Before I ventured into this new path, I spent 2 years as a Cleaning Manager and 4 years as a Cleaning Team Leader. Both roles demanded diverse skills that I believe are crucial for my success as a Data Analyst. Here’s a brief look at my responsibilities and what I learned during those years:

• Managing Teams & Operations: As a Cleaning Manager, I was responsible for leading and managing a team of 40 cleaners and 3 team leaders. I scheduled shifts, assigned tasks, and made sure everyone was working efficiently. This helped me develop strong leadership and coordination skills — qualities essential for working in a data-driven team environment.
• Attention to Detail: Whether it was ensuring that cleaning standards were met or dealing with customer complaints, I had to pay close attention to even the smallest details. Data analysis requires a keen eye for detail when interpreting datasets, finding anomalies, or identifying trends.
• Problem-Solving & Decision-Making: Managing day-to-day operations wasn’t without challenges. Unexpected problems require quick, informed decisions. This experience taught me to analyze situations, identify root causes, and implement effective solutions — a skill directly applicable to analyzing data.
• Time and Task Management: With multiple cleaning units to manage and deadlines to meet, I learned to prioritize tasks and manage my time effectively. In data analysis, handling multiple projects and meeting deadlines while maintaining quality are crucial, and my previous roles prepared me for this.
• Communication & Reporting: I often had to communicate with clients, supervisors, and my team to provide updates, resolve issues, or discuss performance improvements. This gave me strong communication and reporting skills, which will be invaluable in presenting data-driven insights and findings to stakeholders.

After 6 years in cleaning management, I decided it was time to shift gears. I’ve always been passionate about understanding how things work, finding patterns, and driving improvements. The world of data analysis felt like the perfect next step.

To bridge this gap, I enrolled in a Skill BootCamp for Data Analysis. During this intensive course, I’m learning key skills such as:

• Data Fundamentals: What data is. The importance of data analysis and finding out the story of the data. Learning about data security and GDPR.
• Data Cleaning & Transformation: Just as I focused on keeping operations running smoothly and efficiently, data analysis requires cleaning and preparing raw data to uncover insights.
• Data Visualization: Crafting visual representations like charts, graphs, and dashboards to present findings clearly to stakeholders. Power BI, Microsoft Excel, and Google Sheets.
• Statistical Analysis & Python Programming: Using Python and statistical techniques to perform data analysis and predictive modeling.
• SQL & Database Management: Learning how to manage and query data from databases, a critical skill for gathering and processing information.