Data architecture is the process of standardizing how organizations collect, store, transform, distribute, and leverage data. The goal is to deliver relevant information to the people who need it in a timely manner and help them understand it. A poorly structured data architecture can make things go wrong. To avoid this, a data structure must have below mentioned characteristics.
You want business users to define requirements with confidence because the professional data architect can bring information together and create solutions to access it in ways that meet business goals.
Built On Shared Data
In this environment, data is not interchangeable between departments or aggregated, but rather is considered a shared asset across the enterprise.
Automated Frictionless Process
Processes that took months to build can now be completed in hours, even minutes, using cloud-based tools.
If a user needs to access different data, automation allows the subject matter professional to quickly design a pipeline to deliver it. The new information can be immediately integrated into the structure.
Powered by Artificial Intelligence
In this way, ML and AI are responsible for identifying data types, analyzing and correcting quality errors, creating structures for incoming data, identifying relationships to obtain new insights, and suggesting data sets and related evaluations.
Must Be Elastic
The cloud is a key ally here, enabling fast and affordable on-demand scalability, allowing system administrators to focus on troubleshooting rather than gauging exact capacity or over-purchasing hardware to keep up with the demand.
We must strive for simplicity in data movement, platforms, assembly frameworks, and analytics software.
Cyber Security First
It is also capable of recognizing potential existing and emerging threats to data security.