### 1.2 Key Data Assets | Table | Role | Rows | % of Total | Size | |-------|------|-----:|----------:|-----:| | 2015 | dimension | 158 | 20.2% | 0.1 MB | | 2016 | dimension | 157 | 20.1% | 0.1 MB | | 2018 | dimension | 156 | 19.9% | 0.0 MB | | 2019 | dimension | 156 | 19.9% | 0.0 MB | | 2017 | dimension | 155 | 19.8% | 0.1 MB | These five tables represent annual snapshots of global happiness metrics, each capturing country-level well-being indicators for a specific year. The remarkably even distribution—ranging from 155 to 158 rows per table—indicates consistent geographic coverage across the five-year observation window, with each table representing roughly 20% of the total 782-row dataset. ### 1.1 Business Data Landscape The **world-happiness** dataset captures longitudinal well-being and quality-of-life metrics across nations from 2015 through 2019. Each of the five dimension tables (2015, 2016, 2017, 2018, 2019) functions as an independent annual survey, storing country-level happiness scores alongside socioeconomic and governance factors that influence citizen satisfaction. This structure reflects a time-series research design where each year's findings stand as a discrete cross-sectional study, enabling year-over-year comparisons of national well-being trends. The dataset supports strategic analysis of how economic prosperity, social support systems, health outcomes, and governance quality correlate with population happiness across different geopolitical contexts. ### 1.3 Data Integration Posture The dataset currently operates as five parallel annual snapshots with zero validated inter-table relationships, meaning cross-year trend analysis requires manual alignment by country identifiers. This siloed structure limits the ability to perform integrated longitudinal queries—tracking how individual nations' happiness trajectories evolved across the five-year period, or identifying which socioeconomic factors showed the strongest correlation with happiness improvements over time. To unlock strategic insights such as "which countries demonstrated the most significant well-being gains between 2015 and 2019" or "how did economic downturns in specific years impact happiness scores," the organization should consider consolidating these annual tables into a unified time-series structure with explicit year and country dimensions, enabling seamless temporal analysis without requiring analysts to manually stitch together five separate datasets.