The New York times reported that data scientists spend significant time transforming raw data so that it can be analyzed by algorithms implemented in software. A number of startups are focusing on this problem with tools that work with raw data.
What can enterprise and solution architects do make data ready for automated analysis so that organizations can react more quickly to the signals they uncover in data?
Post your response here.
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EA architects must do their job, that is, EA and as such IA. Then implement the harmonisation roadmap to organise data to achieve single version of truth…
Information Architecture (IA) is part of and aligned to EA in that it follows similar structures. IA ensures that information is structured and aligned to enterprise entities, normalised and linked across the enterprise. The Data Architecture illustrates the next level of detail.
Hence IA and DA ensures that data formats are known and harmonised, information is easily extracted without compatibility issues and maybe processed in batch and/or real time for whatever purpose.
And indeed, a data mining and BI view of EA should be provided for processing use.
Grigorlu, very good answer. Information architecture is definitely part of enterprise architecture. Do you, or any other EAPJ readers, know of an enterprise architect that has recently planned for target state in which large volumes of data in varying or uncertain formats must be continuously analyzed? It seems like this would require a mix of business process and supporting software applications. It would be great to hear from someone who has planned for this type of situation.