Fatima Iganya Suleiman

I am an experienced Data Analyst & Data Manager with over 3 years of professional expertise in data analysis, data management, and reporting. I specialize in transforming complex data into actionable insights, building efficient data pipelines, and ensuring data integrity for decision-making across different industries.

My work has spanned data analytics, database management, and business intelligence, where I have successfully delivered projects that improved efficiency, enhanced reporting accuracy, and supported strategic planning.

Core Skills & Expertise

Data Analysis & Reporting: Skilled in analyzing structured and unstructured data, identifying trends, and creating meaningful dashboards and visualizations.

Database & Data Management: Proven ability to manage, clean, and optimize large datasets while ensuring data accuracy, security, and compliance.

Business Intelligence (BI): Experience in generating reports, KPIs, and interactive dashboards to support stakeholders in making informed business decisions.

Automation & Efficiency: Developed automated workflows and reporting pipelines to reduce manual effort and improve data accessibility.

Tools & Technologies

Programming & Data Analysis: Python (Pandas, NumPy, Scikit-learn) and R

Data Visualization:  Power BI, Tableau, Matplotlib, Seaborn

Databases & Querying: SQL (MySQL, PostgreSQL, MS SQL Server), Excel (advanced formulas, Power Query, Pivot Tables)

Data Management & Collaboration: MS Access, Google BigQuery, SharePoint, Microsoft 365 Suite

Project & Workflow Tools: Hubstaff, Jira, Trello, Asana

Key Achievements

Delivered end-to-end data management solutions, from data extraction and cleaning to visualization and reporting.

Improved reporting efficiency by automating dashboards in Power BI and Tableau, reducing manual reporting time by 40%.

Managed and optimized large-scale databases, ensuring accuracy and compliance with industry standards.

Collaborated with cross-functional teams to provide data-driven insights, leading to improved operational decisions.

Developed predictive models using machine learning (Python & R) to classify, forecast, and optimize business processes.