AI in Big Data
Artificial Intelligence and Big Data technologies, along with Internet of Things, Blockchain, are playing a crucial role in transforming modern business operations. Most organizations leverage only 20% of their data effectively and leave the remaining 80% outside of the decision-making processes (Hackernoon, 2019).
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| (Rahul Asthana, 2019) |
The data is growing exponentially stimulated by the IoT, churning out of the data by consumers and business. It does not matter whether the data is in multiple dimensions or one, structured or unstructured, fast or slow, if the data is massive organizations need apply new technologies to help manage it, understand data trends and derive actionable insights. In other words, collecting such massive data is only useful if it can be processed in right ways. This is where technologies like AI comes into play and helps in analysing, assisting in understanding the data properly, digging into the buying patterns deeper (Sinur, 2019).
Here are the areas where AI can assist humans (Asthana, 2019):
- Anomaly detection: AI can assist by recognizing unusual occurrences in the data set to identify a potential problem that needs attention.
- Future outcome prediction: AI can analyse Big Data using statistical algorithms to determine known conditions that have a certain probability of influencing the future outcome.
- Pattern recognition: AI can inspect Big Data to find both expected and unexpected events, signals, and patterns that were undetected by humans through NLP categorization and relationship capture.
- Hyper-personalization: AI can assist with building personalized customer profiles by leveraging machine learning technics that can learn and adapt.
- People identification: AI is useful for identification of people using biometric data such as fingerprints, retinal eyes scans, and facial recognition.
Conclusion
AI and Big Data are now seemingly inseparable and creating a synergistic effect, where AI is useless without data and data is overwhelming without AI. This modern trend is driven by the deep understanding that AI analytics applied to Big Data can be a virtual goldmine for organizations (Gupta, 2015).
References:
Hackernoon (2019) “Artificial Intelligence and Big Data”. Available at https://hackernoon.com/artificial-intelligence-and-big-data-zys3258 (Accessed: 19 February 2020).
Jim Sinur (2019) “AI & Big Data; Better Together”. Available at https://www.forbes.com/sites/cognitiveworld/2019/09/30/ai-big-data-better-together/#2e366d3360b3 (Accessed: 20 February 2020).
Rahul Asthana (2019) “Big Data and Artificial Intelligence”. Available at https://www.colocationamerica.com/blog/big-data-and-artificial-intelligence (Accessed: 20 February 2020).
Vin Gupta (2015) “Without Good Analysis, Big Data Is Just a Big Trash Dump”. Available at https://www.entrepreneur.com/article/246470
(Accessed: 20 February 2020).

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