As a result, big data and artificial intelligence expand upon traditional customer relationship management (CRM) while increasing both efficiency and customer satisfaction. In the future, artificial intelligence will be an essential part of every point at which businesses and customers interact. Chatbots are just one example of new, language-based interfaces.
2. Use unstructured data with machine learning
The digitization of documents, patents and maintenance reports, or of entire archives and image databases, generates a wide range of unstructured mass data that is not easily accessible for conventional analysis. Businesses can also use machine learning to transform this data into value-added benefits. One example is invoice auditing. Big companies receive thousands of printed invoices from various sources that have to be scanned, audited and matched with the correct cost center. Machine intelligence allows algorithms to independently learn how to audit and match invoices or identify commonly occurring errors by reviewing maintenance reports.
Machine learning is also enjoying increasing use in applications related to the Internet of Things (IoT). Smart sensors record and intelligently analyze data. One example is condition-based maintenance of equipment in buildings and factories. Sensor swarms can use vibration and noise measurements to learn to differentiate between the normal operating condition and impending damage – a feature that can be used in the maintenance of elevators, escalators and ventilation systems in buildings, as well as in highly sophisticated manufacturing machinery or machines and vehicles used in the construction sector.
Smart data analytics at Lufthansa Industry Solutions
- Conceptualization and implementation of big data solutions, from the development of architecture and implementation to staff training
- Development of analyses and reports or fully data-based minimum viable products (MVPs)
- Consultancy and use of machine learning and artificial intelligence technologies for the analysis of unstructured mass data
- Intelligent analysis of sensor data