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MIS2502-Extra-Credit-Tarisha

The goal of this project was to write a short essay about a topic that has not been discussed in class in order to expand our understanding of data analytics. I chose to write about Social Network Analysis (SNA), which is when the social relationships between individuals/groups are plotted in a massive network diagram. Here’s an example of what an SNA diagram might look like:

In my essay, I wrote about how this can relate to what has been taught in class because data can be extracted from this diagram and be processed in SQL, or data that’s designed in SQL can be used to create an SNA diagram, and then I wrote about an example of how researchers were using SNA and SQL to predict criminal behaviors in societies. I learned about how the SQL knowledge I learned in class can be applied for processing massive amounts of data in the real world, and a practical way of diagramming Big Data involving people and relationships between people.

1. Include the goals, results, project URL (if applicable), and what you learned in a brief paragraph.
   Deep Learning is an innovative and revolutionary type of machine-learning, that a machine can become more intellectual through the process of self-learning.
   All the AI systems require the raw data that we have collected, and AI finds a better or the best solution based on the data that is historically accumulated.
   Especially, data and analytics are essential part of machine-learning system.

   MIS-2502-Data-Analysis-Optional-Extra-Credit-Hojoon-Jacob-Lee

Description:

In MIS 2502: Data and Analytics, we have learned a variety of topics relevant to the discovery, research, tools of communication, and systems of interpretation regarding data. In this course, there are a few specific topics that are touched on but not dug into deep enough compared to the focal material of the course. One of these is the topic and relevance of Artificial Intelligence in the world of data. Artificial Intelligence, also well known as AI, is the developed intelligence composed of variations within computer science demonstrated by machines that are designed to perform tasks that are typically done by a human being. AI is relevant to analytical science and data through its assistance in conducting a more in-depth analysis of data in specialized areas of study that is not naked to the human eye.

Generally speaking, AI allows organizations to have a more advanced and effective base when making important decisions, developing core business strategies, and increasing the agility of computational operations for these organizations at lower costs. An example of how artificial intelligence aids data-related situations is with big data, data that is too large or complex and needs to be condensed in some form (Surya). Usually in these cases, since such data can grow exponentially over time, traditional data-processing application software is unable to minimize the data due to its high levels of complexity, thus, AI resolves the issue. Some analytical operations AI runs include identifying connections through different databases, locating errors and coding malfunctions, and recognizing advanced computational knowledge to further assist data systems in executing their sensitive information properly (Dixon). As AI is designed to replicate an advanced version of the human mind, it has the ability to work faster and for longer compared to humans, demonstrating the effectiveness of its existence in the world of analytical data. 

Without the presence of Artificial intelligence when creating and using data analysis systems, it would be far more difficult to develop accurate databases at the speed it currently takes utilizing AI. With the inclusion of such advanced intelligence, organizations are set to succeed and are less likely to generate faulty systems and interpretational tools. In the future, it would perhaps be beneficial for students to understand the purpose and importance of the relationship between AI and the processes within data analysis by further expanding on the concept in the course.

Big Data

The goal of this project was to research a current topic in Data Analytics that we haven’t covered in class and learn about it, write a brief overview of the topic and connect it to 2502. my topic was Big Data.

1. AI in Soccer Essay
2. The goal of this essay was to explore the different ways that artificial intelligence has begun to take shape within the sport of soccer. A lot of the information was something that I already had prior knowledge of, but I found it particularly interesting to see the ways that data was actually applied to a wide variety of aspects of the sport, from coaching to match scheduling. The ability to curate film through code and other match libraries was also interesting and I found Abhishek’s work in that department particularly applicable to work that I do currently.

1. Include the goals, results, project URL (if applicable), and what you learned in a brief paragraph.
2. Once approved, the description is automatically displayed in a post on your e-portfolio.

mis 2502 extra credit

The overall goal of this learning is to understand the Amazon cloud computing concepts, AWS core services, security, architecture, pricing, and support