- The task was for me to evaluate the class website using Norman concepts. I did my evaluation using concepts such as the three levels of processing, gulf of execution, affordance, signifiers, and conventions. I ended up presenting my evaluations to the class using powerpoint. I learned more about how the design of a website can be broken down into certain concepts and how they all inter-relate with one another. The project has opened my eyes to a new perspective when using websites in the future.
Search Results for: --------
Cloud Computing Write-Up
- Include the goals, results, project URL (if applicable), and what you learned in a brief paragraph.
The goal of this assignment was to research two different topics relating to cloud computing. I explained what they were and how they were important. I also explained how they were relevant to the class and how they were relevant to each other. I learned a lot about what mobile cloud computing was and how switching an app to the cloud could greatly benefit it. Apps could run faster and the storage would be on the cloud and not on the device. I also learned about how cloud computing can become greener and how cloud computing makes companies greener. Cloud computing can cut back on carbon emissions and reduce energy consumption greatly.
- Once approved, the description is automatically displayed in a post on your e-portfolio.
Covid data API
http://misdemo.temple.edu/tuk45129/propoint_covid
Learned how to use .getJSON and jQuery using an API displaying real-time covid data. Then showed statistics such as the country and continent with the most cases, most deaths, most tests using for loops and buttons.
Live Covid-19 Data Results though Web API
Used API data to create summary statistics for Live Covid Data. Created an HTML form with a button for various statistics. Used JavaScript and CSS. When buttons are clicked, data for each statistic is retrieved from the Web API.
Link to the website: http://misdemo.temple.edu/tuj75099/MIS%20Pro%20Point%20Covid%20Project/Covid%20Data.html
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/.
Data Analytics Extra Credit Assignment
The purpose of this assignment was to research a topic relating to data analytics that was not covered thoroughly in class and show that I can understand and describe it. For this assignment, I did a 300-word writeup focusing on NoSQL databases. I learned more about the four different types of NoSQL databases and how they differ from relational databases. Additionally, I was able to research different software used for each of the different types of NoSQL databases and find some real-world examples of when and why they have been used.
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.
Artificial Intelligence in Data Analytics
The aim of this project is to research a topic on data analytics not covered extensively in class and more fully understand and describe a facet of data analytics. I learned about the history and use of artificial intelligence in my research, dating back to the Turing Test in the 1950s. Overall, AI can boost the functionality of data analytics with the capacity to skim through large datasets and pick out subtle trends.
Please find my write-up at the link below.
