Topics Covered in this Chapter
- This chapter explains the role of data standards for the success of any DaaS program and provides an overview of how to ensure that the quality of data published by enterprise data services is suitable and fit for public consumption.
- The significance of data profiling as a foundational process for successful DaaS quality programs are explained. As such, this chapter provides details on how use of data discovery and profiling tools can be useful for organizations in assessing the quality of data received from incoming data sources.
- The significance of data standards is also discussed as well as how these standards can be practically implemented by a data provider in real life.
- Finally, the benefits of using a metrics-driven approach to improve the quality of a data service are explained.
“It is a capital mistake to theorize before one has all the data.”
—Sherlock Holmes (Sir Arthur Conan Doyle)
As discussed, introducing Data as a Service (DaaS) can act as a key enabler for sharing and reusing information across an organization by providing a consistent set of enterprise data services both to external consumers and internal service subscribers. This requires adopting data standards that can support the secure exchange of data across diverse platforms, databases, files, and other unstructured data formats.
Effective data sharing and reuse can be achieved in organizations by combining reusable data services ...