Legacy data warehouse architecture inhibits visibility into schema, data types, and movement and transformation processes. This leaves data warehouse teams in the dark when it comes to planning and redesigning a data warehouse on a modern platform. Data modeling and data intelligence tools from Quest automate the use of metadata to document the legacy system and inform the design of the new system.
Organizations migrating to a modern data warehouse inevitably face increased costs, longer timelines and decreased accuracy if the work is done manually. Automating processes like redesigning schema, replicating data and verifying data accuracy can reduce costs while also enabling high availability, disaster recovery and workload distribution. Quest tools work across database platforms to ensure data is always available when and where it is needed.
The traditional disconnect between IT teams and business users has resulted in a lack of visibility into the rules and policies governing data classification, usage and retention of data warehouse assets. This low level of stakeholder data literacy can affect compliance as well as reduce the overall quality of enterprise data. Data governance tools from Quest ensure all teams understand data usage policies along with the business purpose of stored data.