An enterprise data architecture defines how data is acquired and organized within the organization. Some of the key drivers for formulating an enterprise data architecture include:

Fit for purpose

Data is only useful, if it is available in the right form, to the right people, in the right place and at the right time. The problem is – companies dont exactly know what data will be needed by whom, where and when. In such a situation, building a data hub that stores all the data, and building systems, frameworks and policies to make that data available as needed seems to be the only right approach.

Optimization

Building data management solutions is a huge tasks, something that individual businesses cannot afford to do on their own. Hence an enterprise wide initiative in necessary to achieve cost optimization. Applications, frameworks, policies and guiding principles associated with acquiring and managing data should be created centrally, and evangelised across the organization, in order to leverage the true potential of data in the most optimized manner.

Compliance

Data is also a key component for various business compliance initiatives, and data architecture needs to account for the compliance requirements. This may involve preserving of historic data, or timely reporting of data to regulatory authorities. It also involves ensuring data privacy and protection of organization’s confidential data and customer identity data.