Kartheek Naik Mood

Certified Power BI and Data Analyst with extensive experience in building dynamic dashboards, maintaining scalable data pipelines, and implementing robust data governance frameworks. Proficient in Power BI, Python, SQL, and ETL processes, with a proven track record of improving data accessibility, reducing manual processes, and optimizing decision-making. Skilled in API integration, cloud data platforms, and automation tools, delivering innovative solutions for real-time analytics.

Dynamic Power BI Reporting and Excel Automation

• Objective: Designed and maintained dynamic Power BI reports and Excel automation to streamline data analysis and reduce manual effort.
• Key Activities: Automated workflows with Power Query, DAX, and VBA, reducing manual data entry by 85%. Created Power BI dashboards for CXOs, project managers, and operations teams, offering real-time insights into KPIs and operational performance. Implemented validation processes for data accuracy and ensured seamless connectivity between data sources and Power BI.
  
• Maintenance: Continuously monitored data pipelines and dashboard performance, ensuring uninterrupted reporting and data integrity.

Skylink API to MongoDB and Power BI Integration

• Objective: Developed a robust pipeline to ingest data from Skylink API into MongoDB hosted on AWS Cloud, with dynamic reporting in Power BI.
• Key Activities: Validated JSON data submissions to MongoDB, ensuring data accuracy and compliance.
  Monitored pipeline connectivity and optimized data flows to handle large datasets efficiently.
  Built dynamic Power BI reports with advanced DAX and Power Query for real-time analytics, enabling actionable insights for stakeholders.
  
• Maintenance: Regularly updated and optimized API integrations and MongoDB bandwidth usage, ensuring pipeline scalability and reliability.

Server Utilization Pipeline: Local Servers to Power BI

• Objective: Designed and implemented a pipeline to monitor server performance metrics, including CPU, RAM, and storage utilization, across multiple time frames.
• Pipeline Design: Local Servers → API → OneDrive → Power BI Services.
• Key Activities: Automated data extraction using Python scripts and API connectivity to collect server metrics. Created Power BI dashboards with daily, weekly, and monthly performance views for resource monitoring. Improved pipeline efficiency by reducing data latency and enhancing connectivity with Power Query.
  
• Maintenance: Continuously tracked pipeline performance and implemented enhancements to improve data accuracy and reporting efficiency.

Microsoft Power BI Data Analyst Certificate:

• Advanced training in data preparation, modeling, and visualization using Power BI
• .Specialized in DAX, Power Query, and dashboard creation for actionable business insights.