KEY POINTS TO CONSIDER
SCALABILITY, RE-USABILITY AND UNIFORMITY
Data Services in a DaaS environment is intender to serve multiple projects and use cases, and the value of the data formats and data services should be designed to both outlast and exceed the value of the particular systems, have a scalable and adaptive design and should be compatible with all data and analytics systems of the business
Security, in a data-as-a-service deployment must be uniform and ubiquitous. FOr businesses with different security models across different data assets face this barrier to adoption. Different entities will not share data without built-in security, and extensive data without controls becomes a privacy and compliance risk.
DATA VIRTUALIZATION AND ABSTRACTION
Data abstraction, is the handling of data in meaningful ways, or the ability to re‐ represent the data using structures that are more meaningful to the users of the data and the AI/ML deployment. Data virtualization is used to integrate data from multiple disparate sources that may exist within the enterprises, outside the enterprise, or cloud computing‐based, to provide a unified virtualized view of the data for use by any number of data consumers.
CLOUD COMPUTING MODEL
With the DaaS Cloud computing model, data is readily accessible through a Cloud-based platform. Simply put, DaaS is most optimum path to accessing business-critical data within an existing datacenter. Within the DaaS environment information can be delivered to a user regardless of organizational or geographical barriers. Some of the most common business applications powered by DaaS technology includes Customer Resource Management (CRM) and Enterprise Resource Planning (ERP) applications.