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|Efficient expansion of data warehouse system in big data environment||Real-time search of over 2 billion mobile network quality information on a daily basis on the map|
|The existing data warehouse(DW) system becomes unstable due to the explosion of input data(over 100 billion data per day).|
⇒ Instead of expanding capacity of the existing DW system at high cost, IRIS takes over heavy-load processes running on the DW.
|Data can not be retrieved due to performance degradation when searching for massive data(more than 2 billion a day) related with the wireless quality
⇒ Stores and searches wireless quality data in IRIS
|- Reduces the expansion cost of existing DW by 60%|
- Resolves the problem of service disruption caused by data explosion
|- Allows users to search wireless quality data at low cost by introducing IRIS|
|Service quality analytics per 4G/5G subscriber||Cyber threat information sharing system|
|Analytics system of service quality perceived by individual subscriber is necessary in order to resolve customer complaints about service quality.|
⇒ A probe system together with IRIS is introduced.
|Client wants to share the cyber attack information with external organizations in real time in order to respond to cyber attacks and prevent the spread of damages.|
|- Captures packet data from the network and generates the detailed call logs in real time|
- Allows operators to monitor end-to-end service quality per subscriber in real time
|- Provides a comprehensive analysis environment for various types of cyber attacks
- Contributes to prevent spread of damage by sharing information in real time
IRIS DB has acquired GS(Good Software) certificate and received the New Software Grand Prize.
Mobigen's IRIS DB was certified with GS(Good Software) related to big data DB for the first time in South Korea The outstanding quality of IRIS DB has been recognized with the New Software Grand Prize from the Minister of Knowledge Economy.
Mobigen has proved that it enabled to analyze more than 100 billion records per day successfully by applying IRIS DB Cluster to systems that are desired to process such big data.
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