Huawei’s Big Data Analytics Awarded Most Innovative Data Governance Solution

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With the upgradation of the tech world and the increase in real-time transactions, the need for the best data management had its way out. We nowadays are very closely related to concepts like cloud computing, 5G, and IoT. The latest reports reveal that today at the Telco Big Data Analytics Summit Euro 2017, hosted by Informa and Telefonica, Huawei’s big data analytics platform FusionInsight-Universe Analytics received the ‘Most Innovative Data Governance Solution’ award.

Huawei’s big data product expert Ignacio Barbudo stated how Huawei has accumulated machine learning technology and knowledge from multiple years of Telco big data project implementation in its FusionInsight-Universe Analytics platform and provided intelligent data integration capabilities to carriers.

Huawei’s big data governance solution provides high-quality data to AI and big data applications efficiently and shortens the AI and big data application Time to Market (TTM). The solution further helps in reducing data integration workloads. This includes:

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  1. data management across heterogeneous data warehouses.
  2. integrated quality audits.
  3. data lifecycle management.
  4. data lineage analysis.

Therefore, on the basis of the reports gained with the experience with China Mobile and many other projects, data governance efficiency has increased by more than 40%, and high-quality data increased by more than 40%. At the same point in time, the data preparation cycle decreased to hours from months, and AI and big data application TTM decreased from months to weeks.

Summit guests from carriers praised Huawei for its intelligent data government solution. The solution is highly capable of resolving the issues related to:

  • big data governance efficiency.
  • reduce big data utilization costs by resolving problems like a lack of Telco data knowledge.
  • poor data quality.
  • long data preparation TTM.

Huawei has promised to provide better data governance solutions by continuously improving capabilities like data management across heterogeneous data sources, automatic data feature detection, and intelligent data preparation.

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