Fallacies of Enterprise Information Management (part deux)…

With some hearty comments from Tom Maguire, I’ve been forced to adjust some of these fallacies:
1. Data quality is perfect – data is correct, complete and coherent across all enterprise contexts
People will remediate bad data – if inaccuracies are found (contrary to the axiom above) users will willingly and proactively make changes, and all users will agree with those changes
2. Relationships are Known – The linkages between data entities are well known, hierarchical, navigable and everlasting
3. There is a singular master model that is explicitly and consistently factorable for all enterprise uses
One dictionary – There is a consistent dictionary with well agreed and complete set of meta-data supporting the modeled domain
Static model – The model is complete, and no changes will ever be necessary
4. Expectation of XA/2Phase Transactionality – The data exchanges will be ACIDly transactional, and based upon XA/2-phase transactional mechanisms
– Transactions complete in a timely fashion and are not affected by Deutsch’s fallacies
6. Idempotent Data – There is one master copy of enterprise data, and application specific “caches” are always synchronized and consistent
Working currently on more consistent “information exchanges” these fallacies have been driving some specific architectural artifacts, including:
– the need for appropriately targeted abstractions providing consistent to/from canonical forms,
– the need to support similar meta data/policy models and transformations in support of context bridges and securitization
– support for multi-master synchronization
– needs for distributed model governance, non-destructive model mutation and potentially late-modeled forms
(though OWL/RDF brings some new challenges in transactional systems wrt. transitive closure)

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