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Powerful Machine learning algorithms demonstrate value through three ways that can be easily implemented in your business today.
Reveal and optimize processes in ways
Automated learning can effectively help in processing data that has been too complicated or expensive to analyze before. This gives insights into processes that can be improved in new ways.
Predictive maintenance: Use detailed sensor data and algorithms to deter the first real signals of problems in parts or machines. BI Consultant in Saudi Arabia this can save huge sums of money compared to changing them on a regular schedule regardless of whether they are worn or not – worse – wait until the parts fail and production stops. These techniques are even used for expensive human assets such as professional athletes.
Text analysis and classification: Machine learning can be used to extract texts and images from electronic documents, and then classify that information so that it can be analyzed more easily than ever before. Microstrategy Consultant in Saudi Arabia uses include analysis of insurance claims texts for potential fraud and emotion analysis for customer retention and drug interactions based on research documents and much more.
- Machine learning requires a lot of high-quality data. In most enterprises, this is found in current business applications such as finance, logistics and sales. The data in these systems has already been collected, cleaned and stored over a long period of time, so there is a lot of data available to create useful and useful predictive models.
- Machine learning works best when there is a precise decision, thousands of times a day, using a few variables, where the errors are obvious and can be corrected quickly to improve the SAP BO Business Objects Consultant in Saudi Arabia For example, “Which of these bank payments corresponds to this invoice?” Much easier than “How can we improve lung cancer survival rates over the long term?”
Few Examples of automatable processes:
- Classification of transactions for tax compliance
- Predict when needed to renew contracts based on use
- Forecasting and delays in transit stock delays
- Calculate the optimum length of time between actual inventories to ensure their compatibility with automated systems
- Direct customer service requests to the most appropriate teams
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