Businesses rely on data from an increasing number of systems, applications, devices, and platforms. Getting that data into the right place, in the right format, and at the right time can become difficult as volumes increase and technology environments become more complex.
A data mediation solution provides the integration layer needed to collect, process, transform, normalize, aggregate and distribute data between different systems without requiring every source and destination to work in the same way.
This is particularly important in high-volume environments such as telecommunications, where usage records and network events need to be processed quickly. The same capabilities can also support organizations that need to integrate data from multiple sources, process it in real time, and deliver consistent data to downstream systems.
Depending on the environment, this can include real-time data integration, data transformation, data normalization, data aggregation, usage data processing, CDR processing, usage mediation and billing mediation.
When Does a Business Need Data Mediation?
Data mediation becomes valuable when data needs to move between multiple systems that use different formats, protocols, structures or processing requirements.
Organizations may need a mediation layer when they are dealing with:
- High volumes of usage or event data
- Multiple data sources and destinations
- Different data formats and structures
- Legacy and modern systems operating together
- Real-time processing requirements
- Data that needs to be transformed or normalized before use
- Usage records that need to reach billing or charging systems
- Network, application or platform data that needs to be aggregated
- Data pipelines that require monitoring and control
In these environments, implementing separate integrations between every source and destination can become difficult to maintain. A mediation layer can provide a more centralized way to manage how data is collected, processed and delivered.
Data Mediation Capabilities for Real-Time Data Integration
A data mediation solution provides an integration and processing layer between systems that generate, exchange and consume data. Depending on the environment, it can support:
Real-Time Data Integration
Connect data from multiple systems and deliver it to downstream applications as it is generated. This can support environments where current usage, event or operational data needs to be available without relying solely on batch processing.
Data Transformation and Normalization
Transform incoming data into the formats required by downstream systems and normalize information from different sources so it can be processed consistently.
Data Aggregation
Aggregate records and events from multiple sources before delivering them to consuming systems. This can be particularly useful where large volumes of data need to be consolidated or processed before further use.
Usage and Billing Mediation
Process usage records before they reach billing, charging or other downstream systems. Depending on the environment, this can include usage mediation, billing mediation, CDR processing and usage record processing.
High-Volume Data Processing
Process large volumes of records and events across complex data environments while maintaining the throughput required by operational and downstream applications.
Legacy and Modern System Integration
Connect legacy infrastructure with newer applications, platforms and services, allowing data to move between systems with different interfaces, formats and processing requirements.
Data Routing and Distribution
Route processed data to the appropriate downstream applications, databases, platforms or services based on defined requirements.
What to Look for in a Data Mediation Solution
When evaluating a data mediation solution, buyers should assess whether the platform can support their data sources, processing volumes, integration methods, latency requirements and downstream applications.
Processing Throughput and Latency
Evaluate whether the solution can process the required volume of records and events while maintaining the latency needed for real-time or near-real-time applications.
Transformation and Normalization
Look for capabilities to transform, normalize and standardize data from different sources so it can be consumed consistently by downstream systems.
Source and Destination Connectivity
Consider whether the solution can connect to the databases, applications, network systems, APIs, message queues and other interfaces used across the environment.
Usage and CDR Processing
For telecommunications environments, assess support for usage data processing, CDR processing, usage mediation and billing mediation, including the ability to validate, transform, aggregate and deliver records to downstream systems.
Routing and Distribution
The solution should be able to route processed data to the appropriate applications, databases, platforms or services based on defined business and technical requirements.
Monitoring and Error Handling
Look for operational visibility across data flows, including monitoring, alerts, error handling, exception management and reporting.
Scalability
Assess whether the mediation platform can scale as data volumes, sources, destinations and processing requirements increase.
Legacy and Modern System Integration
Consider whether the solution can connect existing legacy infrastructure with modern applications, cloud platforms and services without requiring extensive changes to either side.
Data Mediation vs. Point-to-Point Integration
Point-to-point integrations can work when only a small number of systems need to exchange data. As the number of sources and destinations increases, however, the number of individual connections can also grow.
A mediation layer provides a centralized point for processing, transforming, normalizing and routing data between systems.
This can make it easier to manage complex integration environments, particularly where data needs to undergo different processing before reaching multiple downstream applications.
|
Approach |
Best suited to |
Consideration |
|---|---|---|
|
Point-to-point integration |
Small numbers of simple connections |
Can become difficult to manage as connections increase |
|
Data mediation |
Complex, high-volume, multi-system environments |
Provides centralized processing and routing |
|
Data mediation + APIs/message queues |
Real-time and event-driven environments |
Supports more flexible data flows |
How Data Mediation Supports Real-Time Data Integration
Real-time integration requires more than simply moving data from one system to another. Data may need to be transformed, normalized, filtered, enriched, aggregated or routed before it can be consumed by another application.
A mediation layer can perform these processing steps as data moves through the environment, helping downstream systems receive data in the format and structure they require.
Data Mediation With Neural Technologies
Neural Technologies provides data mediation capabilities as part of its broader data integration platform, helping organizations collect, process, transform and distribute data across complex technology environments.
The platform supports high-volume data processing and integration across different data sources and systems, with capabilities for real-time processing, data transformation, normalization, aggregation and monitoring.
For telecommunications environments, these capabilities can support usage mediation, billing mediation, CDR processing and network data integration. They can also support broader enterprise requirements where organizations need to integrate data from multiple sources and deliver it to downstream applications in a consistent and usable form.
By providing a mediation layer between data sources and consuming systems, Neural Technologies helps organizations manage complex data flows without requiring every system to use the same format, interface or processing model.
Looking for a data Mediation Solution for high-volume or real-time data integration?
Explore Neural Technologies’ data mediation capabilities to see how the platform can support real-time data processing, transformation, normalization and integration across complex data environments.
Have a specific integration or mediation requirement? Speak to the Neural Technologies team to discuss your requirements.
Frequently Asked Questions (FAQs)
A mediation layer can provide a centralized processing and routing layer between multiple sources and destinations. Instead of creating and maintaining individual integrations for every connection, organizations can manage transformation, normalization and routing through a common mediation environment.
A mediation solution can collect usage records from network and other source systems, validate and transform the data, normalize different formats, aggregate records where required, and deliver the resulting data to billing, charging and other downstream systems. This approach can support usage mediation, billing mediation and CDR processing within a broader telecom data integration environment.
