, even though it’s only 12 years old. That is funny to me, yet I am not surprised. It is amazing that we are preparing students now for jobs and advancement in technologies that are currently not invented yet. Americans just need step up the game in education.

There were a few facts that I found interesting about the video. First was that 1 in 6 relationships today started on facebook and that a majority of relationships end in divorce also because of facebook. I thought this was interesting because there use to be a time when people enjoyed meeting others in public and getting to know a person by spending physical time with them. Now it seems that we are so used to technology that we can actually meet and fall in love with someone by just communicating online with them before actually meeting in person. Another fact I found interesting was the fact that technology is so rapidly improving that schools are teaching students skills needed to problem solve problems that are not even problems yet and preparing them for jobs that are not even created yet. This was interesting because it shows that technology is something that we have become so dependent on and that is changing everyday.

The most interesting fact that I saw in this video was about how large the populations of India and China are in comparison to North America. Along with the population size, the video also pointed out how advanced those two nations are from an educational standpoint by saying India and China have more “honors” students than we do total students. I think that it is important for the United States to advance in education along with nations like India and China.

I think it is very interesting that this is the first point in time that four generations: traditionalist, baby boomer, gen-x, and millennial, are working together side by side. I feel this would make firms and companies better decision makers as they have the view points of different-minded individuals, and each generation has strengths and weaknesses. While traditionalists may not seem well versed in modern technology, their life experience and knowledge of the world are very valuable assets.

I found many of the facts in this video very interesting, but one that really caught my eye was how advanced in education China and India are than the U.S. They have more honors students than the U.S. does with students in general. It’s amazing how these students are being prepared for jobs that don’t even exist yet. It is crucial for the U.S. to make some advances in eduction as compared to India and China. Also, It is crazy how much can change year after year and this video really shows how advanced modern day human beings are compared to past generations.

What I found most interesting about the video was the fact that, new technical information doubles every year. I know older engineers who say that their degrees from a decade ago are basically useless because they didn’t keep up with the changes in technology. The video mentioned that, half of what college students who are majoring in technical field learn during their first year will outdated by their third year. Technology is always changing so people in the technical field almost always have to continue their learning after college. People in the technical field can never really follow a fixed set of learnings and if they choose not to evolve with technology their degree will end up being useless in a matter of years.

What I found to be the most interesting fact within the video was the fact that today’s learners are being groomed to operate future technologies that have yet to be developed. I have two children who are almost at the age to begin school and it is very interesting to know that they will learn to use futuristic technologies and answer questions that are inconceivable at the present moment. However exciting this is to hear, this also begs the question of whether or not, as their father, that I will be able to keep up with them and aid them in their studies.

The theory that today’s learner will have held 10-14 jobs by the age 38 is interesting. I am 28 and have held a full-time job at four different companies. I enjoy my job but my goal is to further my career so there is the possibility that I will achieve at least 10 different jobs by the time I am 38. I feel that number is high which could show that businesses are unable to retain long term employees, or that people are changing with the technology by being replaced by more automated systems or people are furthering their careers through education and experience.

I actually found a lot of things interesting about this video that was filled with so many facts. It’s amazing at which rate we are growing in population and how technology is growing with us. Technology makes things spread so much quicker. The way Facebook is so popular and has so many users when Facebook didn’t come out that long ago but I feel like everyone has an account. Even my grandparents have learned how to use the computer and signed themselves up for a Facebook account. It is amazing at the rate we are progressing and also in the video it said we are teaching kids for jobs that haven’t been created yet and teaching them to resolve problems that haven’t occurred yet.

I found the fact that one weeks worth of New York Times contains more information than a person in the 18th century would come across in their lifetime. This just shows how dependent we are on instant news and connectivity to the world. Technology and information moves forward at such an astonishing rate that if people are not connected almost all the time they will be left behind.

Every fact presented in this video was interesting. However, I found the ‘1 in 5 divorces are blamed on Facebook’ fact to be very strange and scary. As time goes on, social media use will only increase, I’m sure. I find it sad and alarming that it causes so many rifts in relationships to the point that it’s the blame for many divorces. Its a factor that did not exist years ago, but it’s become part of many peoples lifestyles.

Honestly, i found a number of facts to be very interesting when it came to data, however the idea that candy crush saga makes $830,000 per day and $230,000,000 pretty amazing. This video does a good job of jamming a large number of statistics into one brief video to give the viewers a quick realization of just how much things have changed in the last decade. Since technology is moving at such a rapid rate and we are now taking in and processing so much more information on a daily basis in comparison to old times, it isn’t that surprising to hear that some people are choosing to technically get a degree in a specific field whose jobs aren’t even available yet.

I found this video to be pretty interesting. I was surprised that on average people will go through 10-14 jobs by the age of 38, I pictured that number much lower. I also find it cool and surprising on how much technology is transforming and that there will be so many job openings for it, some that aren’t even around yet. So many parts of this video surprised me, like how many self driving cars we will have on the roads within 4 years. It is not surprising how much google is used though. It’s crazy to think that we are growing up in an era where technology is being revolutionized each and every day.

The video gives insights into the age we’re living in – the age of rapid technological growth. Technology influences us tremendously, in terms of communication, education, administration, etc. One piece of information that stands out to me when watching the clip was that there will be more new jobs that we’ve never thought of, and this completely changes the purpose of today’s education. Learners can no longer rely on educational system to prepare for the future; they have to prepare themselves and orient themselves to the right direction.

I found the YouTube video “Did You Know” to be very interesting and informative. I found the fact that the 25% of the population of China with the highest IQ’s is greater than the total population of North America. The statistic of the number of babies being born in the U.S, China and India was an interesting perspective and visual of the growing population. The evolution and changes in technology and society are very apparent and was demonstrated by the statistic of the top jobs in demand barley existed 10 years ago. I also found it interesting that they showed how things might be like in the future such as 10 million self-driving cars will be on the road by 2020. Technology is a tool that most people use everyday and the video demonstrated different ways technology affects us everyday and will affect us in the future.

I thought this video was eye-opening in the myriad of different interesting facts it displayed. Most interesting for me, as a student who would like to pursue international marketing, was the rapid rate at which the population of India and China are growing. While still developing nations, they are sure to be two highly consequential economies in the next decades to come. I have an interest in e-commerce so large entities like Alibaba and other online platforms intrigue me. I can only imagine the vast stores of data that Alibaba holds and how valuable their big data really is! MIS must be crucial to these companies as millions of shoppers have access to their online stores daily.

What I found to be really intriguing is the preparation for the upcoming generations. Our society is literally training young minds to take over at a faster pace, broadening their minds to all types of possibilities, so that when the technology becomes available they have taste for it. A hunger for advancement and creation through a data driven society. Another important detail about this video is how the internet revolutionized communication, entertainment, and the social lifestyle for the whole world. Information is so easily available this day in age, and how it far surpasses the way information used to travel just 20 years ago.

The most important take away is the mindset used data analytics. I learned that I needed a logical understanding of how a system works, so that I could wrap my head around all the concepts. This covers learning the programs needed in class, relating content it to your life and adopting new ideas in general. I realized the mindset’s importance recently because of the internships I’ve been communicating with. Every internship focuses on a logical and analytical mindset to achieve their goals and learn new jobs.

One of the significant concepts that I have taken away from this Data Analytics course is understanding computer language and the benefits of tools such as SQL and R Studio. As a Strategic Communications major it was really interesting learning different commands for SQL and leveraging that to extract information from different database. Initially, I thought some of the concepts were tedious specifically for the assignments, however I have noticed an improvement in my problem solving skills after having to reconfigure and readjust my approaches to the assignments. In a job interview, I would explain what I’ve learned by discussing the programs and the benefits that they have in helping businesses make decisions using the data they already have.

The most important takeaway that I learned from this class was how to utilize software like MySQL and R Studio and along with the architecture of an Organization with how data travels. MySQL and R Studio are both software that I’m sure I will see in the future so it was definitely important to get some background knowledge about them and how to use them. Also, learning about how data is transferred from the beginning stages of data entry to data analysis was helpful because I’m interested in either the data analyst or system analyst field. I would tell a future employer that I learned how to create data models, transactional databases, and analytical databases along with utilizing software such as MySQL and R Studio to create and browse databases.

the most important takeaway that I took from this class are the experience of learning and using SQL and RStudio. The way I would explain to my employer of why having this knowledge is important is by explaining that I can take cluttered information to make it into information that can be more beneficial for the company. As a Marketing Major, in a sense I am able to use the information that is given and directly market towards customers within the demographic area, or even by the products they have purchased. Retaining this knowledge will definitely help me in the long run.

The most important takeaway from this course is my new understanding of the power of data. Not only was I able to gain familiarity with several tools for data analytics, I was also able to gain an appreciation and an interest for how data analysis can benefit any company or organization. I would explain this to an employer by giving examples of certain assignments that I’ve had, and give details about skills I’ve learned in SQL and R. In addition, I would just explain my general understanding about the role data analysis should play in the company I’m interviewing with.

The most important takeaway that I took from this class is the importance that data analytics plays in all parts of our lives. From supermarkets to retail shopping, from large corporations to small businesses, from in store retailers to online purchases, data analysis is used to make everyday business decisions that could potentially increase revenues. Taking a look at the statistical importance of different business decisions using R studios has shown me first hand why our particular skill set as MIS majors is so in demand.

Before I attended this first class, or even before i chose the MIS major, I never really knew what data was about. So for me, the most essential takeaway from this Data Analytics course was learning the importance of big data. This course guided me on the path to think more critically and analytically when approaching a problem. To my future employer at a job interview, I would explain that i’ve learned how to seek relevant information to solve business problems by manipulating data using software such as MySQL, R Studio, and Excel.

The two biggest takeaways that I have from this course are 1) a preliminary understanding of the data analysis workflow/cycle and 2) my understanding of the “data-speak” behind basic analytical tools such as R and SQL. While not an MIS major/minor, I am glad I took this class because so much is rooted in data now. I hope to work in government and policy and with the civic tech. movement, I think that being able to talk in terms of data analysis will be helpful in interviews. It will separate me as someone not vertically versed in policy-making but also data-driven policy-making.

13. This class really showed me how data works and how I can use it for my benefit. Understanding the different types of data, and how it is transformed into historical data through the ETL process was very beneficial. It is also important to differentiate among data to find what is most relevant. Something that I enjoyed using was the SQL database, in which data relevancy was important, to create a good database with efficient results. Next, using R studios was a great tool to use when browsing through large databases. R studios can save us a lot of time, so that alone can solve many issues if we were pressured on time. Finally, data visualization, which I believe is one of the most important elements because it is all about presenting our data. If it isn’t done clearly or in the right way, our work might just mean nothing to others. I would use SQL, R-studios, and data visualization to explain to my future employer.

The most important things that I would take away from this class would be my knowledge from using different analytical tools such as SQL, R and RStudio. I think that these particular things were most interesting and opened my mind to new and exciting technologies. In a job interview I would explain to my employer that I am proficient in using SQL, both pulling data out of a database and putting data into the database. I would also explain how I was familiar with RStudio as well as analyzing the data from the decision trees and clustering graphs and charts. Learning more about Excel will also better prepare me for my future job as an MIS major no matter what job I will have in the future. Everything that I’ve learned in Data Analytics this semester was new and interesting and I can’t wait to use this knowledge and apply it to future job positions.

Everything in this course was important because everything links together. I believe that learning the feel of some of the software we used was a good way to understand how these software’s work. Such as: MYSQL, R Studio and Excel are many ways we can manage data which is very important.
I learned in my data analytic class that we have different types of data, different types of software that help us find data we need. How we can make better decisions using data, how we can put data into graphs and have any random person look at it and understand what is on the graph.That is how we are able to connect both worlds of IT and business together!

The most important aspect of the course was learning how to adjust to information technology as a language, and being able to apply the language to a business situation. For example, using MySQL and Rstudio took a degree of adjusting to technology language, but once understood, I was able to tell a story with the data. If an employer asked what I have learned from this course, I would simply say I can understand, interpret, and communicate information technology language much more fluently now.

The most important takeaway from this course for me was through the use of Excel and SQL. These tools will come in handy when your boss gives you a spreadsheet filled with a million rows of data. I would explain to my potential employer that our Excel and SQL assignments simulated questions that we may come across while working in the field such as which customers spent the highest amount of money in a given month or year? Through these tools, we can analyze and make sense of collected data we are given.

The most important takeaway for me is the learning how to code in SQL. As I have found out, SQL is used everywhere and by putting that on my resume, I can stand out from the crowd. I would explain to a future employer that I am proficient in writing SQL code and can do basic functions such as selecting specific data from a database as well and modify database tables.

I feel that the most important take away from this class was actually learning to work with data! In MIS 2101, when the Data Analytics Challenge became a requirement, I felt entirely overwhelmed by it because I did not know there were accessible tools that could help me interpret the data. Now that I’ve been introduced to tools like MySQL and Rstudio, I feel that working with data has not only become much easier, but it has become interesting as well.
In a job interview, I would explain the work I’ve done with data analytics in those particular programs. The experience would definitely look good and they would know that I’m someone who would be able to handle a company’s data!

Among all the MIS classes that I have taken, this is by far the most interesting and personally most favorite class of all. I like how I was taught the various aspect of data presentation and visualization and what goes on before and after it is processed into meaningful information. Software is usually tough to grasp (as observed in the MIS3501 classes) however I believe that the flow and pace of this class helped in understanding the fundamentals of data and eventually working on high end software (such as MYSQL and R Studio) and see the possibilities of creating meaningful information.

After taking this course, my ability to understand and interpret the way data and information (as well as the difference between the two) is created and made, has increased. After gaining experience with SQL, it is a lot easier to grasp the concepts of creating tables, retrieving and editing data – I also learned the importance of doing so in order to make more efficient decisions. Data and information are key elements in today’s world and society let alone a staple of the business world (every department can benefit from the better decision-making that efficient displays of data can provide us with).

The most important takeaway for me in this course would be having gained the overall knowledge of how data analytics works. I’ve learned the various different ways of how to extract meaningful data from databases and use that to find out specific information about a problem or situation. I would explain to a future employer that I now have the skills to use different systems, such as MySQL and R Studio, to extract meaningful data that would ultimately help out the company. I provide specific examples of the in-class exercises and assignments that we have done to further explain what exactly I was able to do to analyze and extract different information.

The most important takeaway for me from this course was learning how to use and interpret MySQL and RStudio. Another important skill that I learned was how to analyze data through the use of pivot tables created in Excel. I learned a little bit about pivot tables in the Introduction to Microsoft Excel course, but I feel that I was able to understand it more from examples that we completed in class. I would explain to a future employer that I am proficient in both MySQL and RStudio, and able to analyze large data and translate it into something that the average person would understand.

I learned a whole lot in this course. The greatest benefit in my eyes was learning the basics of “coding” and how to use multiple different database systems. Being able to discuss both SQL and R should greatly benefit me in a future interview. I have not worked with PHP, HTML, Java or other programming languages yet, but I am relatively certain that this class has properly prepared me for when I do need to learn them.

The most important thing that I got out of this class, was that working with data is fun. Whether it is working with SQL, creating visualizations, or using Pivot tables, you can uncover so many things from data. Tools such as R and SQL will definitely tools I will work a lot with in the future. Data analytics will be important for companies to gain an advantage in the future.

One off the biggest takeaways in this semester is learning the power of analyzing data. I appreciate the exercises we used in Excel because Excel is used throughout the business world. The company I will be interning at this summer uses SQL therefore learning the basics of SQL in this class gives me a solid foundation of the language and will prepare me for the type of work I will be doing in this summer.

The takeaways from this course I find most important are Excel and SQL. During the internship interviews i had this semester every firm asked me about my Excel proficiency. Learning the framework of SQL in class then furthering my learning independently did help me in my interviews. Having a solid base of Excel and SQL allowed me to accept my internship at TD Bank this summer doing IT Audit.

The biggest takeaway from this course for me was learning just how many ways data analytics can improve decision making on a daily bases. This class, along with learning about data analytics in 2101, were what ultimately inspired me to add a double major in MIS. The most crucial technical skills that I’ve learned and will be able to take advantage of in my future career are how to utilize MySQL Workbench in order to create, modify and query databases, as well as how to utilize R Studio to determine relationships and patterns in the data. I have also learned how to utilize Excel even more efficiently, by being able to create pivot tables and augment data variables to see the exact correlations that I am interested in seeing. In addition to learning how to read and get information, this course has also taught me how to better display and present information to a co-worker, superior, or potential client through using proper data visualization techniques. This knowledge is also completely relevant for Marketing purposes, and therefore I will be able to use my combined knowledge in both fields to be able to optimize my effectiveness when working in a future potential internship and career.

The most important take away from the course for me was the use of SQL and Excel. Extracting information, manipulating data, and updating databases with functions that other users often have no familiarity using. I would tell an employer that I have gained a coveted set of skills working with big data through course assignments. These set of skills have better prepared me for working in an analytical role with big data and making decisions based on the information found.

When looking back at the class I think I value a number of things that I learned. However, more than anything else, I found learning how to manipulate and read data in multiple different ways takes the highest level of importance. Now that I know how to input and output data in more than one way, I have no reason not to believe that this class could possibly be the reason why I land a future internship or job position.

The most important takeaway from this class is learning how to utilize data and making it into something that we can use to predict things. Being able to manage tons and tons of data and turning data into information. I would tell them that I learned how to handle and manipulate data and turn it into something useful that can be used for the benefit of the company.

The most important takeaway from this course is understanding well the relation of data and information. The tools we practiced to use like MySQL, pivot table, R language and basic ERD graph, they are all designed for easiest and fastest data processing. But all of tools are based on understanding of materials, excerpt information to simpler commands on tools. You need to read instructions, practices more and write basic commands to get perfect answers. If I am in a job interview in the future, I would tell my employers about how can I quick learn, understand and use these data processing applications in different working environment.

This course has given me great insight on how data analytics is used in business and other sectors. A main takeaway from this course are the skills needed to utilize MySQL and R Studio. These programs are very helpful in managing and analyzing data for a wide range of uses. I feel that I have more expertise that I can add to my knowledge bank for my career.

The biggest takeaway from this class for me was learning various ways of analyzing data for different purposes. This allows to me to see the data in a different perspective and gives me an idea how big data is analyzed in a systematic way. Also, the knowledge that I learned from this class will help my professional career because it enhanced my computer skills. And I believe that knowing how to use RStuido and MySQL can help my career in the insurance industry because insurance industry is heavily relay on the use of the big data.

I most enjoyed learning how to use the “hot” technology that all companies use to sort, analyze, and visualize their data, specifically: SQL and R. Both of these new skills I’ve developed will help me succeed in my internship role this summer, and in upcoming employment opportunities. I would explain to an employer in an interview that this class gave me the tools needed to better understand how data works, and the inspiration it gave me to learn more about all aspects of “big data.”

Everything that I learned in this class was valuable from SQL to analyzing data in R. What we learned in SQL really helped me with my other MIS courses that also used SQL. My favorite part of the class was using Rstudio to analyze statistical data. I especially liked the clustering assignment because it produced various visuals to analyze the data. I also enjoyed learning data visualization principles. We see manipulation of data in graphics all the time for various companies such as Verizon who markets their company by using a map to show Verizon users. I would tell a future employer that I have experience analyzing data in Rstudio and manipulating databases in SQL.

Learning SQL and R was very important in this class as it will be very beneficial in the future to not only have experience with these specific systems, but also to have experience learning new systems in general. Use of these systems helped with data visualization which brought the course together from what we learned in the beginning until now. Being able to analyze big data with these systems will be helpful in the future working in the IT field.

For me, the most important takeaway from Data Analytics would be learning SQL, pivot tables in Excel and R/RStudio. The tech industry is getting bigger and bigger and there is an explosion of the amount of data that is stored in servers all over the world. Companies need the people to fill in those high demand jobs and knowledge in database management or data software is a huge plus in this field. Knowing how to sift through piles of data is huge for anyone looking to land a tech job either in the US or looking to work all over the world. Many of these database management jobs can be done remotely which gives you the option to travel around the world while you work on your laptop. No matter what, data is huge everywhere.

I would explain that because of my knowledge of SQL, pivot tables in Excel and R/RStudio, I am able to organize massive amounts of data for a company which can help its business and financial decisions. In SQL I’ve learned how data can be read, written to and manipulated. Tables can be generated, dropped, changed and altered easily through commands. I’ve learned about the table structures and how the databases are contained on the servers which can be accessed remotely from anywhere in the world. MySQL (along with other DBMS’s) are crucial to data storage because of the exponentially increasing amount of data. With pivot tables in Excel, I am able to extract, transform and load different formatted data into easier to read tables to generate critical information faster and easier. Data can be extracted in Excel similar to SQL for easier interpretation for better business decisions in the future. Excel can be used in conjunction with SQL for further data analysis. R and RStudio is a great tool for data modeling which can be used to get into the nitty-gritty details of your data. With R and RStudio, data can be observed with varying levels of granularity which is important if you want to find the intricate details of the data.

Personally, I believe the most important takeaway from this course is understanding how data can be transformed and analyzed to help solve everyday business problems in short and long term scenarios. Learning to use different systems like SQL, Excel, and R/R studios opened my eyes and expanded my knowledge on how easily data can be recorded and retrieved for business purposes. Gaining the experience with these different softwares prepared me for real life business situations where I can use data to my advantage.

2) I would advise to choose predictors variables that have the most impact. These include: income, age, has children or not, mortgage and others with the same caliber.

A business question regarding your own career that you could answer using a decision tree could be what university you’re going to attend. The data needed to be collected would include if you want to attend college in the first place, where the university is, how much money you’re willing to spend, where the college is, and what major you’re interested in. This would be a somewhat lengthy decision tree needing a lot of information, but it could be done.

1. As a general example, I can imagine a company using a decision tree to answer the question of, “Should we buy or build our technology?” They’d need to collect data such as: unique or common situation, ability to build vs. not able to, cost to maintain vs. cost to buy, etc. This is one small way to demonstrate the many uses of a decision tree.

A business question that could be answered by using a decision tree is “Is the job candidate qualified for the available position?” The data need that would need to be collected in this type of decision tree would be whether the candidate attended college. If yes then what degree. Some other data that would need to be collected is whether the candidate has prior experience. If yes then how many years of experience, etc. It would really depend on what type of position it was to determine what data needed to be collected. If it were a tech consultant job, data that could be collected is if the candidate had customer service experience.

A business question such as whether or not a company should invest in a new technology can be answered with the help of a decision tree. The data that would need to be collected would be the cost of the technology, benefits, the amount of time it would take to implement, and how much capital does the company have. With the analysis of the collected data, a company should have a general idea of whether or not they should invest in a new technology.

Colleges could use decision trees to take a better look at applicants for upcoming school years. The data could include GPA, SAT and ACT scores, gender, ethnicity, family income etc. This could be used to determine who of the applicants to accept and who to reject.

What advice would you give someone regarding how to select the right predictor variables for a decision tree analysis?

I would advise them to break down the problem description clearly, so that they can find their predictor variables easily.

A retail company could use decision trees for determining product roll-out strategies. Data which would be included in the tree is previous sales data for similar product categories, geographical and demographic data for the potential new regions in which a product would be rolled out in, and previously existing customer data that the company has, in order to forecast sales predictions in a specific region.

1) Name and describe a business question that you could answer using a decision tree. What data would you collect to perform the analysis? Don’t use an example we’ve covered in class.

A business question that could be answered using a decision tree could be used to determine whether or not someone should be accepted to get auto insurance in a certain group. It can be used to determine the age, location, income, and other attributes that can allow the person to be placed into a certain insurance class. If they do not get accepted into a certain class, they will then have to go to the government insurance pool that can be very expensive.

A business question that could be answered using a decision tree is whether a company should merge with another company. The aspects that we could analyze using a decision tree would be revenue per quarter, number of employees, number of warehouses, number of products produced, and the cost per product output. Other aspects that could be analyzed that are not financial or number based are the culture of the company and popularity of the brand.

One decision that could be made using decision trees is whether or not a restaurant chain should open a in a new location. The manager will be able to analyze the data to determine if the company has the capital available in order to jump start this new restaurant location, and whether or not that particular location would be conducive to generating profit. Data gathered for the decision tree should include company history, customer history, information about the new location (such as traffic patterns, area demographics, crime rates, etc.), and information about the current financial state of the company.

1) A possible real-world problem that could leverage the power of decision trees would be predicting the outcomes of high-risk youth in inner city schools. I know this isn’t necessarily business-related but I think that much of what we learn in this class can be applied to areas outside of business, which is why I like this class. For this problem, you could utilize data on students such as test scores, suspension records, attendance, retention, and other metrics in order to develop a decision tree to predict their likelihood to graduate, their likelihood to get involved with the juvenile justice system, and other possible outcomes for inner city youth. Maybe we already do this, but if we don’t, I think this data would be incredible useful in helping identify students who ned additional supports ahead of time.

Business questions: what will be my expected return on investment in the derivatives market in a specific position and economic condition?
Variables need: volatility, time, interest rate, dividend yield (y/n), market price, strike price, probability of price up-move, probability of price down-move.
This situation can be examined in multi-period or single-period binomial trees that predict that value of a derivative at a specific time in the future give the above variables. With this information, a trader can then price the derivative accordingly and determine the probability his/her position/portfolio being profitable.

A business question that could be answered using a decision tree would be the quantity of products that a store sells. For a store like Dick’s Sporting Goods, who sell a variety of products, they could use a decision tree to break down previous year’s sales and determine which products are most popular based of gender, color, and time of year. For example a pair of Curry or Lebron basketball shoes would probably sell more than a certain toddler shoe since there’s more of a market for Curry’s or Lebron’s so Dick’s would be smart to have more of them on hand than toddler shoes.

The best advice I could think of is to first, clearly understand and think it through what you want to analyze. Then write down all of the variables that might relate to what you are trying to analyze. After that you start to choose the most important and most relevant variables and get rid of all others. Variables that don’t have a significant impact on your analysis are probably unnecessary meaning that they shouldn’t be used.

After doing research, I realized that lots of financial institutions and companies in various industries use R to carry out functions and bring about various data related to their work and research. Examples include finding standard deviations, averages,maximum & minimum return and even various qualitative information as well. This kind of work will also include decision trees which help in various decision making processes. One example would be, what is the size of investment the company is capable of doing (big or small size)? And according to that, what kind of investments should we look into?

A business question that you could answer using a decision tree would be what type of car someone might buy. Car dealers would be able to analyze a person’s age, gender, marital status, and income level to make this prediction through the use of a decision tree. For example, a married man, who has three children, would probably more interested in a safe, child-friendly SUV than a sporty, smaller car.

An example of a business question that could be answered using R and decision trees could include whether or not to run a particular ad campaign or not. The data necessary to collect to answer this question could include variables such as the need for an ad campaign or not, cost of the campaign vs. the company’s advertising budget, the time it would take to create the ad vs. when the company needs it to air, and the projected sales impact of running the ad. You could also use a decision tree to filter through which consumers would fit the company’s target market model in order to determine where to focus primary advertising efforts.

1) An auto insurance company could use decision trees to predict how likely it is that someone will get into an accident based off of age, gender, whether they live in a rural or urban environment and much more. This information could be useful to help them determine rates based off of this risk.

A great business question that could be answered using decision tree analysis would be insurance companies deciding on who to insure or not and what prices to charge which individuals. Decision trees provide accurate percentages and outcomes which can be a great tool for calculating risk. Also, risk managers could use these percentages to correlate the prices that they should charge their customers based on the amount of risk that is involved in insuring the individuals.

A great business question would be, how many of our customers in our loyalty program received food assistance from the government? What are the three main products customers purchase the most and what promotional deals can we offer to help support them? The best data that should be collected to perform the analysis is: age, gender, residence, family size, income, and frequently purchased items. To help an employee determine the most important variables, I would encourage them to think about other variables that would influence a customer receiving government assistance: income, family size and gender are all important variables in determining this.

Regarding what variables to choose for a decisions tree analysis. Is really to know if those variables would affect the decision tree in any way. Some variables might have no effect on the tree so those variables are useless to a decision tree. The variables that have effect on the decision tree must be added for a more accurate decision making. We always seek having a better analysis an more accurate analysis.

1) A business question that could be used using decision trees is which sales people a company should keep, fire, and promote. Data that should be collected should be sales rate, average sales, average item per order, and other measures of productivity. They can also use office ranking and sales activity throughout the year into account.

A business question that we can answer using a decision tree would be if we would want to continue a product line. We can base it off of sales, is it profitable, average order, how many was bought this year, who bought it.

A business question for colleges/universities that could be answered using a decision tree could be “Which prospective students should receive a scholarship?”. The data that would be collected to perform the analysis would include (but not limited to): ethnicity, gender, family income, age, declared/undeclared major, High-School GPA, and SAT score. Analyzing this data would regulate whether the candidate gets accepted or not.

My business question that can be answered using a decision tree would be whether or not a designer should release a new piece to their collection such as sunglasses, wallets, leather goods etc. They would want to exam the age of potential customers, income of those customers, gender, and loyalty to the designer (if they are a repeat customer or not).

What advice would you give someone regarding how to select the right predictor variables for a decision tree analysis?

When it comes to the predictor variables, you want variables that will accurately help provide outcomes. With that being said, when the decision tree is made it is crucial that the predictor variables play a part in the decision making process to determine the probabilities. A predictor variable should only be chosen if it can aid in determining a probability.

An example of a business question that could be answered using R and decision trees could include whether or not for a new computer would be popular. The data might need to perform the analysis would be: size, quality, shape, price, weight, function, memory storage capacity, speed, etc. There are so many good predictors that we can use to determine the outcome, popular or not popular.

My advice to those determining which predictor values to use for a decision tree would be to choose the variables that greatly divide the data first. You would then incrementally choose lesser differentiators until you reach the leaf node values. The order of the predictor values would be different depending on what you are trying to decide.

Name and describe a business question that you could answer using a decision tree. What data would you collect to perform the analysis?
My examples is whether or not the company uses the new applications or system for internal management. So it will test the compatibility on the devices (like portable laptops, smartphones, computers and multimedia), price (for installment and permission), privacy and security (safe=additional firewall, special keychain or authorization), complexion (easy or hard to use), range (limitation).

1.) A business decision that could be made using a decision tree is whether to stay in your current role at your place of employment or explore other career opportunities. Data that can be collected for to make this decision is income, daily/weekly hours, culture, benefits, and location.

In order to select predictor values in a decision tree it is easiest for me to work backwards. Think about the end goal. What is it that you want to find? From there, you can then backtrack in the data. How will your desired outcome get extracted from the larger data set?

An example question I thought of could be do people like to ski or snowboard more and what makes that so? We have learned that some factors that we thought would never play a part in statistical patterns actually do, so there could be some tellers we would never expect for this question. Some could include Income, a comparison of two hobbies picking one or the other (would you rather play basketball or hockey?), what temperature do you keep your house set to? (snowboarders may enjoy colder temperatures than skiers. These could all be right or wrong, but the point is that some indicators could tell a story that we never thought could work.

1. Name and describe a business question that you could answer using a decision tree. What data would you collect to perform the analysis? A business can use decisions tree to see if a person is insurable for health insurance. By looking at different factors you can see if a person is too much of risk. This will help companies choose good risks and not catastrophic risk.

1) A business decision that could be made using a decision tree could be selecting and adjusting types of food to be placed on a restaurant menu. Data that can be collected and utilized for this decision would be highest selling dishes, costs, popularity, taste and ingredients. These factors will help determine which foods will sell better depending on the time of year.

1) A business could use decision trees for many things, for example marketing a new drug to a certain geographic location. Whether their return on adverting would be worthwhile to deploy marketing in that area. Data used for this analysis would be, age, gender, income, average usage of drug or similar drugs, etc.

Most Hollywood movies are shown in almost every theater around the US. Smaller indie films are only shown in select theaters around the country so a decision tree can be used to decide whether or not a customer will see a certain movie depending on their location, age, sex, neighborhood cluster or other demographics.