Neta Data Platform: Unlocking the Value of Meter-to-Cash Data

An integrated data model and new access methods to leverage Neta data for reporting, analytics, and integration with the customer's data ecosystem.

Meter-to-Cash processes generate large volumes of information related to customers, contracts, service supplies, meter readings, consumption, invoices, payments, collections, and operational activities.

When this information is distributed across different applications and functional domains, creating KPIs and generating meaningful business insights requires data extraction, reconciliation, and other time-consuming data preparation activities.

Neta Data Platform provides an integrated data model that organizes and makes accessible the information generated by Neta processes, creating a common foundation for reporting, analytics, and integration with the customer’s data ecosystem.

A Common Data Model for Meter-to-Cash

At the core of the Data Platform is a model that organizes information generated by Meter-to-Cash processes into functional domains: customers and contracts, billing, credit management, metering and consumption, CRM, and workflow processes.

The goal is to provide data organized within a common structure, eliminating the need to reconstruct information from individual applications or processes.

On this foundation, customers can develop dashboards, KPIs, and cross-functional analyses using their preferred Business Intelligence and Analytics tools.

From Static Reporting to Flexible and Autonomous Data Access

Neta Data Platform complements the operational reporting capabilities already available within Neta applications by offering data access methods that allow customers to use information directly within their own analytics ecosystem.

Two primary approaches are available.

Data Product Sharing

Organizations with their own data platform can receive Neta data models and related entities through Delta Sharing and Open Sharing protocols.

This enables customers to use Neta data within their analytics ecosystem, combine it with other enterprise data sources, and independently build analyses and services directly on their infrastructure.

Managed BI Access

For customers who wish to use Business Intelligence tools without maintaining their own data platform, Neta Data Platform provides access through a SQL Warehouse.

Customers can query the data model and use the results within their preferred BI tools, maintaining full autonomy in building dashboards and analyses without the burden of managing a dedicated analytics infrastructure.

While these two approaches address different needs, they share the same objective: making Neta data accessible in a flexible and autonomous way.

From Data to Business Use Cases

The availability of a unified data model enables cross-domain analysis, allowing organizations to correlate consumption and revenue, reading quality and source information with billing outcomes, customer profiles and lifecycle stages with credit and payments, or invoices, overdue balances, and collections.

Dashboards and KPIs are therefore not limited to predefined reports. Customers can use the data model as a foundation to build analyses tailored to their operational and strategic requirements.

A Data Foundation Ready for Advanced AI and Analytics

The information assets available within the Data Platform can also support more advanced Analytics, Machine Learning, and AI use cases.

Depending on available data and business needs, organizations can develop scenarios such as customer segmentation, consumption forecasting, churn risk analysis, credit risk assessment, collection forecasting, and other descriptive and predictive models based on Meter-to-Cash data.

Turning Data into Value

Neta Data Platform eliminates data fragmentation across applications and processes by providing a common data model and access methods adaptable to the customer's technology ecosystem.

Information can therefore be used to create dashboards and analyses, feed enterprise data platforms, integrate external systems, and support new analytics, AI, and automation use cases.

Discover how to unlock the value of the data already available in your systems and identify new use cases to bring into your organization.