By Pushpak Sarkar
Data as a Service indicates how agencies can leverage “data as a provider” via delivering real-life case stories at the quite a few and leading edge architectures and similar patterns
- Comprehensive method of introducing facts as a carrier in any organization
- A reusable and versatile SOA established structure framework
- Roadmap to introduce ‘big information as a carrier’ for capability clients
- Presents an intensive description of every part within the DaaS reference structure so readers can enforce solutions
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Extra resources for Data as a service : a framework for providing reusable enterprise data services
So far, we have seen many benefits from adopting DaaS frameworks. However, there are some limitations that readers also need to take into consideration. r Because DaaS applications are hosted in the Cloud, far away from the application users, this could introduce latency into the environment. At times, the DaaS model is not suitable for applications that demand response times in the milliseconds (unless aided by performance improvement tools, which are discussed in Chapter 13). r When data is being stored on the DaaS vendor’s servers, data security could become a major issue faced by the organization.
For many years, companies such as Amazon have been leading the way in this area. For example, many of Amazon’s products are sourced from suppliers in other countries and sold to online customers in western countries. So Amazon keeps its own product catalog updated on a real-time basis for the customer to access. , are available to the customer via EDS. Additionally, internal projects can also save time, effort, and money by reusing the EDS across different departments in the organization. Thus, in terms of hard dollar benefits and savings, investments in EDS, and other common components can be justified both from the strategic and project-based perspectives.
Data publication) and data accessibility. The strategy should also ensure strict compliance to data security and privacy standards. In fact, any data that is published over a data service has to be “fit for use” by a broad cross section of external customers, enterprise users, and downstream applications. Having a data strategy that prioritizes these underlying factors will be essential in terms of supporting complexities of system interoperability and data exchange in a service-enabled environment.
Data as a service : a framework for providing reusable enterprise data services by Pushpak Sarkar