Search Results for: Analytics

For this Data and Analytics project, students were expected to research a current Data Analytics topic and write a short overview of their topic, how the it relates to material discussed in class, and an real world example of how this idea is used in practice. After quickly researching many suggested topics, I was became interested in text mining and sentiment analysis and wanted to explore these ideas further. I learned what sentiment analysis is, the purpose and importance of this technology, and how it is applied in a business setting. I would love to experiment with and even work with  text mining and sentiment analysis in the future to learn more and become well versed in these topics. My full report and bibliography could be found here.

Mike McGill

Prof. Raven

MIS 2502

4/11/21

MIS2502: Data Analytics
Optional Extra Credit Assignment

              In the modern business efficiency has become the name of the game. With this big of an emphasis on the importance of maximizing efficiency more and more industries turn to technology to scrape any competitive edge. In MIS 2502 we are beginning to build the foundational tools of using data bases to reduce “redundancy”. On a larger scale in both production and data management businesses are expanding into pairing AI with Big Data to bring efficiency to a near frictionless point. Chemical companies like Solenis, have implemented AI to negate any waste in chemical application. Titans of business like Disney, are using Big Data analytics to predict market movements as if they were privy to tomorrow’s news. AI and Big Data are changing our definition of efficiency, and the companies that wield this power are holding the competitive edge in the modern business.

Artificial intelligence otherwise known as AI is the expansion of automated technology into areas that would normally require human input. AI is capable of predictive calculations as well as sorting data at a rate no longer matched by humans. In 2019 Solenis successfully released OPTIX Applied Intelligence an AI designed on the platform of ProcessMiner, with the goal to better the paper and pulp industry (1). Today, Solenis has seen great success with OPTIX still continuously increasing the product quality while reducing the usage of raw materials as well as water and energy consumption in the mills that bring in Solenis. With the algorithm set to perfection OPTIX makes certain that mills waste no bottom line in subpar batches of product. The predictive capabilities of this technology mean that any chemical input on Solenis’ end is done at the bare minimum needed to achieve success, so there are no wasted inputs of material in production. Beyond the monetary bottom line that the AI implementation of OPTIX will save a company when it comes to efficiently reducing waste, the modern world also has a huge demand for sustainability. Simply said, we live in a world of finite resources and AI ensures that none of those resources go to waste and the industrial process becomes a lot greener.

Big Data refers to every single bit of information that can be inputted and used for the benefit of business. Recently we learned how NoSQL can be used to sort through these inputs to answer specific questions. During our assignments we sorted through a few hundreds of fake inputs and answered trivial questions. Disney on the other hand is sorting their Big Data analytics with an Affective AI. This allows them to accurately gauge the potential consumer appeal of unreleased products at a more precise level than what normal market tests can provide (2).

Big Data and AI are no longer a thing of the future. In fact, companies that steer away from their benefits are falling further and further behind. In the ever-increasing demand for optimization in business, technology is seemingly the only path for a competitive company to stay afloat.

 

 

Works Cited

 

1. “OPTIX AI Helps Paper Mill Operations.” Solenis, 22 Feb. 2021,

www.solenis.com/en/resources/news-releases/2020/solenis-enables-tissue-maker-to-achieve-unprecedented-autonomous-chemistry-control-with-artificial-intelligence-platform.

 

2. “Big Data Behind Disney Magic.” Digital Innovation and Transformation, 13 Nov. 2019,

digital.hbs.edu/platform-digit/submission/big-data-behind-disney-magic/.

 

 

 

The goal of the Write-Up was to research a current topic on Data Analytics that was not extensively discussed in class. For my Write-Up I choose to research the topic of Big Data. Through this assignment, I referenced various sites and gathered information on all things related to Big Data. I learned how Big Data was collected, stored, processed, and utilized. Most importantly, I gained deeper understanding of how Big Data is a powerful tool and offered massive value to organizations as they make decisions and predict future outcomes.

MIS2502 Big Data Write Up

 

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.

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.

AI in Data Analytics_ CSabanas 12.5.2020

Goal  – Research a current topic on Data Analytics that was not covered extensively in class, then create a write-up, with the purpose of this assignment to give an outlet to display ability to understand and describe an aspect of data analytics to current and future employers.

Results – extra credit paper

I learned the connections between sports and NoSQL, and how important it is for teams to store their unstructured data to understand their players.

1. Overview and Purpose:

   Research a current topic on Data Analytics that we have not covered extensively in class. You will create a write-up, and the purpose of this assignment is to give you an outlet to display your ability to understand and describe an aspect of data analytics to your current and future employers.

   Possible topics:

   • Big data
   • Distributed data technologies (i.e., Hadoop)
   • Natural Language Processing
   • Text mining and sentiment analysis
   • Virtual data cubes and/or in-memory analytics
   • The Internet of Things (IoT)
   • Cloud-based analytics/Cloud computing
   • NoSQL databases
   • Deep learning
   • Artificial Intelligence
   • Social network analysis/analytics

   Content:

   Your write-up should be between 300 and 400 words, not including references.

   You should cover the following points in your writeup:

   • A brief overview of the topic (i.e., what is it and why is it important).
   • How the topic relates to the material we have covered in MIS2502. How does it build on the concepts covered in the course? What are the related topics in MIS2502?
   • An example that describes how this tool or technique has been applied in practice.
   • Citation Guidelines: If you use materials (text, figures, data, etc.) in the write-up that was created by others, you must identify the source and clearly differentiate your work from the materials that you are referencing. Failure to do so will be considered plagiarizing. There are many different acceptable formats that you can use to cite the work of others. The format is not as important as the intent. You must clearly show the reader what is your work and what is a reference to someone else’s work.

Response:

Big data and new data collection and analysis techniques are providing unique insights for people, businesses, and governments across the world. Data professionals in all fields are working tirelessly on finding the tech world’s next big breakthrough. Recently, insurance companies have begun to use telematics devices for more advanced and detailed data collection.

A telematics device is a data collection device, usually provided by your insurer, which transmits certain data to your insurance provider for advanced analysis on your driving behavior. By implementing these devices, insurers are better able to assess the risk tolerance and expected loss for insuring a particular driver. One of the driving principles of insurance is uncertainty. Customers and insurers alike are uncertain about the amount of losses they may occur. Collecting more advanced data such as average speed, acceleration rates, total driving time, and other metrics allows insurers to perform complex data analysis, pool similar drivers together, and more accurately calculate fair premium rates for their customers. Telematic devices can be advantageous for consumers as well. These devices, if used effectively, can lower insurance premiums and encourage drivers to take fewer risks or avoid risky behavior in general when driving. Furthermore, insurers may even be able to create new risk pools with lower overall premiums for high performing, telematic-using customers.

MIS 2502 explores the major principles and processes of data analytics through exploring traditional data analysis (SQL, NoSQL, MongoDB, Tableau, etc.) and data mining (Decision Trees, Clustering, and Association Rule). Some of these techniques would surely be used to help determine the premium rate set by insurers using telematic devices. Data analysts would use some sort of querying language to pull out the data they would like to use to run an analysis. Then they would transfer it into a digestible format for the analytical data store. Once stored, they extract the data and run some sort of mining analysis. In this case, analysts could use decision trees to determine if drivers will or will not exceed the loss amount that would be covered by their current premium. If they determine a driver will not exceed projected losses, the insurance company may then be more confident in lowering the premium rates for their customer.

 

John Jeong

Tuid: 909875325

April 20, 2019

MIS 2502 Section 004

Professor. Deng

 

Artificial intelligence

 

Nowadays, most people have access to social media software, such as Facebook, Instagram, Waze, and the host of apps found on their phone. These softwares, so called applications, have some level of artificial intelligence (AI). The programmed AI shows the user an advertisement that the user might be interested in, or shows the fastest route based on traffic conditions. AI has improved people’s lives more by helping people be more efficient. Additionally, it can teach itself to do the work of a human and they are more accurate and faster than when a person does the work. Hence, AI will lead this generation into the next advanced innovative society.

Throughout MIS 2502, we have learned with R how to interpret data and make decisions. With the help of the program, the work has gotten much easier and more accurate, but we still have to follow our intuition when we make decisions such as, how many clusters we should have to interpret most accurately, or how many nods we need to have within a decision tree, or deciding whether the chart is junk or not. All these decisions can be taught and learned from experiences. However, there is still a chance of making mistakes or interpreting incorrectly. With the help of AI, we can minimize the risk so that we can maximize our scarce resources.

More than 90 percent of the data we have today was generated within last two years. It is nearly impossible for humans to have access to all that data and make precise decisions interpreting them. However, AI can not only have access to all the information but can also interpret and make the most accurate decisions, better than a human’s intuition. For example, Google’s DeepMind has created an AI called AlphaGo that plays a board game called “Go” which has infinite combinations of moves. AlphaGo had access to records of all the games ever played and learns from them. It also has access to the internet so it can learn new moves instantly as it is playing the game. Ultimately, make its own decision that it thinks has the highest possibility of winning. AlphaGo played against Lee Sedol, the Go grandmaster, and the result was victorious. This kind of moment shows that an AI is more accurate and effective than a person who is at the highest level one can be.

The world has revolutionized rapidly in the last 100 years. During that period, humans have developed tools to make the revolution of industry much easier and faster. Now, there is AI, a new tool that humans have developed to aid the revolution. With AI, we will accomplish more than what we have in the past.

 

 

 

 

 

 

 

 

 

 

 

 

 

References

90% Of Today’s Data Created In Two Years. (n.d.). Retrieved from

https://www.mediapost.com/publications/article/291358/90-of-todays-data-created-in-two-years.html

 

90% Of Today’s Data Created In Two Years. (n.d.). Retrieved from https://www.mediapost.com/publications/article/291358/90-of-todays-data-created-in-two-years.html

 

Artificial intelligence vs human intuition: interpreting data. (2018, August 23). Retrieved April 23, 2019, from https://medium.com/@BetterTrader.co/artificial-intelligence-vs-human-intuition-interpreting-data-5f8f0c5712e6

 

 

 

Goals-

A brief overview of the topic (i.e., what is it and why is it important).  How the topic relates to the material we have covered in MIS2502. How does it build on the concepts covered in the course? What are the related topics in MIS2502?  An example that describes how this tool or technique has been applied in practice.

URL –

NoSQL Databases

What I Learned –

During this assignment, I was able to learn about new technology that relates to data. It was great to learn about NoSQL and how it is currently being implemented in the industry.

 

 

 

1. For this class project I researched Big Data. The concept of Big Data is extremely relevant to MIS2502. The assignment can be viewed at: http://community.mis.temple.edu/shorgan/coursework/mis2502-big-data/