Traditionally, data quality has been measured independently of the context in which data is produced and used, focusing instead on stored data and collecting metrics on fields or columns. This considerably limits the capability of these systems to provide the high-quality data that is required by data consumers within an organization. This situation has led to considerable debate amongst leaders in the data analytics industry concerning use of existing data quality tools verses building a custom data quality platform.

For over a decade, RS Software has operated and managed the IT system’s infrastructure, application and networks of its leading brands to help them achieve maximum efficiency, security, quality and zero downtime. In parallel, we have provided significant value adds including data quality services for payment domain customers to use to measure and maximize their return on investment. Our experience includes implementing our own data quality platform that we have enriched over time to fit into a variety of client ecosystems. It can also be adapted to fit on existing big data platforms and can incorporate a variety of tools including Abinitio, Trillium, and Talend.

The Data Quality Platform

Our company has extensive experience in implementing our Data Quality Platform (DQP) that is built to be versatile enough to support the needs of payments industry customers. Below are some of the features of this platform:

• Interfaces – Interfaces with enterprise-wide application to extract data quality metrics.
• Components – Components that access data quality metrics that can be used to speed up a variety of on-boarding processes.
• Alerts – Application specific alerts that can be used to prevent the migration of poor quality data to downstream systems.
• Dashboard – Enterprise-relevant dashboard providing data visualization.
• Training – Training to help application owners and management team members leverage DQP.

RS DQ Platform framework

DQ Tools

Apart from our enterprise DQP implementations, RS Software has considerable experience in improving data quality using data quality tools and techniques. Below are some of the solutions implemented by RS Software utilizing these tools and techniques:

• Enterprise Level Monitoring and Cleansing of Referential Data
• Entity Resolution Master Data Management
• Name and Address Standardization Within Enterprise Data Hub
• Enterprise Metadata Management and Lineage
• Implementation of Custom and SAS Data Quality Components

Scope and Scale of DQ tool implementation