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Top Requirements
A client is seeking a Data Analyst who performs data collection, analysis, validation and reporting. Designs, tests, and documents processes, SQL queries, and stored procedures. Extracts and analyzes data from various sources, including databases, manual files, and external websites. Responds to data inquiries from various groups within an organization. Creates and publishes regularly scheduled and ad hoc reports. Documents reporting requirements and processes and validates data components as required. Requires experience with relational databases and knowledge of query tools and/or statistical software. Strong analytical and organizational skills are also essential. This is primarily a data inventory accuracy position. They are making sure everything in the environment inventory wise is accurate. They will use python support and automate to ensure reporting and graphs are accurate. They are analyzing data and making sure it’s accurate.
- Data Collection and Preparation: Gather data from various sources, including databases, APIs, and web scraping. Clean and prepare data for analysis, including handling missing values, correcting errors, and removing inconsistencies.
- Data Analysis and Interpretation: Perform statistical analysis and data modeling to identify trends, patterns, and anomalies. Use data analysis techniques to uncover insights and answer specific business questions.
- Data Visualization and Reporting: Create visualizations (charts, graphs, dashboards) to communicate findings to stakeholders. Prepare reports and presentations to present data insights in a clear and concise manner.
- Collaboration and Communication: Work with cross-functional teams to understand their data needs and provide relevant insights. Communicate findings and recommendations to stakeholders in a clear and actionable way.
- Data Quality and Integrity: Ensure the accuracy, consistency, and integrity of data. Develop and maintain data quality standards and processes.
- Problem Solving and Decision Making: Identify areas of concern and suggest solutions based on data analysis. Support data-driven decision-making by providing insights and recommendations
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