Revolutionizing Data Management for Render Networks

Streamlining Carbon Credit Management for Agriprove

Industry:
Agriculture
Environmental Services

Client Overview

Render Networks, a global telecommunications company, sought to enhance its data management and customer engagement processes. The goal was to streamline operations, improve customer onboarding and retention, and foster innovation.

Objective

To develop a central event stream to streamline data collection and auditing, reducing reliance on traditional database systems.

Client Mandate

Streamlining Customer Onboarding

Reducing onboarding time from 8+ weeks to quickly unlock platform value for customers.

Integrating Advanced Data Analysis

Eliminating the need for external data analysis tools by enhancing in-platform analytics.

Automating Custom Reporting

Enabling self-service for custom reports to reduce dependency on development teams.

Expanding Reporting Dashboards

Broadening the scope of out-of-the-box dashboards for immediate business insights.

Optimizing Operational Efficiency

Automating processes to cut manual steps and reduce operational costs.

Protecting Revenue

Upgrading analytical features to retain customers and prevent them from turning to third-party solutions.

Speeding Up Pre-Sales

Making pre-sales demos and POCs faster and more efficient to improve customer acquisition.

Encouraging Product Innovation

Utilizing analytics to drive innovation and enhance product offerings for market competitiveness.
Telecommunication
Australia / India
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12-14 months
Kafka
Confluent
 Apache Spark
Python
Sisense
Jupyter notebooks
Terraform automation
React
Databricks
AWS infrastructure
Okta SSO Integration

Proposed Solutions

Debezium for Change Data Capture

Utilized to monitor and capture data changes in the PostgreSQL database, ensuring no event is missed.

Confluent Kafka

Deployed to provide a scalable, fault-tolerant system for event streaming.

Kafka Connect

Bridged Debezium and Kafka, facilitating seamless data movement.

Event Stream Integration

Unified real-time event ingestion from various data sources.

Temporary Storage in Kafka Topics

Ensured reliable event processing and storage.

Event Consumers Development

Created microservices for specific event-processing tasks.

Real-Time Event Processing

Enabled immediate actions and workflows based on event analysis.

Auditing Capabilities

Allowed for retrospective analysis and fulfilled compliance requirements.

Technical Outcome

Render Networks achieved streamlined data collection and auditing, significantly reducing the complexity of their data infrastructure.


The implementation of Debezium, Confluent Kafka and Databricks provided a robust, scalable solution for real-time data management.

Business Outcomes

The new system design facilitated responsive and automated decision-making processes, enhancing overall operational efficiency.

Leveraging customer audit trails, the system ensured precise and accurate billing, eliminating discrepancies and enhancing trust.

Customers experienced immediate value with zero setup delays, thanks to streamlined access to the Data hub.

The integration of instant dashboard access, market-aligned products, and a robust foundation for AI-driven insights significantly accelerated the customer acquisition process.

Providing instant access to actionable insights served as a critical tool for retaining customers by continuously delivering value.

This partnership with Pixid has allowed Render Networks to overcome significant data management challenges, proving the effectiveness of a central event stream system. The project not only optimized data handling but also set a new standard for data infrastructure in rapidly growing companies.

Interested in transforming your data management system?

Contact Pixid today to learn how we can tailor our solutions to meet your unique challenges and drive your business forward.
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