What Is Data Architecture as a Service?
Data governance might be hard to execute in a decentralized company. During the Enterprise Data World conference, two primary methodologies were presented: top-down and peer-based.
Peer-based efforts, on the other hand, were shown to be more successful in decentralized companies, while top-down techniques were mostly beneficial in centralized organizations with a specific emphasis.
Data Architecture as a Service (DAaaS)
The authors suggest using a technique called Data Architecture as a Service to handle the issue of data governance in a decentralized organization (DAaaS). The hype around Software as a Service (SaaS) and Platform as a Service (PaaS) is combined with peer-based data architecture ideas in DAaaS. (PaaS).
The authors aim to make it appear as if they are providing their customers with a valuable service while carrying out data architecture chores that are typically carried out via governance.
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DAaaS guarantees to assist application projects with any data-related problems they encounter. To make sure their product is attractive and useful, they provide assistance with data modeling and their data modeling tool. They also assist business data owners by making the process of limiting access to their data easier. They collaborate with implementers to make sure that any applications that could access their data adhere to enterprise-level guidelines for information access.
The argument for DAaS is based on data sharing, and it is given to management as follows: if data is to be shared across applications, the programs that share access must agree on the format and meaning of the shared data. If they disagree, the IT infrastructure will be filled with transformations that are costly to construct, slow down the gathering of correct data, increase the time it takes to distribute updates and new applications, and increase the risk of fragility due to unforeseen side effects. So, the deal presented by DAaaS is simple: through their services, they boost the efficacy of application projects, and the results they deliver increase the efficiency of the whole IT company.
The authors' internal website makes all the developed artifacts accessible to the public to guarantee that they help. This comprises both their high-level enterprise data model and other detailed data models. They have developed a high-level data model with no more than 20 entity types that highlights the crucial linkages that must exist across the organization. They also provide a choice of more complex data models that may be used right away in their own models.
The authors' corporate data model is seen as a dynamic resource that links data throughout the organization. As it is used to organize data exchange, it enjoys the backing of the crowd. Similar to this, they have a number of checklists and guidelines that they see as evolving works and which they have put on their website rather than submitting for official approval or review. They also evolve based on experience and are once again influenced by public knowledge.
“Flexible product with great training and support. The product has been very useful for quickly creating dashboards and data views. Support and training has always been available to us and quick to respond.
- George R, Information Technology Specialist at Sonepar USA
The enterprise data concepts model is a structured glossary that defines the high-level entity types in the business data model as well as a few additional concepts that are vital to the company. It closely resembles the corporate data model. One may argue that the corporate data concepts model should come first. To learn the essential ideas, one might create an enterprise data model if they are a data modeler. Regardless of who came first, structure and meaning are presently used, have developed together, and are even intertwined since they are not fully independent of one another.
Business data owners and software projects are the two types of customers for the authors' DAaaS solution. Business data owners are responsible for maintaining the security and integrity of their data, and the authors assist them in handling requests for data access coming from application projects. The authors additionally handle access control object settings as an extra service to owners of business data since these requests may be somewhat abstract.
For application projects, the authors provide assistance with data models.