Phanice

• Conducting Iris data exploratory analysis to understand the dataset.
• Developing Power BI dashboards to visualize superstore performance data, including sales and profit.
• Analyzing data using Python based on project requirements.

Utilized Microsoft Excel and SPSS to analyze data and identify trends and patterns that drive strategic decision-making.
Created data visualizations and reports using Power BI to communicate key findings effectively to technical and non-technical stakeholders.
Interpreted findings from data analysis and presented them in clear and concise graphs.
Utilized automated tools to extract data from various sources and performed data cleaning to remove corrupted data and fix coding errors.
Collaborated with a cross-functional team to understand data requirements and translate them into data-driven solutions.
Developed and maintained databases to ensure easy data retrieval.
Contributed to developing data governance strategies to ensure data consistency, accuracy, and security.
Designed visually appealing dashboards in Power BI.
Managed to enhance data interpretation efficiency by 25%.
Attained a 98% accuracy rate in predicting students' class attendance using the linear regression model.

Assisted with research projects and analysis of livestock production data.
Planned and initiated research and monitored regulatory and subject binders.
Organized, implemented, and administered data collection and analysis systems.
Performed site-monitoring visits to ensure adherence to clinical research protocols and good clinical practice guidelines.
Collected various forms of data, like crop diseases and livestock production.
Analyzed data, which guided the firm in making timely and factual decisions.
Ensured the safety of the unit by close monitoring of surveillance and personnel.
Developed expertise in research methods, data collection, and cleaning.
Use Analytics tools to turn data into actionable insights for demand forecasting, data management, research management, and trend analysis.

Conducting Iris data exploratory analysis to understand the dataset.
Developing Power BI dashboards to visualize superstore performance data, including sales and profit.
Analyzing data using Python based on project requirements.
Use analytics tools to turn data into actionable insights for demand forecasting, price management, inventory management, and market trend analysis.