VENKATA KRISHNA CHAITANYA MUKIRALA

Project 1:

• Analyzed UK accident, traffic, and weather datasets using Python, SQL, and Power BI to identify patterns, seasonal trends, and risk factors across 200+ districts
• Built analytical models for accident severity, time-based clustering, and correlation analysis to support road-safety planning and government decision-making.
• Developed interactive Power BI dashboards with geospatial heat maps, KPI views, and performance insights used by stakeholders across the UK Department for Transport.
• Conducted statistical analysis to uncover the key contributors to accident frequency, supporting interventions that led to a 15% reduction in incident rates.
• Defined analytical KPIs, improved data quality workflows, and collaborated with policy and operations teams for evidence-based improvements.
• Regularly prepared and delivered data-driven presentations, visual summaries, and reports to internal and external stakeholders.
• Addressed real-time data challenges, rapidly identifying root causes and recommending immediate, actionable solutions to mitigate emerging risks

Project 2: Medical Operations & Patient Appointment Analytics — Healthcare Client (UK)

• Analyzed patient appointment datasets to identify trends in no-shows, cancellations, long wait times, and scheduling inefficiencies.
• Prepared and cleaned operational healthcare data using Python and SQL for accurate KPI reporting.
• Created Power BI dashboards to visualize patient flow, appointment utilization, consultation duration, and operational bottlenecks.
• Provided actionable insights that reduced patient waiting times and improved clinic workflow efficiency.
• Delivered regular analytical updates, reports, and presentations to healthcare operations teams.

• Developed Power BI dashboards tracking network uptime, latency, and packet loss across 1,000+ devices.
• Standardised raw logs into relational SQL models enabling advanced SLA and performance analysis.
• Reduced fault detection time by 40% through predictive anomaly alerts and SLA compliance tracking.
• Delivered actionable insights to network engineering teams, strengthening uptime and reliability metrics.
• Analysed 200K+ customer support tickets using SQL and Python to identify recurring complaint patterns and escalation triggers.
• Developed Power BI dashboards visualising agent performance, average resolution time, and first-call fix rates.
• Improved issue-resolution efficiency by 25% through targeted root-cause analytics and dashboard-driven operational reviews.

• Led a cross-functional analytics initiative as SME to identify and eliminate invalid modem shipments to customers, reducing operational inefficiency and warranty losses.
• Executed Root Cause Analysis (RCA) using Excel, SQL queries, and process-mapping techniques to trace invalid device replacements across multiple telecom regions.
• Implemented data validation rules and anomaly-detection logic that improved product verification accuracy by 65%, saving significant logistics and service costs.
• Developed and automated reporting dashboards using Power BI and Excel VBA, visualizing daily shipment patterns, replacement rates, and quality KPIs.
• Performed keyword analysis on customer feedback and service datasets to identify recurring service issues and improve quality response actions.
• Collaborated with business, QA, and supply chain units to define analytical metrics, automate RCA dashboards, and implement process improvements.
• Recognized by senior management for achieving 99.9% accuracy in data validation and reducing recurring equipment replacement issues.
• Trained and mentored a team of 20+ associates on data quality management, process auditing, and dashboard automation best practices.