The Data Interoperability Lectures define the overall architecture and process of achieving interoperable data environments.
Most organizations have implemented a number of different databases via one or more routes: ERP packages, custom development, evolved legacy non-database access, and data warehouses. Rarely do all of these databases employ enterprise standards with an overarching data architecture and model which utilizes standardized enterprise-level data elements. Lacking these benefits, the results often are stovepipe solutions with a lack of horizontal integration, resulting in an excessive use of extract-transform-load tools.
These Data Interoperability Lectures are geared to provide guidance and an overall framework for engineering interoperable data environments, whether these are created through forward-engineering, or in most cases, reverse-engineering.
The key topics presented in the lectures include: the goal of integrated database, data architecture classes, data management goals, data interoperability architecture components, and challenges to be met along the way.
Also included in the lectures is material on frameworks, the need for cross-functional communities of interest, a strategy to build a business rational information systems plan, an 18 step process model, and then the demonstration of the two most commonly seen strategies: forward and reverse engineering.
These topics are further detailed in the Data Interoperability Lectures topical outline.