Data Quality & Address Validation

• Platform as a Service (PaaS) - Data Management Platforms

• Data Science Services
• System Integration

The logistics company was facing a challenge with the expansion to new territories which meant more address data that was notoriously difficult to validate and interpret. Particularly in Emerging Markets, the company was facing vast regional differences in both address structure and rules, and had to contend with the availability of tools and databases, or lack thereof, to process them. The company had assembled a data quality team tasked with manually verifying and cleaning the data, working shifts to meet overnight delivery deadlines. However, the ever-growing need for manpower to process more data with a quick turnaround became a bottleneck that blocked the company’s ability to expand further.

The customer is a fast-growing logistics company that was facing a challenge with data quality, particularly with address validation and cleansing. The company was expanding to new territories which meant dealing with more address data that was notoriously difficult to validate and interpret. The company had assembled a data quality team tasked with manually verifying and cleaning the data, working shifts to meet overnight delivery deadlines. However, the ever-growing need for manpower to process more data with a quick turnaround became a bottleneck that blocked the company’s ability to expand further.

CloverDX provided a data quality solution to replace a team of 30+ workers dedicated to manual address validation and cleansing. The solution was an automated platform that allowed the company to scale throughput by several orders of magnitude. The solution validated, geo-located, and repaired 80 to 90% of addresses instantly, while also providing self-learning tools that helped the client’s team manually work through exceptions quickly and efficiently. The solution was delivered as a framework that can be expanded to support additional countries with their specific validation rules and external lookup and geo-coding services. The framework consists of numerous CloverDX transformations and automation jobflows that form the core rule engine. Rules can be easily added or modified without the need for coding.

• Removed a hard-to-scale bottleneck of 30+ workers needed for manual address validation
• Implemented a scalable address validation and cleansing framework customizable to country-specific rules for future expansion to new markets
• Minimized human interactions down to 1/10th – a figure that’s still decreasing with the system’s self-learning capability

• The solution validates, geo-locates, and repairs 80 to 90% of addresses instantly
• Minimized human interactions down to 1/10th