Another pillar that supports data-centric architecture is agility. AI technologies require real-time access to data to provide agile responses to users.
In this regard, unified infrastructure and enhanced processing power must enable instant access to data by applications. This ensures agility for organizations to respond appropriately to the speed of the digital age.
Accessibility
Data-centric architecture must be democratic . Anyone, regardless of spain phone number list their experience or technical knowledge, must have access to data to make the best decisions and optimize the quality and speed of processes.
Therefore, this model must also prioritize user accessibility, considering the different levels of access permissions.
Implementation would be much easier if the organization were able to become data-centric from the start of its operations. However, the reality is that companies are already dealing with multiple applications and tools, have already gone through mergers and acquisitions, and are faced with a confusing data landscape.
For this reason, implementing data-centric architecture requires a more complex process to be implemented. Let's now look at what your company should do:
How to implement data-centric architecture?
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rubinaruma
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