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IT management is the discipline of monitoring and administering the information technology systems of an organization including the hardware, software, and networks. The main focus of IT management is to find a way to make information systems more efficient and facilitate business growth. Thus, improving IT management can lead to a successful business.

Here is a four-step approach to improving IT management:

Level 1 (Re-Master The Basic Troubleshooting): If an organization is facing problems such as-

• IT support is overloaded
• IT service outages are not resolved timely
• Growing ticket backlog
• Long downtimes disrupting business workflows
• End users are not happy with IT

Level 1 approach is essential for such organizations. The motive is to analyze current troubleshooting practices and makes them more effective. The organization needs to make use of thorough diagnostics, IT support knowledge sharing, and IT infrastructure tracking. The end result involves redesigning the IT processes, redefining IT guidelines, and adjusting the processes to fit the needs.

Level 2 (Prevent IT Failures): Level 2 approach suits the organizations facing issues such as-

• Troubleshooting is fine but IT service availability can’t be improved
• Increasing number of incoming IT tickets
• Growing costs incurred on resolving IT issues
• IT support agents have to spend much time on manual data entry in the ticketing tool

Level 2 approach facilitates preventive IT service management, tracking events/changes in IT infrastructure, managing available IT assets, and automating IT support tasks. It focuses on rooting out the cause of similar incidents and automatic reporting of abnormalities in IT infrastructure to free the IT support for resolution tasks. Proper visibility of IT assets enables timely and efficient distribution among end-users resulting in increased IT service availability. This reduces the IT/business disruption and the costs involved.

Level 3 (Improving IT Services): Level 3 approach is suitable for businesses that extensively depend upon IT to execute business processes. Also, it is the suited solution if the business organization faces any of the following problems-

• No set guidelines for reviewing & improving IT services
• IT costs are very high
• IT service agents can’t conform to strict SLAs

Level 3 focuses on timely updating IT services in order to keep them relevant. It also suggests making use of automation and machine learning for improving IT service management accuracy & productivity.

Level 4 (Merging IT & Corporate Strategies): In a dynamic business environment, it is important to synchronize IT & business strategies for uninterrupted growth. This will facilitate the quick introduction of new IT services whenever a business change occurs.

For more information on a stepwise approach to improving IT management for businesses, 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.

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.