Solutions for Telco Industry
Operation Acceleration, Big Data Strategy Deployment
With the rapid development and wide application of mobile communications technology, smart phone mobile devices have quickly occupied the market. Telecommunication companies collect massive amounts of data about their user information and network. It is extremely important to analyze and mine spending power, traffic, network requests, displacement volume of mobile users, and build a new service and application program.
- Data silos Data is stored across a company's many physical locations. Each company subsidiary keeps its own data and segregates it based on different business categories.
- Data volume Massive amounts of disparate and complex data are being collected. Daily transactions can generate up to hundreds of billions records with hundreds, even thousands, of dimensions.
- Diversified operations Data comes from a variety of sources such as daily transactions, social media, GPS, corporation internal O&M, business channels and so forth.
- Data consistency and consolidation Cross-regional and cross-business data will need to be unified and consolidated while the quality, reliability and consistency of data can be maintained.
- Big data storage Massive data needs to be stored while latency needs to be reduced from data transfer to guarantee reading and access speed.
- Big data analysis The big data ecosystem should not only include management of existing analysis models but also provide self-service to explore and build new models.
Rapids Data's big data platform has developed a business needs-based labeling classification system and a search engine. Through analysis of customer behavioral patterns in accessing the network, the platform can provide insights into network issues, allowing telco companies to optimize their services with equipment monitoring, capacity planning, and preventative maintenance. It also provides customer matching and marketing strategy optimization recommendations for merchants/advertisers to materialize their data value.
- 01 Distributed storage: Rapids Data's big data platform allows for horizontal storage capacity expansion without compromising performance.
- 02 High hardware availability: Through software design, hardware failures can be detected and mitigated as part of a routine procedure.
- 03 “Non-shared” architecture: The independence among the distributed machine nodes, data center and data mart prevents resource contention and ensures the efficient and stable operation of the platform.
- 04 Exploratory self-servicing analysis: In response to ever-changing business needs, the Rapids Data platform provides self-service data preparation and analytics.
- Storage As a data warehouse, a distributed data center needs to undertake data storage and balance the resources of various functions. Rapids Data's big data platform can solve the bottlenecks of high concurrence and throughput of distributed data centers.
- Computing The Rapids Data MPP data mart is a distributed data store that is dedicated to analytic data, and concentrates more system resources on data retrieval and distributed computing. At the same time, distributed storage ensures data independence and integrity.