GIS Specialist & Data Analyst well versed in SQL, Python, Tableau, Power BI, ArcGIS, QGIS@sefabckn
This project demonstrates a comprehensive data warehousing and analytics solution, from building a data warehouse to generating actionable insights. Designed as a portfolio project, it highlights industry best practices in data engineering and analytics.
This SQL script performs Exploratory Data Analysis (EDA) on the Gold Layer of the Data Warehouse built using SQL Server and Medallion Architecture (Bronze → Silver → Gold).
This project focuses on analyzing and predicting customer churn in the telecom industry using Python and machine learning. By working with a real-world dataset, I explored customer behavior through extensive exploratory data analysis (EDA) and visualizations to uncover patterns linked to customer attrition. Key features such as contract type, monthly charges, tenure, and service subscriptions were analyzed to identify their impact on churn.
Covid 19 Death Cases, Infected numbers and which location has the more and least amount of Infected people. I used SQL queries to show the total situation of Covid 19
Scrapping data from Amazon by using BeautifulSoup library of Python The code scrapes product details (title and price) from an Amazon page, logs the data to a CSV file daily, and optionally sends an email alert if the price drops below a specified threshold.
Batman province in the Southeastern Anatolia region close to the city centre.1/100000 scale I46, I47, M46 and M47 sheets used as a base map. After the sheets are merged and obtained as a single raster data then with the help of the Georefencing menu of the ArMap software by defining control points at grid points. Affin transformed, error value tolerances under the UTM 6⁰ projection. Project in UTM 6⁰ Projection It was studied in WGS84 datum and 37th zone. The project area covers the Batman province border.
This project focuses on the data cleaning process of layoff data from 2020 to 2023. The cleaned data is visualized using Power BI to provide insights into trends and patterns, such as the industries most affected by layoffs, the geographical distribution of layoffs, and the timeline of layoff events. These insights help identify key factors contributing to workforce reductions and inform strategies for mitigating future layoffs.
This project involves the design and implementation of a relational database system for a real estate agency operating across multiple cities and countries. The system effectively stores, manages, and analyzes data related to properties, locations, prices, availability statuses, and sales team transactions. Key features include tracking property listings (size, location, rooms), managing multiple office operations, monitoring property status, recording pricing history, assigning salespersons, and generating analytical reports using aggregate functions for business insights and performance evaluation.