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DISCOVER PROJECT

Distriweb Users KPI

From Raw Logs to Real Time Insight Power BI Analytics for Pharmaceutical Platform User Management
A Power BI Business Intelligence internship project connecting to a MariaDB backend to track user demographics, account status, and login behavior for the Distriweb pharmaceutical platform, covering active/inactive tracking, validation workflows, and lab/country engagement analytics

POWER BI - MARIADB - ODBC - DAX - MYPHPADMIN - SQL - KPI DASHBOARDS - DATA MODELING

Project Overview

The objective was to design an operational KPI tool that lets administrators monitor user engagement, enforce security policies (password changes every 4 months, deactivation after 4 months of inactivity), and validate new account requests without manual database queries. The work required setting up the full data pipeline first connecting Power BI to the MariaDB backend before any visualization could be modeled.

Built a multi-page Power BI dashboard connecting user, login, request, and lab/country data into a unified model to monitor account status, login history, and organizational engagement across Tridem Pharma's global operations. The report tracked 110 active and 150 inactive users, with color-coded status indicators (green/orange/red) giving administrators instant visibility into account health and automated validation messaging for new requests. Additional drillthrough pages covered per-user login history, lab-level connection counts, and country/lab mapping, with Tridem Pharma itself emerging as the top-engaged account at 24.9K logins

The dashboard was built around translating raw relational data into intuitive, self-explanatory visuals: a search and filter user table, conditional color coding for account risk, and drillthrough pages so any KPI (logins, validations, lab counts) could be explored top-down or bottom-up. Rather than static reporting, the emphasis was on interactive, real-time administrative decision support, enabling operational teams across global departments to spot inactive users, refused requests, and under-engaged labs at a glance

The dashboard was built around translating raw relational data into intuitive, self-explanatory visuals: a search and filter user table, conditional color coding for account risk, and drillthrough pages so any KPI (logins, validations, lab counts) could be explored top-down or bottom-up. Rather than static reporting, the emphasis was on interactive, real-time administrative decision support, enabling operational teams across global departments to spot inactive users, refused requests, and under-engaged labs at a glance

SUCCESS

SUCCESS

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SATISFACTION

SATISFACTION

90
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