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Work / Ministerial Analytics — and the Clean Data Beneath It

Ministerial Analytics — and the Clean Data Beneath It

Executive BI + National Data Normalization (ETL) + Software

Client
Factories

Data Engineering + Business Analytics + Software Development + Staff Augmentation

Engagement
Project

Overview

AYNITECH built the analytics system for the Minister of Transportation and delivered a range of related work spanning analytics, implementation, software development and staff augmentation. A representative engagement: defining and documenting the ETL process to clean and normalize the national vehicle-plate database underpinning the Ministry’s Intelligent Transport System — a dataset that, in its raw state, carried tens of thousands of inconsistent vehicle colors, thousands of duplicate makes, and dozens of conflicting identity-document types. AYNITECH profiled and quantified the data-quality problems, designed a normalized target structure with documented transformation rules and scripts, and produced a clean, reusable database.

At a Glance

  • National vehicle-plate database normalized for the Intelligent Transport System

  • Data-quality profiling: 66,000+ vehicle colors, 5,000+ duplicate makes and 50+ conflicting ID-document types reconciled

  • Documented ETL process, transformation rules and scripts

  • Clean, normalized database delivered in the working format and CSV

Why It Matters

Clean data is the foundation of any downstream analytics, AI or supervisory system. The engagement shows data-engineering rigour applied at national scale — and AYNITECH supporting one public-sector client across analytics, software delivery and staff augmentation alike.