Data Quality and Profiling
Segue’s experience in Enterprise data management for enterprise systems provides us with a solid understanding of the many inherent challenges of large, shared information sources. Numerous stakeholders and players, massive amounts of data, poor data quality, low data interoperability, interface issues, challenging requirements, and senior-level interest in meeting aggressive schedules all impact the goal of combining data into a reliable information source. To cut through these hurdles, Segue focuses on the primary goal, releasing data from vertical stovepipes to allow information to flow horizontally through the enterprise. To achieve this, Segue employs a simple four-part approach to data storage solutions– based on LEAN principles:
- VALUE involves identifying authoritative data sources that support user requirements (demand) and ensuring data is fit for use (quality)
- FLOW means data interoperability
- PULL means users can access data anytime/anyplace
- PERFECT refers to continuous improvement of the data flow process