Cross Platform Integration :
As new applications and environments are released in the market , it has become a challenge for organizations to transport mission critical data back and forth various applications and databases. The market requires a true cross platform integrator that can enable data transport between applications and environments, seamlessly and yet simple to use. The most important business rule that is forgotten by many developers and data integrators is the process of how to abstract and conceal intricate information of each platform that participates in data integration away from the user. Many products that promises cross platform data integration, might not truly deliver the complex business requirements set forth by the organization, instead, they tend to carry the obscure information that is tightly coupled with an application, database or a platform from the start to the end of the data integration lifecycle.
Moving to DIAL:
DIAL is a true cross platform integrator, The primary element that is absolutely different and unique in DIAL compared to any other data manipulation products , is its underlying architecture. DIAL is an innovation in Data integration, the moment users start to experience the process defined by DIAL they will feel the uniqueness and seamlessness in the way various components go hand in hand to accomplish their data automation requirements.
Business Analysts , Developers, and Product Architects over the past 2 decades have been hard coding the key components that play an important role in Data Integration, and as information grows and as new applications start to participate in data integration, there is a huge demand for these key component to being loosely coupled (not hard coded) so that the organization's data integration process and requirements can be reused, but since the original / underlying architecture is tightly coupled the developers end up building features and functionalities on top of the original delinquent design. This, in turn, makes the organizations, To buy expensive licenses at the same time hire developers and architects to write & keep customizing scripts that can run in parallel to achieve what they want.
The traditional architecture followed by many developers and products.
Issues with the current architecture used in data integration
- The Table Definitions & relationships are tightly coupled with the underlying connection (adapter)
- The Workflow from the start to the end of the data integration cycle always carries the identity of a table / dataset referencing them with their respective connection or source type.
- Mapping of data to complete the integration requirement is tightly coupled with the source type
- The Functions are hard coded.
- Business logics and rules are always built on the source and destination type of the data.
- Integration of 1:N (One to Many) is complicated and in practice leads to too many errors when deployed and executed
- SaaS integration with databases is hard to design and implement and is never foolproof.
- Reusing the existing data integration design and workflow is practically not feasible.
The main problem more than anything is the time that it takes to prepare and implement the same redundant business processes over and over again without reusing it.
The Distinction - DIAL Architecture