Data unification
Raw data from multiple systems was normalized into a consistent schema using SQL views and Laravel-based ETL jobs. Each source was documented with its refresh frequency, reliability score, and known data quality issues.
Mohammed Baobaid
Reporting views that turn fragmented business data into usable decisions.
A decision layer for teams that need clean metrics, traceable sources, and dashboards that explain what changed without extra meetings.
Role
Analytics builder
Outcome
Made performance signals easier to scan, compare, and act on.
Leadership had data scattered across spreadsheets, databases, and third-party tools. Reports were manually compiled, inconsistent in format, and often outdated by the time they reached decision-makers.
I mapped every data source to a unified schema, built automated ETL pipelines using SQL and Laravel scheduled commands, and delivered Power BI dashboards with drill-down capabilities. Executive summaries were designed to answer "what changed and why" at a glance.
Raw data from multiple systems was normalized into a consistent schema using SQL views and Laravel-based ETL jobs. Each source was documented with its refresh frequency, reliability score, and known data quality issues.
Every dashboard follows a three-layer pattern: executive summary at the top (what changed), trend context in the middle (how it compares), and operational detail at the bottom (where to dig deeper). This structure lets different stakeholders get value at their preferred depth.
Laravel scheduled commands handle data refresh, validation, and anomaly detection. When a metric moves beyond expected thresholds, the system flags it in the next dashboard refresh so it surfaces naturally in the daily workflow.
I build systems like this for teams that need reliable engineering, clean interfaces, and measurable outcomes.