Aspiring Data Analyst | Data Engineering Enthusiast
Final-year Bachelor of Science in Information Technology student with a strong interest in data analytics, data engineering, and business intelligence. Experienced in collecting, cleaning, transforming, and analysing large datasets to generate meaningful insights. Skilled in SQL, Python, Power BI, ETL processes, and real-time data analysis, with a passion for building data-driven solutions that support informed decision-making.
- Programming: Python, SQL
- Data Analysis: Pandas, NumPy
- Data Visualisation: Power BI, Tableau, Matplotlib
- Databases: Microsoft SQL Server, MySQL
- Data Engineering: ETL (Extract, Transform, Load), Data Cleaning
- Big Data: Apache Spark (basic knowledge), Big Data concepts
- Real-Time Analytics: APIs, SQL, Python, Power BI dashboards
- Performed comprehensive data cleaning by removing duplicate records, handling missing values, correcting inconsistencies, and standardising data formats to improve data quality.
- Implemented ETL (Extract, Transform, Load) processes by extracting data from multiple sources, transforming it into a consistent structure, and loading it into a relational database for analysis.
- Analysed large datasets to identify trends, patterns, and business insights that supported data-driven decision-making.
- Developed SQL queries to retrieve, filter, aggregate, and analyse data efficiently.
- Created interactive dashboards in Power BI to visualise key performance indicators (KPIs) and business metrics.
- Integrated live data using APIs to enable real-time data collection.
- Processed and analysed incoming data using Python and SQL to generate timely insights.
- Designed Power BI dashboards that refreshed automatically to display current trends and performance metrics.
- Monitored live data streams to detect anomalies and support operational decision-making.
- Applied analytical techniques to improve reporting accuracy and data reliability.
- Built data visualisation dashboards using Power BI and SQL.
- Performed exploratory data analysis (EDA) using Python and Pandas.
- Worked with large datasets to identify trends, generate reports, and support business intelligence tasks.
- Applied data engineering concepts, including ETL workflows and data quality management.
Bachelor of Science in Information Technology (BSc IT) (Final Year)
- Data Cleaning
- ETL Pipelines
- Big Data Fundamentals
- Real-Time Data Analysis
- SQL Query Optimisation
- Data Visualisation
- Business Intelligence
- Problem Solving
- Critical Thinking
- Team Collaboration
Email : moatshemasego73@gmail.com
"Data is not just numbers; it's the story of our decisions and their impacts."