DAT 260 Project
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Feb 20, 2024
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Proposal for New Wearable IoT Product
Created by Tara Culpepper
2/17/2023
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Big Data Tools
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Big data is used in analytics to find patterns, trends, and preferences. Big data is what fuels our online infrastructure. Big data is large data sets that can be analyzed to reveal trends that could be impossible to process traditionally. Big data benefits different aspects of online operations such as risk management, which can help catch fraud on sensitive data. Next, innovative ideas can create efficiency in an industry. Finally, it can benefit the overall customer experience, big data can create a monitoring system to make sure that the issues are resolved as quickly as possible. Big Data is an essential tool for many organizations, and can range from large to smaller companies. Big data works to collect, process, and analyze any large datasets that would help optimize the operations of an industry. Big data works to collect data, process data, clean data, and analyze data. Some of the best tools that can be used to analyze big data are Python, STORM, Spark and Hadoop. Each of these tools are used for specific industries and specific tasks, each have their own benefits. For example, Python is very well known and is best used for statistical analysis whereas Spark is best used for group processing. Relational vs. Non-relational Databases
Relational databases store data and allow access to data that relate to each set, best used for complex queries making it best used for structured data. Whereas non-relational databases are
best used with unstructured data. Non-relational databases offer a more flexible approach to storing data. Structured and unstructured data is important to note based on how each database runs. The difference between relational and non-relational databases is the way that data is
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stored. Relational databases are stored in rows and columns and non-relational databases use a storage-like model. Effects of IoT
IoT, Internet of things, is popular when working to impact the way that industries operate
technical experiences. Based on customer experience it can monitor the problems that arise and find solutions and solve them before they surface. IoT can predict problems before they happen so that solutions can be fixed efficiently. A way that IoT can improve an organization’s ability to use information to benefit their customers is when discussing maintenance operations, IoT plays a huge role in daily operations. AI and IoT are used on heavy machines and equipment. Before the use of Iot and AI, industries used to discover a failure and it caused a large amount of down time for that piece of equipment, causing a halt to production putting an industry behind. Iot gives an industry the opportunity to rely on preventative maintenance to solve this problem. Preventative maintenance can help move
operations along, and make sure that customers receive their goods and services in a timely manner. Machine Learning and AI
Machine learning works hand and hand with artificial intelligence or AI. Machine learning can improve a business process and solutions that create a more effective level of customer service. AI and machine learning can offer personalization, faster assistants, understand
the customers needs better by providing common questions as well as the improvement of customer analysis. Machine learning will pull data from what the customer provides to be able to
use it to be able to predict the patterns and trends of individuals and how an industry can
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efficiently solve customer problems. AI can be used to identify a consumer's risk for fraudulent activity and use it to create preventative measures to guard their personal and private data. Impacts of AI
AI has the opportunity to benefit from the technical advances in our life however, there are cybersecurity threats that we may face when it comes to further development of AI and IoT-
powered capabilities is just how vulnerable the devices can be. Take IoT-powered devices, according to a comcast report “the average households is hit with 104 threats every month,” leaving devices that are unable to hold any firewalls or antiviruses more apt to be hacked, thi is because IoT-powered devices do not have the facilities to hold ay protection based on the storage
capabilities of such devices. There will always be cyber security risks when using AI, as AI continues to change, hackers are gaining the same amount of knowledge and are able to be one step ahead. Making sure your devices have strong passwords and making sure that when on an unsupported WiFi that you have your information protected as much as possible. AI and Business Strategies
AI can be used to facilitate interaction with consumers by improving efficiency, and promoting optimization in an industry. For example, maintenance issues are a top issue for manufacturing industries, and how it could halt production. During a busy season, a company might struggle if there are any long term shut downs to pieces of equipment. This in turn leads to
loss of money, and a loss of production time. AI could be used to manage such production problems, giving companies the opportunity to predict when a maintenance failure may take place.
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References
MongoDB. (n.d.). What Is A Non-Relational Database? https://www.mongodb.com/databases/non-relational
Rayome, A. D. (2018, March 16). 4 ways IoT can improve the customer experience. TechRepublic. https://www.techrepublic.com/article/4-ways-iot-can-improve-the-
customer-experience/
Kapoor, A. (n.d.). Hands-On Artificial Intelligence for IoT. O’Reilly Online Learning. https://www.oreilly.com/library/view/hands-on-artificial-intelligence/
9781788836067/27671693-a149-4657-8bc3-990df9e000cd.xhtml