Data as a service : a framework for providing reusable by Pushpak Sarkar

By Pushpak Sarkar

Data as a Service indicates how companies can leverage “data as a provider” by means of delivering real-life case experiences at the numerous and leading edge architectures and comparable patterns 

  • Comprehensive method of introducing facts as a provider in any organization
  • A reusable and versatile SOA dependent structure framework
  • Roadmap to introduce ‘big info as a carrier’ for capability clients
  • Presents a radical description of every part within the DaaS reference structure so readers can enforce solutions

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Extra info for Data as a service : a framework for providing reusable enterprise data services

Sample text

The DaaS framework can fundamentally transform an organization to a service-driven IT delivery model by utilizing reusable data services that facilitate information sharing and distribution with their customers. Chapter 1 also discussed how many organizations can generate business revenues by providing data as a service to their clients through fee-based subscriptions. However, in addition to helping monetize an organization’s data assets, the DaaS framework can also significantly enhance reuse and exchange of enterprise data across large organizations internally, by distributing data to subscribers across the enterprise with the use of Enterprise Data Services (EDS).

Reusability over rework: The underlying foundation of DaaS is typically based on the concept of service reuse, enabling users to interact with their business using common reusable services over the web, the Cloud, and related technology. The reuse and flexibility associated with the Data Service components make it easier to leverage by businesses or by operational processes in an organization. Business services can be deployed as customized, functional modules of software stored in a centralized service repository, which can be run in a network.

18 Chapter 1 Introduction to DaaS r Data type-based model This pricing model separates the DaaS pricing tiers by data type or attribute. This is a fine-grained model under which data can be sliced or diced, depending on the complexity of the customer’s data request. However, this is a complex model to administer, but may be ideal for certain sectors. An example is a mapping service that offers the geographic coordinates and zip codes of the neighborhoods in a city or town. However, if subscribers need additional details, then they can request more attributes such as school or post office locations, which are sold for an additional charge.

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