Today every application is cloud driven .We can access data in fraction of seconds right from Software as a Service ,Platform as a Service ,Infrastructure as a service ,Data as a Service We have almost everything coming as a utility service .On the other hand our On-premises data integration technology, with its long release cycles, complex and costly upgrades, and general administration, cannot handle the agility and need for speed in the modern enterprise. We are in a transition Period where every newer software purchases are exclusively Cloud based and there are still lots of investment in legacy on-premises enterprise applications that will take time to migrate. This transition Phase gives the need of new Utility service “Integration Platform as a service (iPaaS)”.
In today’s hybrid, multi-cloud environment, modern data integration technology has to be able to handle both on-premises and cloud-based applications with the same efficiency and ease. This Integration is a bottleneck to achieve the big transition of our entire Cloud regime.
We are in a time where we talk about big data. From 2013 to 2020, the digital universe will grow by a factor of 10 – from 4.4 trillion gigabytes to 44 trillion. It more than doubles every two years. There are a growing number of mobile devices and applications producing data. 20 billion devices are already connected to the Internet and by 2020, this number will grow by 50% to 30 billion connected devices.
Let us see what all things in Integration needs to be Upgraded to achieve:
Evolved API management: APIs permeate the digital world (cloud, mobile, web) and the enterprise application world. They drive new ways to access data, to develop apps and innovate the use of data. The REST and SOAP API services used for integration should be abstract and there should be easy and robust ways of consuming these APIs.
Integration solution should move away from Document-centric solution: The Integration SOAP/REST APIs sends and receives hierarchical documents rather than row sets or compressed message payloads of the previous generation client server-based technologies.
Data integration solutions should provide master data management capabilities.
The data integration technology should not use middleware: Traditional Extract Transform and Load (ETL) technologies that are designed for relational databases normally have middleware based architecture which counteracts and nulls any big data advantages. Modern tools that have an ELT (Extract, Load and then Transform on target/source) based technology are best suited for big data integration.
The Hybrid Cloud solution should be more efficient to handle the Cloud and On-Premise systems at the same speeds.
The Hybrid integration should be more elastic and robust and should be compatible to the systems.
The integration should be developed as a service . Soon we should be seeing the rise of this integration as a service (IPaaS )
As the saying goes, “You cannot put new wine in old wineskins.” If you do, the wineskins burst. That’s exactly what is happening with companies who are trying to use legacy in ETL (Extract, Transform, and Load) technology to process and provision data in today’s interwoven world of data. Modernizing Data Integration is the need of the hour to accommodate New Big Data and New Business Requirements. Soon the Legacy systems won’t be our Legacy anymore.