Traditional telecom operations are often slow. Engineers spend hours extracting raw data from databases. They copy data into Excel tables manually. I solve this bottleneck by automating RAN diagnostics. I write custom scripts and database pipelines. This helps network operations teams resolve incidents faster.
My automation stack relies on Python and SQL. I also use Power BI and Tableau. I write worst-cell parsers using the Python pandas library. These scripts import raw performance files automatically. They filter out cells that violate KPI thresholds. This reduces data processing time from hours to minutes.
I build automated alert bots to improve team response times. These bots integrate with Slack and Telegram. They query network databases at scheduled intervals. If a metric drops, the bot broadcasts an alert. The alert card lists the cell name and direct links. Engineers get notified of incidents in real time.
I also automate complaint handling workflows. Customer complaints are often complex to debug. My scripts parse incoming tickets. They extract locations and timestamps. Then, they cross-reference them with local cell alarms. This creates a triage card for the engineer, which speeds up ticket resolution.
Finally, I automate executive reporting pipelines. I write Python scripts to generate polished Excel reports. These scripts calculate metrics and highlight anomalies automatically. This eliminates manual typing errors. My dashboard designs give managers a real-time view of live network trends.