Data Collection and Processing • Extract, transform, and load (ETL) data from various sources. • Clean and preprocess data to ensure accuracy and consistency. • Develop scripts and workflows to automate data collection and processing tasks. Data Analysis and Interpretation: • Perform exploratory data analysis to uncover trends, patterns, and anomalies. • Apply statistical and analytical techniques to derive insights from complex datasets. • Conduct hypothesis testing and predictive modeling to support business objectives. Data Visualization and Reporting • Create visually appealing and interactive dashboards, reports, and presentations. • Communicate findings and recommendations to stakeholders using data visualization tools. • Collaborate with cross-functional teams to design and deliver actionable insights. Data Quality Assurance •
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