When it comes to data technology, are you lost in translation? What's the difference between data federation, virtualization, and data or information-as-a-service? Are columnar databases also relational? Does one use the same or different tools for BAM (business activity monitoring) and for CEP (complex event processing)? These questions are just the tip of the iceberg of a plethora of terms and definitions in the rich and complex world of enterprise data and information. Enterprise application developers, data, and information architects manage multiple challenges on a daily basis already, and the last thing they need to deal with are misunderstandings of the various data technology component definitions.
In a popular Hollywood movie, Lost In Translation, two main characters are "lost" in a foreign culture with humorously obvious incomplete interpretations of instructions they receive from a local movie director, and also "lost" in their personal lives, exaggerated by their displaced location. There probably isn't a single enterprise data/information initiative where stakeholders haven't experienced a similar "Tower of Babel" challenge of misinterpretations, different meanings, and dissimilar understanding of project components and definitions. Alas, unlike Hollywood, business technology (BT) professionals do not have the luxury of humoring such differences — most data/information initiatives are large, complex, and costly, and have a major effect on the business top and bottom lines. Indeed, some of the top reasons business decision-makers whom Forrester surveyed cite for sound data and information strategy and architecture is to make better informed business decisions, improve and optimize business processes, and improve customer interactions and satisfaction. There's no room for misinterpretation in such mission critical objectives. A common language is critical for all stakeholders involved in data related projects.
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