The goal for this project was to analyze and research a topic based on Data Analytics. Upon further research on different topics, the Internet of Things (IoT) resonated with me as it functions in our day-to-day lives. As society advances technologically, IoT plays a major role in connecting all the dots for a better tomorrow. The system of interrelated, internet-connected objects can analyze, collect, and respond to data over the internet without human intervention. Many companies such as Google have started to roll out services of IoT due to its effectiveness in the workplace. Corporations have been seeing the importance of IoT as it reduces the cost margin for many operations, creating an efficient work structure. The Internet of Things is steadily improving and adopted into our lives and the corporate world.
Search Results for: Analytics
April 2021 – Chair’s Message
While we look to the summer and fall with hope for returning to normal, I am proud of what our students, faculty, and staff have accomplished during a challenging year.
I am pleased to highlight two significant achievements, one from our faculty and one from our students. First, Temple MIS faculty were the most prolific in the world in 2020, according to the Association for Information Systems’ List of High-Quality Journals. This accomplishment reflects the dedication and diverse research interests of our faculty.
Second, the Temple University Student Chapter of the Association for Information Systems (Temple AIS) won Student Chapter of the Year for the 2019-2020 academic year. Read about how Temple AIS continues to excel amid a challenging year, fulfilling its mission to its members and the larger community.
We feature professor Aleksi Aaltonen, who studies how people work with data in real-world business settings. Learn how his work goes beyond analytics to investigate the problems caused by big data and how companies should solve them.
Read about how our new, innovative undergraduate course in user experience (UX) design prepares our majors for the workplace. You’ll hear from two recent graduates who have used the UX skills they learned in their careers.
We also profile three of our alumni. Read about how Thomas Steigerwald (BBA ’10) applies the lessons he learned in the Temple MIS program to succeed in multiple roles at Lamps.com. You will also learn how MS in Information Technology Auditing and Cyber Security alumni James Foggie (MS ’19) and Magaly Perez (MS ’17) used their degree to pivot into new careers.
This year has certainly been unique, but it has also been gratifying to see our students and faculty continue to achieve extraordinary success.
MIS 2502 Extra Credit Assignment
The goals of this assignment were to gain a better understanding of a current topic in data analytics not covered in the MIS 2502 course. Once we selected a topic, we had to provide an overview, relate it to the course, and a real life application example. From this assignment, I learned about the Internet of Things and how it is highly involved in the collection of data involved in data analytics. I also learned how massive and beneficial the IoT network is, and how it will play a large role in the MIS industry in the coming years.
Aaltonen studies where big data meets the real world
Assistant Professor Aleksi Aaltonen is interested in how people work with data in real-world business settings. “Not just data analytics–there are a lot of people studying that. I’m interested in data as a new kind of resource for economic activity.” It’s an interest that goes back to Aaltonen’s Ph.D. thesis.
“You need to think about finding, cleaning, integrating, and interpreting the data before you can actually analyze it. We often ignore or gloss over this work,” he says. But, he stresses, if the business world wants to harness the increasingly massive data at its fingertips, someone must pay attention to these practical matters.
One of Aaltonen’s recent projects, forthcoming in the Journal of Management Information Systems, looks at a company with a new business model. “They wanted to turn a mobile network into an advertising space,” he says. People in the network would get advertisements via text message. But counting how many people receive such an ad can be a surprisingly complex thing, according to Aaltonen. After all, no one is going to buy an advertising space unless you can prove someone will pay attention to it.
“If we send a message to a person does that count as a person seeing it? Or do they need to take some other action for it to count?” he asks.
“Solving these problems is surprisingly laborious,” says Aaltonen. The flashier subjects of data analytics and artificial intelligence get more research attention, according to Aaltonen. “But answering these mundane questions is just as important when it comes to actually make use of data in a business setting.”
Aaltonen is also exploring new ways of organizing information. “I’ve studied Wikipedia a lot, and what is most fascinating is the question of how is the system managed. How did Wikipedia learn to govern the 1 billion contributions into a high-quality encyclopedia with no managers?” He thinks part of the answer lies in transparency. On Wikipedia, for example, “you can see who added, removed or changed every a comma,” notes Aaltonen.
There’s a tendency in big business to exert managerial control over everything, according to Aaltonen. “But the ultimate aim of a firm is not to control things, it’s to make a profit. And if you can make better products that people want to use, then you have to look at that,” he says. Wikipedia is probably the most used reference product in the world. “It’s a new way of creating valuable products and businesses have to stay on top of that.”
Extra Credit Assignment
The goal of this assignment was to describe an increasingly dominant concept of data analytics by writing a two-page analysis paper. From a list of various intriguing topics, I picked the topic of Cloud Computing. Exploring the topic, I learned that Cloud Computing is a virtual delivery of on-demand computing services through the following four different models: (1) On-Premises (e.g. Private Cloud), (2) Infrastructure as a Service (IaaS), (3) Platform as a Service (PaaS), and (4) Software as a Service (SaaS). Currently, the most dominant Cloud Computing providers are Amazon (AWS), Microsoft (Azure), and Google Cloud, which provide cost-effective, simple to manage, and reliable virtual computing services such as Compute Engine, Storage, and Networking services.
The following attachment is my analysis paper: Extra Credit Assignment
Deep Learning
In Professor JaeHwuen Jung’s Data and Analytics class, we focused on data, how it is manipulated, stored, visualized, and used. My research project on Deep Learning focused on what this algorithmic function is and how it is implemented into big data processing. With the rapid enhancements in AI technology, deep learning is taking data and analytics to new heights, focusing on volume, variety, and veracity.
Bonus Assignment
- Include the goals, results, project URL (if applicable), and what you learned in a brief paragraph.
- Once approved, the description is automatically displayed in a post on your e-portfolio.
The goal of this assignment was to dive deeper into data analytics. The assignment asked for a paper explaining a data analytics topic, how this topic related to what we learned in class, and then a real-world example of this topic. Below is my assignment on big data.
Emeline Beck
MIS 2502
11/12/2020
The world creates 2.5 quintillion bytes of data per day. Every like on Instagram, text sent, and Google search goes into this number. In fact, 90% of the data in the world was created within the last two years and the volume doubles every two years. This is big data. The true definition of big data is a large volume of data of different varieties (structured and unstructured) coming in at a quick velocity (in real-time). With all this information coming in, companies can organize it to make well rounded projected business decisions. Some ways businesses use big data is marketing, expansion, and time and cost-efficiency. Big data is first gathered, then stored, retrieved, and then interpreted to make these important company decisions.
In our course, we got firsthand experience with some of the databases and tools to store and retrieve big data. Big data is also related to our lessons about structured vs. unstructured data. Structured data is pre-defined and formatted to a structure, unstructured data is the opposite, not pre-defined and not formatted. Relational databases are an example of structured data, semi-structured data include CSV, JSON, and XML, while unstructured data is images, text, and documents. Through relational databases like MySQL and MongoDB, big data is sorted and organized so that it can be easily accessed with querys and interpreted to make decisions. The good thing about relational databases is that the information is imported once, which reduces redundancy. Normalization allows each table to be unique, a very important quality when 2.5 quintillion bytes of data circulate every day.
Although almost all companies use relational databases to simplify their data a specific company is Uber. In fact, Uber uses MySQL! Uber says that MySQL allows its operators to use the data stored in the tables, without having to understand the underlying technologies. By using MySQL Uber can access all information about customers and their demographics, as well as their rides and payment. They can also access information about the drivers, their demographics, car details, and all the data in between. With this data, they can make decisions about hiring, improving their direction mapping, and advertising their product.
“Big Data: What It Is and Why It Matters.” SAS, www.sas.com/en_us/insights/big-data/what-is-big-data.html.
Itamar Ben Hemo Posted on March 27. “Big Data Statistics: How Much Data Is There in the World?” Rivery, 12 June 2020, rivery.io/big-data-statistics-how-much-data-is-there-in-the-world/.
Shiftehfar, Reza. “Uber’s Big Data Platform: 100+ Petabytes with Minute Latency.” Uber Engineering Blog, 6 Apr. 2020, eng.uber.com/uber-big-data-platform/.
Bonus Assignment
- Include the goals, results, project URL (if applicable), and what you learned in a brief paragraph.
- Once approved, the description is automatically displayed in a post on your e-portfolio.
The goal of this assignment was to dive deeper into data analytics. The assignment asked for a paper explaining a data analytics topic, how this topic related to what we learned in class, and then a real-world example of this topic. Below is my assignment on big data.
Emeline Beck
MIS 2502
11/12/2020
The world creates 2.5 quintillion bytes of data per day. Every like on Instagram, text sent, and Google search goes into this number. In fact, 90% of the data in the world was created within the last two years and the volume doubles every two years. This is big data. The true definition of big data is a large volume of data of different varieties (structured and unstructured) coming in at a quick velocity (in real-time). With all this information coming in, companies can organize it to make well rounded projected business decisions. Some ways businesses use big data is marketing, expansion, and time and cost-efficiency. Big data is first gathered, then stored, retrieved, and then interpreted to make these important company decisions.
In our course, we got firsthand experience with some of the databases and tools to store and retrieve big data. Big data is also related to our lessons about structured vs. unstructured data. Structured data is pre-defined and formatted to a structure, unstructured data is the opposite, not pre-defined and not formatted. Relational databases are an example of structured data, semi-structured data include CSV, JSON, and XML, while unstructured data is images, text, and documents. Through relational databases like MySQL and MongoDB, big data is sorted and organized so that it can be easily accessed with querys and interpreted to make decisions. The good thing about relational databases is that the information is imported once, which reduces redundancy. Normalization allows each table to be unique, a very important quality when 2.5 quintillion bytes of data circulate every day.
Although almost all companies use relational databases to simplify their data a specific company is Uber. In fact, Uber uses MySQL! Uber says that MySQL allows its operators to use the data stored in the tables, without having to understand the underlying technologies. By using MySQL Uber can access all information about customers and their demographics, as well as their rides and payment. They can also access information about the drivers, their demographics, car details, and all the data in between. With this data, they can make decisions about hiring, improving their direction mapping, and advertising their product.
“Big Data: What It Is and Why It Matters.” SAS, www.sas.com/en_us/insights/big-data/what-is-big-data.html.
Itamar Ben Hemo Posted on March 27. “Big Data Statistics: How Much Data Is There in the World?” Rivery, 12 June 2020, rivery.io/big-data-statistics-how-much-data-is-there-in-the-world/.
Shiftehfar, Reza. “Uber’s Big Data Platform: 100+ Petabytes with Minute Latency.” Uber Engineering Blog, 6 Apr. 2020, eng.uber.com/uber-big-data-platform/.
Extra Credit Assignment
- Include the goals, results, project URL (if applicable), and what you learned in a brief paragraph.
The goal of this project was to research a topic of Data Analytics not covered extensively in class and write a write-up on the topic. The results of this project was the write-up that I typed after researching my topic which was big data.
What I learned
I learned about big data through this project. Big data is collected by organizations for many purposes. Some of them are for analysis, predictive modeling, and data mining. The classifications of big data are structured, semi-structured, and unstructured data. Big data is important to organizations because it helps them make business decisions or for example, marketing campaigns based on the data. I learned that big data cannot be easily analyzed or processed efficiently by traditional management tools because of the massive size of the data. Some examples of where big data can come from are from social media databases like Twitter data feeds, clickstreams on websites, emails, etc. An example of a company that uses big data is Netflix.
2.Once approved, the description is automatically displayed in a post on your e-portfolio.
MIS2502 Write-Up
This project focused on the impact of artificial intelligence in the broad field of data analytics in relation to MIS 2502. The goals of this project were to identify how successful artificial intelligence would be in the field of data analytics and potentially give an outlook for how the future may look with AI integration in the tasks of clustering, data association, relational diagrams, decision trees, and structured & semi-structured data. The future of AI looks bright, especially for individuals in the data analytics and business field. As companies begin to develop further into automation, the costs of their goods and services will decrease, resulting in better pricing for consumers. The impact will be extraordinary, with AI being able to consistently and effectively update CRMs instantaneously, while also identifying segments of individuals to better market a product to. Overall, AI will serve as a better compass for businesses to identify trends and market segments faster than any individual could ever.
