Solución de virtualización de datos

The contract duration is 12 months from its formalization. There are no specific start or end dates explicitly stated in the document. No extensions (prórrogas) are currently foreseen. The document mentions a "total term" for execution which will be defined at the beginning, but no specific key milestones or partial phases are detailed.

The core scope of work for this tender involves the contracting of a data virtualization solution. This solution aims to integrate and provide unified, secure, and efficient access to information from various systems and data sources. Its purpose is to offer a single layer of access to corporate data, thereby improving interoperability between applications, optimizing information integration processes, reducing technological complexity in data management, and fostering a transversal view of organizational information.

The statement of work summary includes:

• Configuration and integration of the solution with EJIE's corporate systems.
• Provision of e-Learning training services on the product for EJIE personnel and designated users.
• Technical support services, corrective, evolutionary, and adaptive maintenance throughout the contract's duration.
• Updating the solution to ensure its adaptation to regulatory or technological changes.
• Subscription licenses and onboarding as part of the initial installation.
• The solution must automatically create "summaries" based on Machine Learning to accelerate future queries, storing them in cache or external data sources.
• It should use monitoring data to feed a recommendation engine for performance adjustments.
• The solution must have the capability to load summaries directly from the data source to the destination when both are the same database, without passing through the data virtualization layer.
• It must support parallel processing, including native integration with MPP engines for query acceleration in complex big data scenarios, performing parallel operations within the virtualization layer on an MPP cluster (e.g., based on Spark).
• Key functional areas covered include Connectivity – Data Sources, Data Modeling, Data Delivery, Data Catalog, Data Security/Governance, Optimization and Performance, Cache/Selective Replication, Semantics and Data Governance, Batch Processing, Development and Operations (DevOps), Deployments, and Security, Compliance and Certification Requirements.