nyobel/HIV-Indicators-Kenya

# 📊 HIV Indicators Kenya Dashboard An interactive Power BI dashboard exploring HIV trends in Kenya from **1990 to 2024**, with a focus on transforming data into actionable insights. > **A report should tell a story - with or without the analyst being present.** That principle guided every stage of this project, from data preparation to dashboard design. Rather than relying on presentations to explain findings, the report embeds concise insights directly into each page, enabling users to understand key trends independently. --- ## 🎯 Project Objectives - Analyze long-term HIV trends in Kenya. - Build an executive-friendly dashboard that communicates insights clearly. - Transform raw data into meaningful visual narratives. - Apply best practices in data cleaning, modeling, and dashboard design. --- ## 📂 Dashboard Pages ### Executive Overview Provides a high-level summary of Kenya's HIV landscape through: - KPI cards with year-over-year comparisons. - National HIV trends. - Executive insights. ### Prevalence & Incidence Explores: - HIV prevalence among adults aged 15–49. - HIV incidence trends. - HIV incidence by sex. ### Treatment & PMTCT Analyzes: - ART coverage. - Children requiring and receiving ART. - Prevention of Mother-to-Child Transmission (PMTCT) trends. ### Testing & Diagnosis Examines: - HIV testing facilities. - HIV diagnosis indicators. - Testing and diagnosis trends over time. --- ## 🧹 Data Preparation ### Microsoft Excel The dataset underwent validation and cleaning before being imported into Power BI. Tasks performed included: - Removing unnecessary columns. - Removing duplicate records. - Standardizing indicator names and categorical values. - Handling missing values (`NULL`). - Validating numeric values. - Verifying consistency across related columns. - Organizing indicators into logical analytical groups. ### Power Query Additional transformations included: - Validating data types. - Trimming and cleaning text fields. - Pr …