Cognitive cloud computing is a technology platform that combines machine learning, reasoning, natural language processing, speech, vision, and human-computer interaction in a way that mimics the functioning of a human brain. It facilitates better human decision making by allowing thorough data analysis.

For most of businesses, data collection and analysis are important to grow their market and have an insight into the customer experience. Cognitive cloud computing can help in an in-depth analysis of data for making informed and faster decisions. It also allows bringing together the data sets of different departments of an organization for facilitating holistic ideas for business growth.

Here are some applications of cognitive cloud computing in different business aspects:

• Chatbots: Chatbots understand the contextual meaning of communication to simulate a human conversation. The programs use a machine learning technique called natural language processing that helps in receiving human input, analyzing it, and providing logical answers. Cognitive computing helps the chatbots in implementing intelligence in communication like understanding user’s requirements based on past interactions, etc.
• Sentiment Analysis: It is a branch of science that deals with understanding the emotions conveyed in a communication. Unlike humans, it is difficult for machines to understand conversational aspects such as tone, intent, etc. In order to facilitate this, cognitive computing is used to feed the training data of human conversation to the machines and then analyze the accuracy. This helps businesses in understanding and analyzing user communications including social media interactions such as tweets, comments, reviews, complaints, etc. for delivering better customer service.
• Face Detection: Businesses are incorporating face detection for ensuring higher levels of system security. The security feature has numerous applications such as securing user access, security lockers, mobile phones, etc. The underlying process of face detection is an advanced image analysis. This is facilitated by a cognitive system that uses data like facial structure, contour, eye color, etc. to differentiate it from others. While traditional systems used 2D images, advanced cognitive computing techniques make use of 3D sensors that result in higher accuracy.
• Risk Assessment: Risk management and analysis is a major part of businesses. It requires a thorough analysis of market trends and historical data to predict uncertainties involved in an investment. However, big data analysis alone is not sufficient to do a thorough risk assessment. It also requires intuition, experience, gut feel, and behavior analytics. Thus, it becomes essential to make algorithms intelligent. This is made possible by cognitive computing as it combines behavioral data with market trends for generating meaningful insights that can be further analyzed by experienced analysts.
• Fraud Detection: Businesses need to detect frauds or anomalies in order to avoid situations that may cause financial loss or hamper brand image. This can be done with the help of programs that can analyze past data to understand perimeters to be used for judging a transaction. This is another business application of cognitive computing that involves techniques such as Logistic regression, decision tree, random forest, clustering, etc.

For more information on business applications and benefits of cognitive computing, call Centex Technologies at (972) 375 - 9654.

Cognitive cloud computing is a technology platform that combines machine learning, reasoning, natural language processing, speech, vision, and human-computer interaction in a way that mimics the functioning of a human brain. It facilitates better human decision making by allowing thorough data analysis.

For most of businesses, data collection and analysis are important to grow their market and have an insight into the customer experience. Cognitive cloud computing can help in an in-depth analysis of data for making informed and faster decisions. It also allows bringing together the data sets of different departments of an organization for facilitating holistic ideas for business growth.

Here are some applications of cognitive cloud computing in different business aspects:

• Chatbots: Chatbots understand the contextual meaning of communication to simulate a human conversation. The programs use a machine learning technique called natural language processing that helps in receiving human input, analyzing it, and providing logical answers. Cognitive computing helps the chatbots in implementing intelligence in communication like understanding user’s requirements based on past interactions, etc.
• Sentiment Analysis: It is a branch of science that deals with understanding the emotions conveyed in a communication. Unlike humans, it is difficult for machines to understand conversational aspects such as tone, intent, etc. In order to facilitate this, cognitive computing is used to feed the training data of human conversation to the machines and then analyze the accuracy. This helps businesses in understanding and analyzing user communications including social media interactions such as tweets, comments, reviews, complaints, etc. for delivering better customer service.
• Face Detection: Businesses are incorporating face detection for ensuring higher levels of system security. The security feature has numerous applications such as securing user access, security lockers, mobile phones, etc. The underlying process of face detection is an advanced image analysis. This is facilitated by a cognitive system that uses data like facial structure, contour, eye color, etc. to differentiate it from others. While traditional systems used 2D images, advanced cognitive computing techniques make use of 3D sensors that result in higher accuracy.
• Risk Assessment: Risk management and analysis is a major part of businesses. It requires a thorough analysis of market trends and historical data to predict uncertainties involved in an investment. However, big data analysis alone is not sufficient to do a thorough risk assessment. It also requires intuition, experience, gut feel, and behavior analytics. Thus, it becomes essential to make algorithms intelligent. This is made possible by cognitive computing as it combines behavioral data with market trends for generating meaningful insights that can be further analyzed by experienced analysts.
• Fraud Detection: Businesses need to detect frauds or anomalies in order to avoid situations that may cause financial loss or hamper brand image. This can be done with the help of programs that can analyze past data to understand perimeters to be used for judging a transaction. This is another business application of cognitive computing that involves techniques such as Logistic regression, decision tree, random forest, clustering, etc.

For more information on business applications and benefits of cognitive computing, call Centex Technologies at (972) 375 - 9654.