Data Analyst

hace 1 semana

Tratamiento De Aguas Goloso El, España Fresenius Medical Care A tiempo completo

**Dashboard Design and Development**:

- Create and maintain interactive, user-friendly dashboards using Streamlit, Tableau, or Power BI tools.
- Collaborate with stakeholders to understand their requirements and translate them into effective visualizations.

**Data Visualization Best Practices**:

- Implement best practices for data visualization, ensuring clarity, accuracy, and accessibility for a diverse audience.

**Statistical Analysis**:

- Utilize statistical models to validate hypotheses and support decision-making processes.

**Data Exploration and Insights**:

- Conduct exploratory data analysis to uncover trends, patterns, correlations, and outliers.
- Provide actionable and strategic insights by analyzing complex datasets through compelling visualizations and narratives.

**KPI Development and Monitoring**:

- Collaborate with business stakeholders to define and establish key performance indicators (KPIs) relevant to data analysis goals.
- Develop mechanisms for ongoing monitoring and reporting on KPI performance.

**Data Cleaning and Preprocessing**:

- Clean and preprocess raw data to ensure accuracy and consistency in visualizations.
- Collaborate with data engineers to establish efficient data pipelines for visualization purposes.

**SQL for Data Access**:

- Write and optimize SQL queries to extract and manipulate data from databases.
- Ensure efficient data retrieval for analysis and visualization purposes.

**Collaboration with Data Integration Teams**:

- Work closely with data integration teams to ensure seamless data integration for visualization purposes.
- Provide input on data requirements for integration processes.

**Infrastructure and Azure Cloud Services**:

- Leverage Azure cloud services for data storage, processing, and analysis.
- Collaborate with the infrastructure team to implement and optimize cloud-based solutions, ensuring scalability and efficiency.
- Provide input on infrastructure requirements for data storage, processing, and analysis.

**Quality Assurance for Visualizations**:

- Conduct thorough testing of visualizations to ensure accuracy, completeness, and responsiveness.
- Implement quality assurance processes for visual elements and data integrity.

**Documentation and Knowledge Sharing of Visualization Processes**:

- Document the process of creating visualizations, including data sources, methodologies, and design choices.
- Maintain an organized repository of visual assets for future reference.

**Continuous Improvement, learning, and professional development**:

- Stay informed about advancements in data visualization tools and techniques.
- Continuously seek opportunities to enhance and optimize existing visualizations for improved decision-making.
- Stay updated on industry trends, new tools, and methodologies in data analysis.
- Participate in training programs and encourage a culture of continuous learning within the data team.

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