Data Quality

The information that lives in an enterprise database is the lifeblood of most companies. Yet few companies leverage this important asset to operate more efficiently. Fast Iron is unique in its focus on data quality needs of asset-based companies; we understand the challenges associated with leveraging product and customer data across disparate OEM and distributor databases. Transforming data into information requires a dependable and repeatable process. Fast Iron employs advanced algorithms and machine learning to automate data cleansing, minimizing client involvement and accelerating ROI. Fast Iron’s data quality solution is also completely scalable, allowing an organization to leverage clean data across multiple business units and applications.


Fast Iron provides on-demand applications and back office services so clients can harness the power of their business information and begin to experience the benefits of clean data in strategic and operational applications. Fast Iron’s primary focus is normalizing and integrating data from multiple inputs (enterprise legacy, dealer database, UCC, auction results, etc.) and generating output for multiple consumers (CRM, enterprise warehouse, and enterprise facing apps). Fast Iron generated output contains robust content that communicates information with depth and meaning. Utilizing a software-as-service delivery model, implementations are measured in days, rather than the typical months or years.


Fast Iron has successfully integrated multiple and disparate data sources providing tools and information that allow end users to manage down to the lowest level of granularity of an organization’s hierarchy, at the serial-number level. Your company can quickly come to understand how data quality can positively impact the bottom line. Before your business makes the decision to hire additional support staff or fund another costly software initiative, contact us today to hear about our proven and easily deployed solutions.

"Fortune 1000 Enterprises will lose more money in operational inefficiency due to data quality issues than they will spend on Data Warehouse and Customer Relationship Management (CRM) initiatives." -Gartner