Data Quality, Security and Integration
Many organizations begin data management projects to address their large quantity of low quality, and inconsistent, data. Often, because the quality issue is so pressing, the project team focuses their efforts on “cleaning their lake” of bad data. Not much thought is given to what happens once that initial project is over.
What these organizations are missing is that one-time quality projects are ineffective if they not paired with a sustaining process designed to maintain high levels of data quality. The reason is that master data, even the slowly changing dimensions sometimes found in reference data, is not static. Without tools to sustain quality, master data becomes increasingly inconsistent over time.
This is why EBX comes bundled with a wide variety of tools to help your organization maintain data quality. Business rules, computations, and validations can be defined in the data model. As new information enters the platform, the EBX validation engine enforces these rules and provides a real-time validation report that can be used for interactive resolution.
Our multi-factor matching engine provides many algorithms and techniques to find exact and fuzzy candidate matches that can be resolved using human (stewardship) or system/heuristic (survivorship) driven methods.
We create strategies for data integration, data warehouses and data lake. We collaborate with our clients with an iterative approach to constantly improve and track the quality of the data over time.