SQL
Data Analyst
- Produced monthly reports using advanced Excel spreadsheet functions.
- Used statistical methods to analyze data and generate useful business reports.
- Improved decision-making processes with accurate data analysis and visualization techniques.
- Utilized data visualization tools to effectively communicate business insights.
- Created various Excel documents to assist with pulling metrics data and presenting information to stakeholders for concise explanations of best placement for needed resources.
- Collaborated with cross-functional teams to ensure data integrity and accuracy, resulting in better-informed decisions.
- Managed large-scale databases to ensure timely access to critical information for key stakeholders.
- Integrated multiple sources of disparate data into cohesive datasets using ETL processes, improving overall analytic capabilities.
- Developed custom algorithms to optimize data mining, increasing the effectiveness of analytical insights.
- Leveraged advanced analytics to identify trends, enabling proactive business strategy adjustments.
- Enabled more personalized customer experiences by analyzing behavior patterns and preferences.
- Conducted comprehensive data analysis to support strategic planning, leading to more informed decision-making.
- Improved data visualization techniques, making insights more accessible to non-technical stakeholders.
- Collaborated with IT to ensure data security measures were in place, safeguarding sensitive information.
- Created dashboards to monitor and track key performance indicators.
- Developed complex dashboard and reporting tools to track business performance metrics.
- Streamlined data access for remote teams by implementing cloud-based data management solutions.
- Analyzed data to identify root causes of problems and recommend corrective actions.
- Optimized data collection methods to enhance quality and volume of data captured for analysis.
- Utilized data visualization techniques to present and explain complex data sets.
- Assisted with creating data cubes and OLAP models to improve data analysis.
- Optimized data access and storage to improve performance of analytics systems.
- Developed and implemented data governance policies and procedures.
- Developed and maintained data warehouses and data marts to support business operations.
- Supported marketing strategies by providing detailed customer segmentation analysis.
- Deployed predictive analytics models to forecast future trends.
- Designed and developed data pipelines to acquire, clean and process data.