Kenmei Technologies Announces Strategic Technical Partnership with DrakosDataThe objective of this major partnership is to integrate DrakosData's advanced reporting architecture into Kenmei Technologies' solution ADELE. Likewise, mobile network operators will benefit from sub-second response times reporting capabilities, while ensuring massive data scalability. Big data-native system ADELE (which stands for Autonomous Decisions and Learning) allows multiple operational tasks to be performed automatically, enabling network technical teams to gain process, configuration agility and focus on actual issues. DrakosData solutions are based on Apache Kylin™, an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark, supporting extremely large datasets. The combination of both Kenmei Technologies and DrakosData know-how will allow mobile network operators to achieve real-time query capabilities and to provide analytics that are not possible with current stacks. "We are very excited to enter into this new partnership with DrakosData," "DrakosData is thrilled to be partnering with Kenmei Technologies. Both companies share a mutual belief that a deep understanding of the telecom challenges, technology and craft is key to success, and this is where Kenmei Technologies excels. We believe that by working together, our combined solution offerings will help the mobile network operators to leverage their gold mine of data." said Alberto Ramón, Founder and Chief Executive Officer of DrakosData. Kenmei Technologies is a Spanish company based in Valencia founded by telecoms and software experts, focusing on providing data intelligence by machine-based decision making approaches, automating network operations and customer assurance, all designed to help operators deal with a yet incoming network complexity. For more information visit http://www.kenmei.ai. DrakosData is formed by a team of long-time Big Data enthusiasts, willing to solve one of the biggest challenges that companies face with Hadoop: access to big data lake analytics in a fast way (sub-second) Photo: https://www.prlog.org/ End
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