5 Minutes

Power BI Boosts Telecom Network Monitoring Efficiency

John David

A major telecom operator needed to optimize its network performance monitoring system due to inefficiencies in real-time data analysis and predictive maintenance. Sparity stepped into streamline the workflows with Power BI Solution.

Client: Telecom

Services: Power BI

Year: 2024

Client Challenges:

High Data Volume: Processing over 50 million network performance data points daily.

Integration Issues: Data scattered across 10 different systems, including SNMP, Syslog, and proprietary databases.

Real-Time Analysis: Required dashboards to update every 5 minutes to reflect current network status.

Predictive Maintenance: No existing predictive analytics to anticipate network failures.

Slow Reporting: Manual reports took up to 24 hours to compile.

User Access: Over 200 field engineers and managers needed access to actionable insights.

Scalability: Need to support an anticipated 30% data volume increase over the next 2 years.

Sparity Solutions:

Data Integration: Employed Power BI Dataflows to consolidate data from SNMP, Syslog, and other sources into a single dataset.

Real-Time Dashboards: Built real-time dashboards using DirectQuery to ensure updates every 5 minutes.

Predictive Models: Integrated Power BI with Azure Machine Learning to develop predictive models for network failure, analyzing historical data patterns.

Automated Reporting: Created automated reports using Power BI’s subscription feature, reducing report generation time from 24 hours to 2 hours.

Custom Visualizations: Designed custom visualizations using Power BI’s advanced charting features to simplify complex data.

Alerts and Notifications: Set up Power BI Alerts to notify engineers when performance metrics exceed predefined thresholds.

Scalability Planning: Configured the Power BI environment to handle a 30% increase in data volume through scalable Azure resources.

Benefits:

Efficiency Improvement: Reduced network issue detection time by 50% due to real-time dashboards.

Predictive Accuracy: Increased predictive accuracy for network failures by 40%, preventing potential outages.

Reporting Speed: Reduced manual report generation time by 92%, from 24 hours to 2 hours.

User Satisfaction: Enhanced access to insights for 200+ users, improving decision-making efficiency.
Scalability: Supported a 30% data volume increase with no performance degradation.