Smart Data Analytics

Smart Data Analytics

 

When it comes to data analytics, T-Labs is working on concepts for handling extremely huge volumes of data cost-effectively, for example, to discover behavior patterns for specific user groups so that customized service offerings can be developed for them. Research is being done on context solutions based on scientific behavioral findings gathered from anonymous segmentation and signaling data from the mobile communications network, used externally and in conjunction with other mobile technologies such as WLAN in buildings (e.g. indoor analytics). The main objective is to develop new business models with enterprises from other branches of industry.

The consolidation and analysis of telecommunications data and partner data will result in a new kind of value for industry and end users. In addition to the analysis of existing data pools, data analytics are also applied to modern M2M solutions with new and emerging data volumes of enormous magnitude, especially in vertical industries. Key topics here are proactive maintenance, mobile monitoring and communication, which play a role in specific activities. The current portfolio offering will be enhanced with our own and external services (Industry 4.0), and we are collaborating here with customers such as Claas and Lekkerland. Overarching segment data can also be used for proactive troubleshooting, for example, to reduce the number of customer contacts and optimize call center operations. Network data analysis is also an option for improving operational efficiency through optimized network performance and better capacity utilization.

T-Labs has set up an analytics workbench and toolbox to support the initial analyses of huge volumes of unstructured data that are significant to Deutsche Telekom's big data research. Another step toward the advancement of Big Data is the establishment of a competence team which is charged with promoting Group-wide transparency, with the intention of ensuring the exchange of knowledge and information among relevant units to support the positioning of this key topic within Deutsche Telekom. With the support of the Creation Center the competence team took user-centric deep dive into Big Data and developed a compass for Big Data Business in the DTAG.

Landing Page: Smart Data
 

 Data Analytics

 

When it comes to data analytics, T-Labs is working on concepts for handling extremely huge volumes of data cost-effectively, for example, to discover behavior patterns for specific user groups so that customized service offerings can be developed for them. Research is being done on context solutions based on scientific behavioral findings gathered from anonymous segmentation and signaling data from the mobile communications network, used externally (Motionlogic) and in conjunction with other mobile technologies such as WLAN in buildings (indoor analytics). The main objective is to develop new business models with enterprises from other branches of industry (SureNow).

The consolidation and analysis of telecommunications data and partner data will result in a new kind of value for industry and end users. In addition to the analysis of existing data pools, data analytics are also applied to modern M2M solutions with new and emerging data volumes of enormous magnitude, especially in vertical industries. Key topics here are proactive maintenance, mobile monitoring and communication, which play a role in specific activities. The current portfolio offering will be enhanced with our own and external services (Industry 4.0), and we are collaborating here with customers such as Claas and Lekkerland. Overarching segment data can also be used for proactive troubleshooting, for example, to reduce the number of customer contacts and optimize call center operations. Network data analysis is also an option for improving operational efficiency through optimized network performance and better capacity utilization.

T-Labs has set up an analytics workbench and toolbox to support the initial analyses of huge volumes of unstructured data that are significant to Deutsche Telekom's big data research. Another step toward the advancement of Big Data is the establishment of a competence team which is charged with promoting Group-wide transparency, with the intention of ensuring the exchange of knowledge and information among relevant units to support the positioning of this key topic within Deutsche Telekom.