Skip to content
View Vivian-celine's full-sized avatar

Block or report Vivian-celine

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don't include any personal information such as legal names or email addresses. Markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse

Pinned Loading

  1. E-Commerce-Star-Schema-Data-Warehouse-Power-BI-Analytics E-Commerce-Star-Schema-Data-Warehouse-Power-BI-Analytics Public

    An end-to-end e-commerce data warehouse project built using SQL Server and a Star Schema architecture, integrated with Power BI for interactive business intelligence reporting. The project analyzes…

    TSQL

  2. Global-Developer-Survey-Data-Engineering-BI-Analysis Global-Developer-Survey-Data-Engineering-BI-Analysis Public

    Cleaned and transformed a 100k+ row, 293-column developer survey dataset using Excel Power Query and Python (Pandas). Optimized performance by reshaping multi-select survey responses with melt oper…

    Jupyter Notebook

  3. Invoice-Reconciliation-system Invoice-Reconciliation-system Public

    Automated invoice Reconciliation system processing 500+ transactions using Excel formulas (INDEX/MATCH,XLOOKUP) and VBA macros. Reduces manual reconciliation from 3 hours to 5 minutes (96% time sav…

  4. Olist-E-Commerce-Analytics-End-to-End-Data-Cleaning-Modelling-Business-Intelligence Olist-E-Commerce-Analytics-End-to-End-Data-Cleaning-Modelling-Business-Intelligence Public

    End-to-end e-commerce data cleaning, snowflake schema modelling, orphan row detection, and business intelligence dashboard development using Python and Power BI.

    Jupyter Notebook

  5. Online-retail-RFM-analysis Online-retail-RFM-analysis Public

    RFM-based customer segmentation analysis using Excel and Power Query. Includes data cleaning, scoring, pivot-based segmentation, and marketing strategy recommendations for an online retail dataset.

  6. Titanic-Survival-EDA Titanic-Survival-EDA Public

    Exploratory Data Analysis of the Titanic dataset using Python to uncover key survival patterns based on gender, class, fare, age, and family structure.

    Jupyter Notebook