Telecom Data Normalization via Intermediate Representation
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Solution Overview
Problem
Modern telecommunications networks face challenges in managing varyingly structured or unstructured data from multiple sources, leading to inefficiencies in detecting inconsistencies and ensuring network reliability due to manual processing limitations.
Innovation Solution
A system that receives and processes data related to network elements by generating an intermediate representation, applying parsing templates, correlating values to a network model, and normalizing data for storage in a database, enabling automated and consistent handling of disparate data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual entry of data from one system to another is used, then data exchange between parties is possible, but the process is error prone and time-consuming
Solution Approach 1:
The patent introduces an intermediary data processing system that receives data from multiple sources in varying formats, transforms them into a common data model, and stores them in a centralized database. This intermediary layer automatically handles data exchange between network planners, service providers, and vendors, eliminating manual entry errors while ensuring data consistency across all parties.
Solution Approach 2:
The system changes the parameter of data format by detecting the document class of incoming data and automatically transforming it into a standardized internal representation. This parameter transformation allows diverse data formats from multiple sources to be uniformly processed and stored, improving both ease of operation and data reliability.
2Reliability
If manual detection of inconsistencies among varyingly structured data is performed, then data consistency can be checked, but the complexity of current communications networks makes this approach not viable
Solution Approach 1:
The patent segments the data consistency checking function into automated components: a document class detector that identifies data types, a parser that extracts values according to predefined templates, and a correlator that maps data to network entities. This segmentation of the consistency checking process into automated modules makes it viable despite network complexity.
Solution Approach 2:
The system performs self-service by automatically detecting document classes, selecting appropriate parsing templates, extracting values, and correlating data without human intervention. This automation enables consistent data detection across complex networks while reducing the operational burden on network operators.
3Adaptability or versatility
If varyingly structured or unstructured network-related data is processed manually, then data from multiple sources can be handled, but fast detection of inconsistencies and accurate diagnosis of network issues cannot be ensured
Solution Approach 1:
The system performs preliminary action by pre-defining parsing templates for different document classes before data arrives. When data is received, the system only needs to detect the document class and apply the pre-prepared template, rather than creating parsing logic from scratch. This preliminary preparation enables fast detection of inconsistencies while maintaining adaptability to various data formats.
Data Source
AI summary
Systems and methods are disclosed for managing data related to network elements in a telecommunications network. In an embodiment, a document containing data related to one or more of the network elements is received. The document is associated with a corresponding source provider, a location, a receipt timestamp indicating the time and date that the data was received, and a creation timestamp indicating the time and date that the data was created. A document class is then detected for the received document, and an intermediate representation of the document is generated that includes a plurality of key-value pairs. The intermediate representation is parsed to identify relevant values that correlate to a network model that includes a plurality of network entities representing types of network elements in the telecommunications network. Finally, the identified values are normalized according to the network model and written to a networking database.