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Big Data Processing Technologies
In recent years, there is a big demand for obtaining knowledge/regularity from the big data, terabytes/petabytes of data, to create business values or make society more sophisticate and efficient.
Big data processing can be classified into two types of methods in terms of required processing latency. One is the batch based stored data processing and the other is the real-time data-stream processing.
NEC is focusing on developing technologies not only for enhancing the batch based analytics and the data-stream processing , but for fusion of the two in order to realize deep real-time analysis.
- Distributed data stream processing technology for on-the-fly real-time analytics of data/events generated at extremely high rates.
- Technologies for reliable distributed data store, high-speed data structure transform to create analytics DB and quick data placement management.
- Scalable data extraction technology to speed up rich querying functionality, such as multi-dimensional queries, over a Key-value store.
- Scalable distributed parallel processing of a huge amount of stored data for advanced analysis such as machine learning.
